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  • 1.
    Espinilla, Macarena
    et al.
    Department of Computer Science, University of Jaén, Jaén, Spain.
    Medina, Javier
    Department of Computer Science, University of Jaén, Jaén, Spain.
    Hallberg, Josef
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Nugent, Chris
    School of Computing and Mathematics, Ulster University, Coleraine, UK.
    A new approach based on temporal sub-windows for online sensor-based activity recognition2018Ingår i: Journal of Ambient Intelligence and Humanized Computing, ISSN 1868-5137, E-ISSN 1868-5145Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Usually, approaches driven by data proposed in literature for sensor-based activity recognition use the begin label and the end label of each activity in the dataset, fixing a temporal window with sensor data events to identify the activity carried out in this window. This type of approach cannot be carried out in real time because it is not possible to predict the start time of an activity, i.e., the class of the future activity that an inhabitant will perform, neither when he/she will begin to carry out this activity. However, an activity can be marked as finished in real time only with the previous observations. Therefore, there is a need of online activity recognition approaches that classify activities using only the end label of the activity. In this paper, we propose and evaluate a new approach for online activity recognition with three temporal sub-windows that uses only the end label of the activity. The advantage of our approach is that the temporal sub-windows keep a partial order in the sensor data stream from the end time of the activity in a short-term, medium-term, long-term. The experiments conducted to evaluate our approach suggest the importance of the use of temporal sub-windows versus a single temporal window in terms of accuracy, using only the end time of the activity. The use of temporal sub-windows has improved the accuracy in the 98.95% of experiments carried out.

  • 2.
    Cruciani, Frederico
    et al.
    Computer Science Research Institute, Ulster University, Newtownabbey BT370QB, UK.
    Cleland, Ian
    Computer Science Research Institute, Ulster University, Newtownabbey BT370QB, UK.
    Nugent, Chris
    Computer Science Research Institute, Ulster University, Newtownabbey BT370QB, UK.
    McCullagh, Paul
    Computer Science Research Institute, Ulster University, Newtownabbey BT370QB, UK.
    Synnes, Kåre
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Hallberg, Josef
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Automatic annotation for human activity recognition in free living using a smartphone2018Ingår i: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 18, nr 7, artikel-id 2203Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Data annotation is a time-consuming process posing major limitations to the development of Human Activity Recognition (HAR) systems. The availability of a large amount of labeled data is required for supervised Machine Learning (ML) approaches, especially in the case of online and personalized approaches requiring user specific datasets to be labeled. The availability of such datasets has the potential to help address common problems of smartphone-based HAR, such as inter-person variability. In this work, we present (i) an automatic labeling method facilitating the collection of labeled datasets in free-living conditions using the smartphone, and (ii) we investigate the robustness of common supervised classification approaches under instances of noisy data. We evaluated the results with a dataset consisting of 38 days of manually labeled data collected in free living. The comparison between the manually and the automatically labeled ground truth demonstrated that it was possible to obtain labels automatically with an 80–85% average precision rate. Results obtained also show how a supervised approach trained using automatically generated labels achieved an 84% f-score (using Neural Networks and Random Forests); however, results also demonstrated how the presence of label noise could lower the f-score up to 64–74% depending on the classification approach (Nearest Centroid and Multi-Class Support Vector Machine).

  • 3.
    Cleland, Ian
    et al.
    Ulster University.
    Donnelly, Mark
    Ulster University.
    Nugent, Chris
    Ulster University.
    Hallberg, Josef
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Espinilla, Macarena
    University of Jaen.
    García-Constantino, Matías
    Ulster University.
    Collection of a Diverse, Naturalistic and Annotated Dataset for Wearable Activity Recognition2018Ingår i: 2018 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops), IEEE, 2018, s. 555-560Konferensbidrag (Refereegranskat)
    Abstract [en]

    This paper discusses the opportunities and challenges associated with the collection of a large scale, diverse dataset for Activity Recognition. The dataset was collected by 141 undergraduate students, in a controlled environment. Students collected triaxial accelerometer data from a wearable accelerometer whilst each carrying out 3 of the 18 investigated activities, categorized into 6 scenarios of daily living. This data was subsequently labelled, anonymized and uploaded to a shared repository. This paper presents an analysis of data quality, through outlier detection and assesses the suitability of the dataset for the creation and validation of Activity Recognition models. This is achieved through the application of a range of common data driven machine learning approaches. Finally, the paper describes challenges identified during the data collection process and discusses how these could be addressed. Issues surrounding data quality, in particular, identifying and addressing poor calibration of the data were identified. Results highlight the potential of harnessing these diverse data for Activity Recognition. Based on a comparison of six classification approaches, a Random Forest provided the best classification (F-measure: 0.88). In future data collection cycles, participants will be encouraged to collect a set of “common” activities, to support generation of a larger homogeneous dataset. Future work will seek to refine the methodology further and to evaluate model on new unseen data.

  • 4.
    Cleland, I.
    et al.
    School of Computing, Ulster University, Co. Antrim, Northern Ireland, United Kingdom.
    Donnelly, M.P.
    School of Computing, Ulster University, Co. Antrim, Northern Ireland, United Kingdom.
    Nugent, C.D:
    School of Computing, Ulster University, Co. Antrim, Northern Ireland, United Kingdom.
    Hallberg, Josef
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Espinilla, M.
    Department of Computer Science, University of Jaen, Jaen, Spain.
    Garcia-Constantino, M.
    School of Computing, Ulster University, Co. Antrim, Northern Ireland, United Kingdom.
    Collection of a Diverse, Realistic and Annotated Dataset for Wearable Activity Recognition2018Ingår i: 2018 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2018, IEEE, 2018, s. 555-560, artikel-id 8480322Konferensbidrag (Refereegranskat)
    Abstract [en]

    This paper discusses the opportunities and challenges associated with the collection of a large scale, diverse dataset for Activity Recognition. The dataset was collected by 141 undergraduate students, in a controlled environment. Students collected triaxial accelerometer data from a wearable accelerometer whilst each carrying out 3 of the 18 investigated activities, categorized into 6 scenarios of daily living. This data was subsequently labelled, anonymized and uploaded to a shared repository. This paper presents an analysis of data quality, through outlier detection and assesses the suitability of the dataset for the creation and validation of Activity Recognition models. This is achieved through the application of a range of common data driven machine learning approaches. Finally, the paper describes challenges identified during the data collection process and discusses how these could be addressed. Issues surrounding data quality, in particular, identifying and addressing poor calibration of the data were identified. Results highlight the potential of harnessing these diverse data for Activity Recognition. Based on a comparison of six classification approaches, a Random Forest provided the best classification (F-measure: 0.88). In future data collection cycles, participants will be encouraged to collect a set of 'common' activities, to support generation of a larger homogeneous dataset. Future work will seek to refine the methodology further and to evaluate model on new unseen data.

  • 5.
    Kostenius, Catrine
    et al.
    Luleå tekniska universitet, Institutionen för hälsovetenskap, Hälsa och rehabilitering.
    Hallberg, Josef
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Lindqvist, Anna-Karin
    Luleå tekniska universitet, Institutionen för hälsovetenskap, Hälsa och rehabilitering.
    Gamification of health education: Schoolchildren’s participation in the development of a serious game to promote health and learning2018Ingår i: Health Education, ISSN 0965-4283, E-ISSN 1758-714X, Vol. 118, nr 4, s. 354-368Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Purpose

    The use of modern technology has many challenges and risks. However, by collaborating with schoolchildren, ideas to effectively promote health and learning in school can be identified. This study aimed to examine how a participatory approach can deepen the understanding of how schoolchildren relate to and use gamification as a tool to promote physical activity and learning.

    Design/methodology/approach

    Inspired by the concept and process of empowerment and child participation, the methodological focus of this study was on consulting schoolchildren. During a 2-month period, 18 schoolchildren (10–12-years-old) participated in workshops to create game ideas that would motivate them to be physically active and learn in school.

    Findings

    The phenomenological analysis resulted in one main theme, ‘Playing games for fun to be the best I can be’. This consisted of four themes with two sub-themes each. The findings offer insights on how to increase physical activity and health education opportunities using serious games in school.

    Originality/value

    The knowledge gained provides gamification concepts and combinations of different technological applications to increase health and learning, as well as motivational aspects suggested by the schoolchildren. The findings are discussed with health promotion and health education in mind.

  • 6.
    Synnes, Kåre
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Lilja, Margareta
    Luleå tekniska universitet, Institutionen för hälsovetenskap, Hälsa och rehabilitering.
    Nyman, Anneli
    Luleå tekniska universitet, Institutionen för hälsovetenskap, Hälsa och rehabilitering.
    Espinilla, Macarena
    Cleland, Ian
    Sanchez Comas, Andres Gabriel
    Comas Gonzalez, Zhoe Vanessa
    Hallberg, Josef
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Signaler och system. Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Karvonen, Niklas
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Ourique de Morais, Wagner
    Cruciani, Federico
    Nugent, Chris
    H2Al - The Human Health and Activity Laboratory2018Ingår i: 12th International Conference on Ubiquitous Computing and Ambient ‪Intelligence (UCAmI 2018), Punta Cana, Dominican Republic, 4-7 December, 2018. / [ed] MDPI, MDPI, 2018, Vol. 2, artikel-id 1241Konferensbidrag (Refereegranskat)
    Abstract [en]

    The Human Health and Activity Laboratory (H2Al) is a new research facility at Luleå University of Technology implemented during 2018 as a smart home environment in an educational training apartment for nurses and therapists at the Luleå campus. This paper presents the design and implementation of the lab together with a discussion on potential impact. The aim is to identify and overcome economical, technical and social barriers to achieve an envisioned good and equal health and welfare within and from home environments. The lab is equipped with multiple sensor and actuator systems in the environment, worn by persons and based on digital information. The systems will allow for advanced capture, filtering, analysis and visualization of research data such as A/V, EEG, ECG, EMG, GSR, respiration and location while being able to detect falls, sleep apnea and other critical health and wellbeing issues. The resulting studies will be aimed towards supporting and equipping future home environments and care facilities, spanning from temporary care to primary care at hospitals, with technologies for activity and critical health and wellness issue detection. The work will be conducted at an International level and within a European context, based on a collaboration with other smart labs, such that experiments can be replicated at multiple sites. This paper presents some initial lessons learnt including design, setup and configuration for comparison of sensor placements and configurations as well as analytical methods.

  • 7.
    Cruciani, Federico
    et al.
    Ulster University.
    Cleland, Ian
    Ulster University.
    Nugent, Chris
    Ulster University.
    McCullagh, Paul
    Ulster University.
    Synnes, Kåre
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Hallberg, Josef
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Personalized Online Training for Physical Activity monitoring using weak labels2018Ingår i: 2018 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops), IEEE, 2018, s. 567-572Konferensbidrag (Refereegranskat)
    Abstract [en]

    The use of smartphones for activity recognition is becoming common practice. Most approaches use a single pretrained classifier to recognize activities for all users. Research studies, however, have highlighted how a personalized trained classifier could provide better accuracy. Data labeling for ground truth generation, however, is a time-consuming process. The challenge is further exacerbated when opting for a personalized approach that requires user specific datasets to be labeled, making conventional supervised approaches unfeasible. In this work, we present early results on the investigation into a weakly supervised approach for online personalized activity recognition. This paper describes: (i) a heuristic to generate weak labels used for personalized training, (ii) a comparison of accuracy obtained using a weakly supervised classifier against a conventional ground truth trained classifier. Preliminary results show an overall accuracy of 87% of a fully supervised approach against a 74% with the proposed weakly supervised approach.

  • 8.
    Lindqvist, Anna-Karin
    et al.
    Luleå tekniska universitet, Institutionen för hälsovetenskap, Hälsa och rehabilitering.
    Castelli, Darla
    Kinetic Kidz Lab, Department of Kinesiology and Health Education, University of Texas at Austin, Austin, TX, United States. .
    Hallberg, Josef
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Rutberg, Stina
    Luleå tekniska universitet, Institutionen för hälsovetenskap, Hälsa och rehabilitering.
    The Praise and Price of Pokémon GO: A Qualitative Study of Children's and Parents' Experiences.2018Ingår i: JMIR Serious Games, E-ISSN 2291-9279, Vol. 6, nr 1, artikel-id e1Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Background: Physical activity has multiple health benefits; however, the majority of children around the world do not attain the recommended levels of daily physical activity. Research has shown that the game Pokémon GO has increased the amount of physical activity of players and that the game has the potential to reach populations that traditionally have low levels of physical activity. Therefore, there is a need to understand which game components can promote initial and sustained physical activity. By using a qualitative research approach, it is possible to achieve rich descriptions and enhance a deep understanding of the components promoting physical activity among children in a game such as Pokémon GO.

    Objective: The objective of this study was to explore children’s and parents’ experiences playing Pokémon GO.

    Methods: Eight families comprising 13 children (aged 7-12 years) and 9 parents were selected using purposeful sampling. Data collected using focus groups were analyzed using qualitative latent content analysis.

    Results: The following three themes were revealed: (1) exciting and enjoyable exploration; (2) dangers and disadvantages; and (3) cooperation conquers competition. The first centers around the present and possible future aspects of Pokémon GO that promote physical activity. The second focuses on unwanted aspects and specific threats to safety when playing the game. The third shows that cooperation and togetherness are highly valued by the participants and that competition is fun but less important.

    Conclusions: Components from Pokémon GO could enhance the efficacy of physical activity interventions. Cooperation and exploration are aspects of the game that preferably could be transferred into interventions aimed at promoting children’s physical activity.

  • 9.
    Kikhia, Basel
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Stavropoulos, Thanos G.
    Information Technologies Institute, Centre for Research & Technology Hellas.
    Meditskos, Georgios
    Information Technologies Institute, Centre for Research & Technology Hellas.
    Kompatsiaris, Ioannis
    Information Technologies Institute, Centre for Research & Technology Hellas.
    Hallberg, Josef
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Sävenstedt, Stefan
    Luleå tekniska universitet, Institutionen för hälsovetenskap, Omvårdnad.
    Melander, Catharina
    Luleå tekniska universitet, Institutionen för hälsovetenskap, Omvårdnad.
    Utilizing ambient and wearable sensors to monitor sleep and stress for people with BPSD in nursing homes2018Ingår i: Journal of Ambient Intelligence and Humanized Computing, ISSN 1868-5137, E-ISSN 1868-5145, Vol. 9, nr 2, s. 261-273Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Clinical assessment of behavioral and psychological symptoms of dementia (BPSD) in nursing homes is often based on staff member’s observations and the use of the Neuropsychiatric Inventory-Nursing Home version (NPI-NH) instrument. This requires continuous observation of the person with BPSD, and a lot of effort and manual input from the nursing home staff. This article presents the DemaWare@NH monitoring framework system, which complements traditional methods in measuring patterns of behavior, namely sleep and stress, for people with BPSD in nursing homes. The framework relies on ambient and wearable sensors for observing the users and analytics to assess their conditions. In our proof-of-concept scenario, four residents from two nursing homes were equipped with sleep and skin sensors, whose data is retrieved, processed and analyzed by the framework, detecting and highlighting behavioral problems, and providing relevant, accurate information to clinicians on sleep and stress patterns. The results indicate that structured information from sensors can ease and improve the understanding of behavioral patterns, and, as a consequence, the efficiency of care interventions, yielding a positive impact on the quality of the clinical assessment process for people with BPSD in nursing homes.

  • 10.
    Karvonen, Niklas
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Jimenez, Lara Lorna
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Gomez Simon, Miguel
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Nilsson, Joakim
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, EISLAB.
    Kikhia, Basel
    Faculty of Health and Sport Sciences, University of Agder 4879 Grimstad, Norway.
    Hallberg, Josef
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Classifier Optimized for Resource-constrained Pervasive Systems and Energy-efficiency2017Ingår i: International Journal of Computational Intelligence Systems, ISSN 1875-6891, E-ISSN 1875-6883, Vol. 10, nr 1, s. 1272-1279Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Computational intelligence is often used in smart environment applications in order to determine a user’scontext. Many computational intelligence algorithms are complex and resource-consuming which can beproblematic for implementation devices such as FPGA:s, ASIC:s and low-level microcontrollers. Thesetypes of devices are, however, highly useful in pervasive and mobile computing due to their small size,energy-efficiency and ability to provide fast real-time responses. In this paper, we propose a classi-fier, CORPSE, specifically targeted for implementation in FPGA:s, ASIC:s or low-level microcontrollers.CORPSE has a small memory footprint, is computationally inexpensive, and is suitable for parallel processing.The classifier was evaluated on eight different datasets of various types. Our results show thatCORPSE, despite its simplistic design, has comparable performance to some common machine learningalgorithms. This makes the classifier a viable choice for use in pervasive systems that have limitedresources, requires energy-efficiency, or have the need for fast real-time responses.

  • 11.
    Hedemalm, Emil
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Hallberg, Josef
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Kor, Ah-Lian
    Leeds Beckett University.
    Andersson, Karl
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Pattinson, Colin
    School of Computing, Creative Technologies & Engineering, Leeds Beckett University.
    Promoting green transportation via persuasive games2017Ingår i: International SEEDS Conference 2017: Sustainable Ecological Engineering Design for Society – 13th & 14th September 2017, 2017Konferensbidrag (Refereegranskat)
    Abstract [en]

    It is now widely accepted that human behaviour accounts for a large portion of total global emissions, and thus influences climate change to a large extent (IPCC, 2014). Changing human behaviour when it comes to mode of transportation is one component which could make a difference in the long term. In order to achieve behavioural change, we investigate the use of a persuasive multiplayer game. Transportation mode recognition is used within the game to provide bonuses and penalties to users based on their daily choices regarding transportation. Preliminary results from testers of the game indicate that using games may be successful in causing positive change in user behaviour.

  • 12.
    Karvonen, Niklas
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Kikhia, Basel
    Jimenez, Lara Lorna
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Gomez Simon, Miguel
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Hallberg, Josef
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    A Computationally Inexpensive Classifier Merging Cellular Automata and MCP-Neurons2016Ingår i: Ubiquitous Computing and Ambient Intelligence: 10th International Conference, UCAmI 2016, San Bartolomé de Tirajana, Gran Canaria, Spain, November 29 – December 2, 2016, Part II / [ed] Carmelo R. García, Pino Caballero-Gil, Mike Burmester, Alexis Quesada-Arencibia, Springer, 2016, Vol. 2, s. 368-379Konferensbidrag (Refereegranskat)
    Abstract [en]

    There is an increasing need for personalised and context-aware services in our everyday lives and we rely on mobile and wearable devices to provide such services. Context-aware applications often make use of machine-learning algorithms, but many of these are too complex or resource-consuming for implementation on some devices that are common in pervasive and mobile computing. The algorithm presented in this paper, named CAMP, has been developed to obtain a classifier that is suitable for resource-constrained devices such as FPGA:s, ASIC:s or microcontrollers. The algorithm uses a combination of the McCulloch-Pitts neuron model and Cellular Automata in order to produce a computationally inexpensive classifier with a small memory footprint. The algorithm consists of a sparse binary neural network where neurons are updated using a Cellular Automata rule as the activation function. Output of the classifier is depending on the selected rule and the interconnections between the neurons. Since solving the input-output mapping mathematically can not be performed using traditional optimization algorithms, the classifier is trained using a genetic algorithm. The results of the study show that CAMP, despite its minimalistic structure, has a comparable accuracy to that of more advanced algorithms for the datasets tested containing few classes, while performing poorly on the datasets with a higher amount of classes. CAMP could thus be a viable choice for solving classification problems in environments with extreme demands on low resource consumption

  • 13.
    Kostenius, Catrine
    et al.
    Luleå tekniska universitet, Institutionen för hälsovetenskap, Hälsa och rehabilitering.
    Hallberg, Josef
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Lindqvist, Anna-Karin
    Luleå tekniska universitet, Institutionen för hälsovetenskap, Hälsa och rehabilitering.
    A slice of the win-win game: Swedish schoolchildren’s ideas on gamification to promote physical activity and cognitive ability2016Konferensbidrag (Övrigt vetenskapligt)
  • 14.
    Nugent, Chris
    et al.
    Ulster University.
    Cleland, Ian
    Ulster University.
    Santanna, Anita
    Halmstad University.
    Espinilla, Macarena
    University of Jaén.
    Synnott, Jonathan
    Ulster University.
    Banos, Oresti
    University of Twente.
    Lundström, Jens
    Halmstad Universitet.
    Hallberg, Josef
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Calzada, Alberto
    Ulster University.
    An initiative for the creation of open datasets within pervasive healthcare2016Ingår i: Proceedings of the 10th EAI International Conference onPervasive Computing Technologies for Healthcare: 16-19 May 2016, Cancun, Mexico, ICST, the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering , 2016, s. 318-321Konferensbidrag (Refereegranskat)
    Abstract [en]

    In this paper issues surrounding the collection, annotation, management and sharing of data gathered from pervasive health systems are presented. The overarching motivation for this work has been to provide an approach whereby annotated data sets can be made readily accessible to the research community in an effort to assist the advancement of the state-of-the-art in activity recognition and behavioural analysis using pervasive health systems. Recommendations of how this can be made a reality are presented in addition to the initial steps which have been taken to facilitate such an initiative involving the definition of common formats for data storage and a common set of tools for data processing and visualization.

  • 15.
    Nugent, Chris
    et al.
    School of Computing and Mathematics, Ulster University.
    Synnott, Jonathan
    School of Computing and Mathematics, Ulster University .
    Celeste, Gabrielle
    Dipartimento dell’ingegneria dell’informazione, Universita Politecnica Delle Marche, Ancona, .
    Zhang, Shuai
    School of Computing and Mathematics, Ulster University.
    Espinella, Macarena
    Department of Computer Sciences, University of Jaen, .
    Calzada, Alberto
    School of Computing and Mathematics, Ulster University.
    Lundström, Jens
    School of Information Technology, Halmstad University, Halmstad, Sweden.
    Cleland, Ian
    School of Computing and Mathematics, Ulster University.
    Synnes, Kåre
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Hallberg, Josef
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Spinsante, Susanna
    Dipartimento dell’ingegneria dell’informazione, Universita Politecnica Delle Marche, Ancona.
    Ortiz Barrios, Miguel Angel
    Industrial Engineering Department, Universidad de La Costa CUC, Barranquilla, .
    Improving the Quality of User Generated Data Sets for Activity Recognition2016Ingår i: Ubiquitous Computing and Ambient Intelligence: 10th International Conference, UCAmI 2016, San Bartolomé de Tirajana, Gran Canaria, Spain, November 29 – December 2, 2016, Part II / [ed] Carmelo R. García, Pino Caballero-Gil, Mike Burmester, Alexis Quesada-Arencibia, Springer, 2016, Vol. 2, s. 104-110Konferensbidrag (Refereegranskat)
    Abstract [en]

    It is fully appreciated that progress in the development of data driven approaches to activity recognition are being hampered due to the lack of large scale, high quality, annotated data sets. In an effort to address this the Open Data Initiative (ODI) was conceived as a potential solution for the creation of shared resources for the collection and sharing of open data sets. As part of this process, an analysis was undertaken of datasets collected using a smart environment simulation tool. A noticeable difference was found in the first 1–2 cycles of users generating data. Further analysis demonstrated the effects that this had on the development of activity recognition models with a decrease of performance for both support vector machine and decision tree based classifiers. The outcome of the study has led to the production of a strategy to ensure an initial training phase is considered prior to full scale collection of the data.

  • 16.
    Konstantinidis, Stathis
    et al.
    NORUT Northern research institute.
    Brox, Ellen
    NORUT Northern research institute.
    Kommervold, Per Egil
    NORUT Northern research institute.
    Hallberg, Josef
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Evertsen, Gunn
    NORUT Northern research institute.
    Hirche, Johannes
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Online Social Exergames for Seniors: Pillar of Gamification for Clinical Practice2016Ingår i: Handbook of Research on Holistic Perspectives in Gamification for Clinical Practice, IGI Global, 2016, s. 245-276Kapitel i bok, del av antologi (Refereegranskat)
    Abstract [en]

    The population is getting older, and the resources for care will be even more limited in the future than they are now. There is thus an aim for the society that the seniors can manage themselves as long as possible, while at the same time keeping a high quality of life. Physical activity is important to stay fit, and social contact is important for the quality of life. This chapter aims to provide a state-of-the-art of online social exergames for seniors, providing glimpses of senior users’ opinions and games limitations. The importance of the motivational techniques will be emphasized, as well as the impact that the exergames have to seniors. It will contribute to the book objectives focusing on current state and practice in health games for physical training and rehabilitation and the use of gamification, exploring future opportunities and uses of gamification in eHealth and discussing the respective challenges and limitations.

  • 17.
    Beattie, Mark
    et al.
    Computer Science Research Institute and School of Computing and Mathematics, University of Ulster.
    Hallberg, Josef
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Nugent, Chris D.
    University of Ulster. School of Computing and Mathematics, University of Ulster, Computer Science Research Institute, University of Ulster.
    Synnes, Kåre
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Cleland, Ian
    University of Ulster. School of Computing and Mathematics.
    Lee, Sungyoung
    Ubiquitous Computing Laboratory, Kyung Hee University, Seocheon-dong, Giheung-gu.
    A Collaborative Patient-Carer Interface for Generating Home Based Rules for Self-Management2015Ingår i: Smart Homes and Health Telematics: 12th International Conference, ICOST 2014, Denver, CO, USA, June 25-27, 2014, Revised Papers / [ed] Cathy Bodine; Sumi Helal; Tao Gu; Mounir Mokhtari, New York: Encyclopedia of Global Archaeology/Springer Verlag, 2015, s. 93-102Konferensbidrag (Refereegranskat)
    Abstract [en]

    The wide spread prevalence of mobile devices, the decreasing costs of sensor technologies and increased levels of computational power have all lead to a new era in assistive technologies to support persons with Alzheimer’s disease. There is, however, still a requirement to improve the manner in which the technology is integrated into current approaches of care management. One of the key issues relating to this challenge is in providing solutions which can be managed by non-technically orientated healthcare professionals. Within the current work efforts have been made to develop and evaluate new tools with the ability to specify, in a non-technical manner, how the technology within the home environment should be monitored and under which conditions an alarm should be raised. The work has been conducted within the remit of a collaborative patient-carer system to support self-management for dementia. A visual interface has been developed and tested with 10 healthcare professionals. Results following a post evaluation of system usability have been presented and discussed.

  • 18.
    Hedman, Anders
    et al.
    Kungliga tekniska högskolan, KTH.
    Hallberg, Josef
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Cognitive Endurance for Brain Health: Challenges of Creating an Intelligent Warning System2015Ingår i: Künstliche Intelligenz, ISSN 0933-1875, E-ISSN 1610-1987, Vol. 29, nr 2, s. 123-129Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    During the past few years, the market for apps monitoring traditional health and wellbeing parameters such as heart rate, levels of physical activity and sleep patterns has rapidly expanded. In this paper, we articulate how we are currently engineering an early warning system designed to support long-term brain health, termed cognitive endurance, based on such monitoring. It can be thought of as a rudimentary expert system. It will monitor physical and social activity, stress and sleep patterns and signal when these parameters are such that a person’s cognitive endurance might be at risk. The aim of the system is to guide the user to adopt sustainable behavioral patterns from a cognitive endurance perspective. This paper articulates (1) what we mean by cognitive endurance, (2) how cognitive endurance may be enhanced, (3) our cognitive endurance monitoring platform, (4) our approach to calculating cognitive endurance risk, (5) specific challenges related to our approach and (6) what the long term benefits might be of successively monitoring cognitive endurance

  • 19.
    Muuraiskangas, Salla
    et al.
    Digital Health, VTT Technical Research Centre of Finland.
    Merilahti, Juho
    VTT Technical Research Centre of Finland, Espoo, Digital Health, VTT Technical Research Centre of Finland.
    Immonen, Milla
    Digital Health, VTT Technical Research Centre of Finland.
    Hedman, Anders
    Kungliga tekniska högskolan, KTH, Media Technology and Interaction design, KTH Royal Institute of Technology.
    Hallberg, Josef
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Motivational strategy for a cognitive endurance mHealth application2015Ingår i: 2015 6th International Conference on Information, Intelligence, Systems and Applications: (IISA 2015), Corfu, 6-8 July 2015, Piscataway, NJ: IEEE Communications Society, 2015, artikel-id 7388089Konferensbidrag (Refereegranskat)
    Abstract [en]

    Dementia has become a prevalent problem with our aging population. Dementia is threat to our independence because our independence relies on our cognitive performance. Cognitive performance declines as the years advance but it can and should be nurtured to keep it at sufficient functional level. Even though mobile technology has potential to be the desired low-cost and effective means to healthy living, it requires the driving force, motivation, to actually get the person to the destination. In this paper we present a motivational strategy for mHealth (mobile health) application for cognitive endurance

  • 20.
    Andersson, Karl
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Hallberg, Josef
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Project: PERvasive Computing and COMmunications for sustainable development2015Övrigt (Övrig (populärvetenskap, debatt, mm))
  • 21.
    Kikhia, Basel
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Simon, Miguel Gomez
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Jimenez, Lara Lorna
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Hallberg, Josef
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Karvonen, Niklas
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Synnes, Kåre
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Analyzing Body Movements within the Laban Effort Framework using a Single Accelerometer2014Ingår i: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 14, nr 3, s. 5725-41Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    This article presents a study on analyzing body movements by using a single accelerometer sensor. The investigated categories of body movements belong to the Laban Effort Framework: Strong - Light, Free – Bound and Sudden - Sustained. All body movements were represented by a set of activities used for data collection. The calculated accuracy of detecting the body movements was based on collecting data from a single wireless tri-axial accelerometer sensor. Ten healthy subjects collected data from three body locations (chest, wrist and thigh) simultaneously in order to analyze the locations comparatively. The data was then processed and analyzed using Machine Learning techniques. The wrist placement was found to be the best single location to record data for detecting (Strong – Light) body movements using the Random Forest classifier. The wrist placement was also the best location for classifying (Bound – Free) body movements using the SVM classifier. However, the data collected from the chest placement yielded the best results for detecting (Sudden – Sustained) body movements using the Random Forest classifier. The study shows that the choice of the accelerometer placement should depend on the targeted type of movement. In addition, the choice of the classifier when processing data should also depend on the chosen location and the target movement.

  • 22.
    Hedman, Anders
    et al.
    Kungliga tekniska högskolan, KTH.
    Karvonen, Niklas
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Hallberg, Josef
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Merilahti, Juho
    VTT Technical Research Centre of Finland, Espoo.
    Designing ICT for Health and Wellbeing2014Ingår i: Ambient Assisted Living and Daily Activities: 6th International Work-Conference, IWAAL 2014, Belfast, UK, December 2-5, 2014. Proceedings, Encyclopedia of Global Archaeology/Springer Verlag, 2014, s. 244-251Konferensbidrag (Refereegranskat)
    Abstract [en]

    We are developing a monitoring and coaching app for health and wellbeing based on (1) an allostatic model of adaption combined with (2) behavioural change theory and (3) user-oriented design. The (1) allostatic model comes from stress research and was introduced to explain how human health and wellbeing can be maintained. It suggests that human health and wellbeing is a complex multidimensional phenomenon that needs to be understood holistically. We have used this model to incorporate the dimensions of human health and wellbeing that are key for stress reduction: physical and social activity and sleep. The allostatic model can allow us to understand human health and wellbeing but it does not tell us how to support the behavioural changes needed in order to reach a healthy state of allostasis. For this we rely on (2) theory of behavioural change. This article describes how we have integrated (1-3) into the system design and reports from an initial workshop with users.

  • 23.
    Hallberg, Josef
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Casati, Fabio
    University of Trento.
    Hedman, Anders
    Kungliga tekniska högskolan, KTH.
    Plomp, Johan
    VTT Technical Research Centre of Finland, Espoo.
    Synnes, Kåre
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Mental Wellbeing for Active Healthy Ageing2014Rapport (Övrigt vetenskapligt)
  • 24.
    Kikhia, Basel
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Boytsov, Andrey
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Hallberg, Josef
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Sani, Zaheer ul Hussain
    Luleå tekniska universitet, Institutionen för hälsovetenskap.
    Jonsson, Håkan
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Synnes, Kåre
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Structuring and Presenting Lifelogs based on Location Data2014Ingår i: Pervasive Computing Paradigms for Mental Health: 4th International Symposium, MindCare 2014, Tokyo, Japan, May 8-9, 2014, Revised Selected Papers / [ed] Pietro Cipresso; Alaksandar Matic; Guillaume Lopez, Cham: Encyclopedia of Global Archaeology/Springer Verlag, 2014, s. 133-144Konferensbidrag (Refereegranskat)
    Abstract [en]

    Lifelogging techniques help individuals to log their life and retrieve important events, memories and experiences. Structuring lifelogs is a major challenge in lifelogging systems since the system should present the logs in a concise and meaningful way to the user. In this paper the authors present an approach for structuring lifelogs as places and activities based on location data. The structured lifelogs are achieved using a combination of density-based clustering algorithms and convex hull construction to identify the places of interest. The periods of time where the user lingers at the same place are then identified as possible activities. In addition to structuring lifelogs the authors present an application in which images are associated to the structuring results and presented to the user for reviewing. The system is evaluated through a user study consisting of 12 users, who used the system for 1 day and then answered a survey. The proposed approach in this paper allows automatic inference of information about significant places and activities, which generates structured image-annotated logs of everyday life.

  • 25.
    McDonald, Heather
    et al.
    University of Ulster.
    Nugent, Chris
    University of Ulster.
    Moore, George
    University of Ulster.
    Burns, William
    University of Ulster.
    Hallberg, Josef
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Assessing the Impact of the homeML Format and the homeML Suite within the Research Community2013Ingår i: Journal of universal computer science (Online), ISSN 0948-695X, E-ISSN 0948-6968, Vol. 19, nr 17, s. 2559-2576Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The lack of a standard format to store data generated within the smart environments research domain is limiting the opportunity for researchers to share and reuse datasets. The opportunity to exchange datasets is further hampered due to the lack of an online resource to facilitate this. In our current work we have attempted to resolve these issues through the development of homeML, a proposed format to support the storage and exchange of data generated within a smart environment and the homeML suite, an online tool to support data exchange and reuse. A usability and functionality study performed by 8 unbiased members of the research community is presented and discussed. All participants in the study agreed that the homeML format could address the need for a standard format within this domain. Participants also agreed that the homeML suite would be a useful tool to be available to researchers as they perform experiments in the area of smart environments.

  • 26.
    McDonald, H.A.
    et al.
    University of Ulster. School of Computing and Mathematics.
    Nugent, C.D.
    University of Ulster. School of Computing and Mathematics.
    Hallberg, Josef
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Finlay, D.D.
    University of Ulster. School of Computing and Mathematics.
    Moore, G.
    University of Ulster. School of Computing and Mathematics.
    homeRuleML Version 2.1: a revised and extended version of the homeRuleML concept2013Ingår i: XIII Mediterranean Conference on Medical and Biological Engineering and Computing 2013: MEDICON 2013, 25-28 September 2013, Seville, Spain, Wien: Encyclopedia of Global Archaeology/Springer Verlag, 2013, Vol. IX, s. 1262-1265Konferensbidrag (Refereegranskat)
    Abstract [en]

    As a direct result of the changes in global demographics, a significant amount of research has been undertaken in the area of home based support and healthcare provision, particularly in the direction of smart home environments. When applied to data generated within a smart home environment, decision support rules have the potential to recognise an inhabitant’s behaviour and provide suitable support and assistance when required. homeRuleML is an XML-based format for the storage and exchange of decision support rules generated within smart home environments. In our current work we have extended upon the concepts of homeRuleML and have subsequently developed an improved format. The evolution of homeRuleML from version 1.0 to version 2.1 has been documented within this paper.

  • 27.
    Cleland, Ian
    et al.
    University of Ulster. School of Computing and Mathematics.
    Kikhia, Basel
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Nugent, Chris
    University of Ulster. School of Computing and Mathematics.
    Boytsov, Andrey
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Hallberg, Josef
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Synnes, Kåre
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    McClean, Sally
    Computing and Information Engineering, University of Ulster.
    Finlay, Dewar
    University of Ulster. School of Computing and Mathematics.
    Optimal Placement of Accelerometers for the Detection of Everyday Activities2013Ingår i: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 13, nr 7, s. 9183-9200Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    This article describes an investigation to determine the optimal placement of accelerometers for the purpose of detecting a range of everyday activities. The paper investigates the effect of combining data from accelerometers placed at various bodily locations on the accuracy of activity detection. Eight healthy males participated within the study. Data were collected from six wireless tri-axial accelerometers placed at the chest, wrist, lower back, hip, thigh and foot. Activities included walking, running on a motorized treadmill, sitting, lying, standing and walking up and down stairs. The Support Vector Machine provided the most accurate detection of activities of all the machine learning algorithms investigated. Although data from all locations provided similar levels of accuracy, the hip was the best single location to record data for activity detection using a Support Vector Machine, providing small but significantly better accuracy than the other investigated locations. Increasing the number of sensing locations from one to two or more statistically increased the accuracy of classification. There was no significant difference in accuracy when using two or more sensors. It was noted, however, that the difference in activity detection using single or multiple accelerometers may be more pronounced when trying to detect finer grain activities. Future work shall therefore investigate the effects of accelerometer placement on a larger range of these activities

  • 28.
    McDonald, Heather
    et al.
    University of Ulster.
    Nugent, Chris
    University of Ulster.
    Hallberg, Josef
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Finlay, Dewar
    University of Ulster.
    Moore, George
    University of Ulster.
    Synnes, Kåre
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    The homeML suite: shareable datasets for smart home environments2013Ingår i: Health and Technology, ISSN 2190-7188, E-ISSN 2190-7196, Vol. 3, nr 2, s. 177-193Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The lack of a standard format for storing data generated within the smart environments research domain is limiting the opportunity for researchers to compare and share datasets. The opportunity to re-use and share datasets is also being limited due to lack of an online resource available to researchers. In our current work we attempt to resolve these issues through the creation of homeML, a proposed format for storing and sharing data and the development of the homeML Suite as a means of supporting the use of homeML. Within this article the latest version of homeML, version 2.2 is presented, where the 'annotationDetails' element is introduced. An extended evaluation of the homeML Suite is also discussed. A usability and functionality study was conducted by a number of experienced researchers working within the domain of smart environments. The methodology of both studies is discussed in detail. Each participant's interactions with homeML and the suite of tools is presented, the findings of which have been positive. All participants agreed that the homeML Suite would be a useful tool to be available within the research domain and they would recommend it to their fellow researchers.

  • 29.
    Kikhia, Basel
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Hallberg, Josef
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Visualizing and managing stress through colors and images2013Ingår i: Proceeding: SenseCam '13 Proceedings of the 4th International SenseCam & Pervasive Imaging Conference, New York: ACM Digital Library, 2013, s. 78-79Konferensbidrag (Refereegranskat)
    Abstract [en]

    Stress is a widespread health problem [1] and technical solutions to manage stress are limited. This abstract presents a novel solution for identifying stressful situations using a sensecam and a skin conductance sensor. The presented system brings awareness to the user about emotional reactions in life that she might not always be aware of, and therefore helps people in managing their life to better maintain their wellbeing

  • 30.
    Lindahl, Olof
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Signaler och system.
    Andersson, Britt M.
    Centre for Biomedical Engineering and Physics, Umeå University.
    Lundström, Ronnie J.I.
    Centre for Biomedical Engineering and Physics, Umeå University.
    Hallberg, Josef
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    A triple-helix model for refining biomedical engineering research into spin-off companies for the health care market2012Ingår i: World Congress on Medical Physics and Biological Engineering, May 26-31, 2012, Beijing, China / [ed] Mian Long, Berlin: Encyclopedia of Global Archaeology/Springer Verlag, 2012, s. 2088-2090Konferensbidrag (Refereegranskat)
    Abstract [en]

    Triple-Helix activities at the centre for biomedical engineering and physics (CMTF) have generated growth both in academia at the universities and in the industry in Northern Sweden. Cooperation was built up between the 26 research projects and about 15 established companies in the field of biomedical engineering. The established researcher - owned company for business development of the research results from the CMTF, CMTF Business Development Co Ltd, has so far launched one spin-off company and has 15 new business leads to business develop. The activities have also increased the interest for commercial and entrepreneurship questions among the scientists in the centre. So far a total of seven spin-off companies have resulted from the CMTF-research since the year 2000

  • 31.
    McDonald, Heather A.
    et al.
    University of Ulster. School of Computing and Mathematics.
    Nugent, Chris D.
    University of Ulster. School of Computing and Mathematics.
    Hallberg, Josef
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Finlay, Dewar D.
    University of Ulster. School of Computing and Mathematics.
    Moore, George E.
    University of Ulster. School of Computing and Mathematics.
    An approach for the creation of accessible and shared datasets2012Ingår i: Ubiquitous Computing and Ambient Intelligence: 6th International Conference, Ucami 2012, Vitoria-gasteiz, Spain, December 3-5, 2012, Proceedings / [ed] Jose Bravo ; Diego Lp̤ez-de-ipina ; Francisco Moya, New York: Encyclopedia of Global Archaeology/Springer Verlag, 2012, s. 224-232Konferensbidrag (Refereegranskat)
    Abstract [en]

    Due to the change in global demographics, a significant amount of research is being directed towards developing solutions to monitor and support the ageing as they perform activities of daily living. Research in this area is, however, being limited by the lack of shareable datasets available to support the development and evaluation of data driven activity recognition models. In our current work we have developed a suite of resources in an attempt to establish an openly available data repository where all datasets share a common format for the purposes of data storage. Within this paper the homeML Toolkit and the homeML Repository are presented. Results from a usability study of interactions with the toolkit, conducted by five computer science researchers are presented; the initial findings of which have been encouraging

  • 32.
    Candefjord, Stefan
    et al.
    Chalmers University of Technology.
    Murayama, Yoshinobu
    College of Engineering, Nihon University.
    Nyberg, Morgan
    Hallberg, Josef
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Signaler och system.
    Ramser, Kerstin
    Ljungberg, Börje
    Umeå University, Department of Surgical and Perioperative Science, Urology and Andrology.
    Bergh, Anders
    Department of Medical Biosciences Pathology, Umeå University.
    Lindahl, Olof
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Signaler och system.
    Combining scanning haptic microscopy and fibre optic Raman spectroscopy for tissue characterisation2012Ingår i: Journal of Medical Engineering & Technology, ISSN 0309-1902, E-ISSN 1464-522X, Vol. 36, nr 6, s. 319-327Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The tactile resonance method (TRM) and Raman spectroscopy (RS) are promising for tissue characterisation in vivo. Our goal is to combine these techniques into one instrument, to use TRM for swift scanning, and RS for increasing the diagnostic power. The aim of this study was to determine the classification accuracy, using support vector machines, for measurements on porcine tissue and also produce preliminary data on human prostate tissue. This was done by developing a new experimental setup combining micro-scale TRM — scanning haptic microscopy (SHM) — for assessing stiffness on a micro-scale, with fibre optic RS measurements for assessing biochemical content. We compared the accuracy for using SHM alone versus SHM combined with RS, for different degrees of tissue homogeneity. The cross-validation classification accuracy for healthy porcine tissue types using SHM alone was 65–81%, and when RS was added it was increased to 81–87%. The accuracy for healthy and cancerous human tissue was 67–70% when only SHM was used, and increased to 72–77% for the combined measurements. This shows that the potential for swift and accurate classification of healthy and cancerous prostate tissue is high. This is promising for developing a tool for probing the surgical margins during prostate cancer surgery.

  • 33.
    Rana, Juwel
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Hallberg, Josef
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Signaler och system.
    Synnes, Kåre
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Kristiansson, Johan
    Ericsson.
    Harnessing the cloud for mobile social networking applications2012Ingår i: Evolving developments in grid and cloud computing: advancing research / [ed] Emmanuel Udoh, Hershey, Pa.: Information Science Reference, 2012, Vol. 2, nr 2Kapitel i bok, del av antologi (Refereegranskat)
    Abstract [en]

    The cloud computing model inherently enables information from social networking services (Twitter, Facebook, LinkedIn, etc), context-based systems (location, activity, interests, etc.) and personal applications (call logs, contacts, email, calendar, etc) to be harnessed for multiple purposes. This article presents an agent-based system architecture for semantic and semi-automated applications that utilize the cloud to enrich and simplify communication services, for instance by displaying presence information, prioritizing information, and dynamically managing groups of users. The proposed architecture is based on the concept of aggregated social graphs, which are created from harnessed information about how we communicate. This article also presents challenges in achieving the envisioned architecture and introduces early prototyping results.

  • 34.
    Kikhia, Basel
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Boytsov, Andrey
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Hallberg, Josef
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Sani, Zaheer ul Hussain
    Jonsson, Håkan
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Synnes, Kåre
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Structuring and presenting lifelogs based on location data2012Rapport (Övrigt vetenskapligt)
    Abstract [en]

    Lifelogging techniques help individuals to log their life and retrieve important events, memories and experiences. Structuring lifelogs is a major challenge in lifelogging systems since the system should present the logs in a concise and meaningful way to the user. In this article the authors present a novel approach for structuring lifelogs as places and activities based on location data. The structured lifelogs are achieved using a combination of density-based clustering algorithms and convex hull construction to identify the places of interest. The periods of time where the user lingers at the same place are then identified as possible activities. In addition to structuring lifelogs the authors present an application in which images are associated to the structuring results and presented to the user for reviewing. The proposed approach allows automatic inference of information about significant places and activities, which generates structured image-annotated logs of everyday life.

  • 35.
    McDonald, H.A.
    et al.
    University of Ulster. School of Computing and Mathematics.
    Nugent, C.D.
    University of Ulster. School of Computing and Mathematics.
    Moore, G.
    University of Ulster. School of Computing and Mathematics.
    Finlay, D.D.
    University of Ulster. School of Computing and Mathematics.
    Hallberg, Josef
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Signaler och system.
    A web based tool for storing and visualising data generated within a smart home2011Ingår i: Annual international conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2011: Boston, MA; 30 August -3 September 2011, Piscataway, NJ: IEEE Communications Society, 2011, s. 5303-5306Konferensbidrag (Refereegranskat)
    Abstract [en]

    There is a growing need to re-assess the current approaches available to researchers for storing and managing heterogeneous data generated within a smart home environment. In our current work we have developed the homeML Application; a web based tool to support researchers engaged in the area of smart home research as they perform experiments. Within this paper the homeML Application is presented which includes the fundamental components of the homeML Repository and the homeML Toolkit. Results from a usability study conducted by 10 computer science researchers are presented; the initial results of which have been positive

  • 36.
    Lindahl, Olof
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Signaler och system.
    Andersson, Britt
    Centre for Biomedical Engineering and Physics, Umeå University.
    Lundström, Ronnie
    Centre for Biomedical Engineering and Physics, Umeå University.
    Hallberg, Josef
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Signaler och system.
    Development of spin-off companies for health care from biomedical research results2011Konferensbidrag (Refereegranskat)
  • 37.
    Nugent, Chris D.
    et al.
    School of Computing and Mathematics, Faculty of Computing and Engineering, University of Ulster.
    Finlay, Dewar
    School of Computing and Mathematics, Faculty of Computing and Engineering, University of Ulster.
    Davies, Richard
    School of Computing and Mathematics, Faculty of Computing and Engineering, University of Ulster.
    Donnelly, Mark
    School of Computing and Mathematics, Faculty of Computing and Engineering, University of Ulster.
    Hallberg, Josef
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Signaler och system.
    Black, Norman D.
    School of Computing and Mathematics, Faculty of Computing and Engineering, University of Ulster.
    Craig, David
    Belfast City Hospital/Queen’s University of Belfast.
    Remote healthcare monitoring and assessment2011Ingår i: Technology and Health Care, ISSN 0928-7329, E-ISSN 1878-7401, Vol. 19, nr 4, s. 295-306Artikel i tidskrift (Refereegranskat)
  • 38.
    Kikhia, Basel
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Hallberg, Josef
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Signaler och system.
    Bengtsson, Johan
    InterNIT.
    Sävenstedt, Stefan
    Luleå tekniska universitet, Institutionen för hälsovetenskap, Omvårdnad.
    Synnes, Kåre
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Building digital life stories for memory support2010Ingår i: International Journal of Computers in Healthcare, ISSN 1755-3199, Vol. 1, nr 2, s. 161-176Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The number of persons suffering from dementia is increasing, and there is significant human and economic value to gain by enabling them to keep living independently in their homes. The top priority unmet need is for memory support. This paper introduces context-awareness and life-logging in a system using reminiscence therapy methods, embodied as an ICT memory aid for recording past, current and future activities, which can later be recalled. The tool may help build or maintain episodic memories and self-image, although evidence in this area is lacking. It is designed to also give direct and instrumental support in other priority needs areas. A prototype design is described for a system that is by necessity extremely easy to use, with a touch screen computer in the home and mobile devices for data capture and cognitive support. The main life-log entities associated with the logged activities are places, persons, personal items, and recorded media. Privacy, trust and dignity are key ethical issues.

  • 39.
    Kikhia, Basel
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Bengtsson, Johan
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, CDT.
    Synnes, Kåre
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Sani, Zaheer ul Hussain
    Hallberg, Josef
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Signaler och system.
    Creating digital life stories through activity recognition with image filtering2010Ingår i: Aging friendly technology for health and independence: 8th International Conference on Smart Homes and Health Telematics, ICOST 2010, Seoul, Korea, June 22-24, 2010 ; proceedings / [ed] Yeunsook Lee, Berlin: Encyclopedia of Global Archaeology/Springer Verlag, 2010, s. 203-210Konferensbidrag (Refereegranskat)
    Abstract [en]

    This paper presents two algorithms that enables the MemoryLane system to support persons with mild dementia through creation of digital life stories. The MemoryLane system consists of a Logging Kit that captures context and image data, and a Review Client that recognizes activities and enables review of the captured data. The image filtering algorithm is based on image characteristics such as brightness, blurriness and similarity, and is a central component of the Logging Kit. The activity recognition algorithm is based on the captured contextual data together with concepts of persons and places. The initial results indicate that the MemoryLane system is technically feasible and that activity-based creation of digital life stories for persons with mild dementia is possible.

  • 40.
    Baumgarten, Matthias
    et al.
    University of Ulster.
    Guldenring, Daniel
    University of Ulster.
    Nugent, Chris
    University of Ulster.
    Hallberg, Josef
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Signaler och system.
    Embedding self-awareness into objects of daily life: the smart kettle2010Ingår i: 6th International Conference on Intelligent Environments: IE 2010 : Kuala Lumpur; 19 July 2010 - 21 July 2010, Los Alamitos, Calif, 2010, s. 34-39Konferensbidrag (Refereegranskat)
    Abstract [en]

    Intelligent Environments on varying scales and for different purposes are slowly becoming a reality. In the near future, global smart world infrastructures will become a commodity that will support various activities of daily life at different degrees of realism. Such infrastructures have the potential to offer dedicated, context- and situation-aware information and services by simultaneously providing the next-generation of data collection, execution and service provisioning layers. One key aspect of this vision is the correct monitoring and understanding of how people interact with their environment; how they can actually benefit from the added intelligence; and finally how future services can be improved or better personalized to enhance human environment interaction as a whole. This level of intelligence is of particular relevance in the health and social care domain where person-centric services can be deployed to assist or even enable a person in performing activities of daily living. This paper discusses the concept of embedded self-aware profiles for smart devices that can be used to gain a deeper contextual understanding of their use and also discusses the emergence of a general model of Ambient Intelligence that is based on the collective existence and behavior of such smart devices. Although generic in principle, the proposed concepts have been exemplified by a distinct use case, namely a smart kettle.

  • 41.
    Rana, Juwel
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Hallberg, Josef
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Signaler och system.
    Synnes, Kåre
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Kristiansson, Johan
    Ericsson.
    Harnessing the cloud for mobile social networking applications2010Ingår i: International Journal of Grid and High Performance Computing, ISSN 1938-0259, Vol. 2, nr 2, s. 1-11Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The cloud computing model inherently enables information from social networking services (Twitter, Facebook, LinkedIn, etc), context-based systems (location, activity, interests, etc.) and personal applications (call logs, contacts, email, calendar, etc) to be harnessed for multiple purposes. This article presents an agent-based system architecture for semantic and semi-automated applications that utilize the cloud to enrich and simplify communication services, for instance by displaying presence information, prioritizing information, and dynamically managing groups of users. The proposed architecture is based on the concept of aggregated social graphs, which are created from harnessed information about how we communicate. This article also presents challenges in achieving the envisioned architecture and introduces early prototyping results.

  • 42.
    Nugent, Chris
    et al.
    University of Ulster.
    Finlay, Dewar
    University of Ulster.
    Davies, Richard
    University of Ulster.
    Donnelly, Mark
    University of Ulster.
    Hallberg, Josef
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Signaler och system.
    Black, Norman
    University of Ulster.
    Craig, David
    Belfast City Hospital/Queen’s University of Belfast.
    Remote healthcare monitoring and assessment2010Ingår i: Basic Engineering for Medics and BiologistsUndertitel: An ESEM Primer, Amsterdam: IOS Press, 2010, s. 172-184Kapitel i bok, del av antologi (Övrigt vetenskapligt)
    Abstract [en]

    Remote healthcare monitoring is the process of assessing the well-being of a patient when the patient and their healthcare professional are not located together. Advances in technology, specifically medical devices, sensors and high speed fixed and wireless communication networks have made it possible to bring the assessment process to the patient, as opposed to limiting the assessment to the constraints of hospitals and doctors' surgeries. It is also possible for patients to benefit from expert consultants anywhere in the world and receive their advice, without a face-to-face meeting. We discuss these issues in the context of home based medication management and propose a technical solution using emerging technologies. This uses a base station acting as a reservoir of medication and a means to connect the patient to an Internet based care model. The following details of the system are presented; an Internet portal in the form of a web based interface to support the prescribing of medication; an interface for the pharmacist to support the filling of medication containers; a caregiver's interface that provides a means to assess the patient's adherence to their medication regimen.

  • 43.
    Rana, Juwel
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Kristiansson, Johan
    Hallberg, Josef
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Signaler och system.
    Synnes, Kåre
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    An architecture for mobile social networking applications2009Ingår i: 2009 First International Conference on Computational Intelligence, Modelling and Simulation, (CSSim 2009): Brno, Czech Republic, 7 - 9 September 2009 / [ed] Jiri Kunovský, Piscataway, NJ: IEEE Communications Society, 2009, s. 241-246Konferensbidrag (Refereegranskat)
    Abstract [en]

    Mobile semantic Web provides a new way of developing context-aware social networking applications. Social networking applications are changing the way of communication by using userpsilas context-information. For example, micro-blogging has become a smart way of conveying the current situation and activity by using user context. There is currently a significant difference between using social networking applications on a static computer compared to a mobile device, even if current mobile devices are powerful and have good connectivity. The difference is primarily related to the mobility aspect since the user contexts may change more frequently and the user may not be able to interact with the mobile device. In this paper we identify common characteristics of current social networking applications and how they attract users. Finally, we propose an agent-based system architecture that is based on a distributed platform for developing semantic and semi-automated mobile social networking applications.

  • 44.
    Rana, Juwel
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Kristiansson, Johan
    Hallberg, Josef
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Signaler och system.
    Synnes, Kåre
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Challenges for mobile social networking applications2009Ingår i: Communications Infrastructure. Systems and Applications in Europe: first international ICST conference, EuropeComm 2009, London, UK, August 11-13, 2009 : revised selected papers / [ed] Rashid Mehmood, Berlin: Springer Science+Business Media B.V., 2009, s. 275-285Konferensbidrag (Refereegranskat)
    Abstract [en]

    This paper presents work in progress regarding utilization of social network information for mobile applications. Primarily a number of challenges are identified, such as how to mine data from multiple social networks, how to integrate and consolidate social networks, and how to manage semantic information for mobile applications. The challenges are discussed from a semantic Web perspective using a driving scenario as motivation.The main objective is to enable mobile applications to benefit from semantic information obtained from Web services, mobile devices, or the surrounding environment. The goal is therefore to create a framework that enables integration of semantic information (location, activity, interests, etc) with social network data (from Twitter, FaceBook, LinkedIn, etc) to facilitate intelligent yet easy to use communication tools for individual persons as well as groups of persons. An ultimate goal is to make complex communication simple through utilization of semantic information and social network data for pervasive services in mobile devices.

  • 45. Kikhia, Basel
    et al.
    Hallberg, Josef
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Signaler och system.
    Synnes, Kåre
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Sani, Zaheer ul Hussain
    Context-aware life-logging for persons with mild dementia2009Ingår i: 2009 annual international conference of the IEEE Engineering in Medicine and Biology Society: EMBC 2009 ; Minneapolis, Minnesota, USA, 3 - 6 September 2009, Piscataway, NJ: IEEE Communications Society, 2009, s. 6183-6186Konferensbidrag (Refereegranskat)
    Abstract [en]

    The demands of introducing technology to support independent living is increasing. This is true also for persons suffering from mild dementia who may have difficulties remembering important information, such as activities, numbers, names, objects, faces, and so on. This paper presents a context-aware life-logging system, called MemoryLane, which can support independent living and improve quality of life for persons with mild dementia. The system offers both real time support as well as possibilities to rehearse and recall activities for building episodic memory. This paper also presents a mobile client to be used in MemoryLane, as well as an evaluation of the importance of different data for the purpose of memory recollection.

  • 46.
    Hallberg, Josef
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Signaler och system.
    Nugent, Chris
    University of Ulster. School of Computing and Mathematics.
    Davies, Richard
    University of Ulster. School of Computing and Mathematics.
    Donnelly, Mark
    University of Ulster. School of Computing and Mathematics.
    Localisation of forgotten items using RFID technology2009Ingår i: 2009 9th International Conference on Information Technology and Applications in Biomedicine: ITAB 2009 ; Larnaka, Cyprus, 4 - 7 November 2009 ; [including workshop papers], Piscataway, NJ: IEEE Communications Society, 2009, s. 310-313Konferensbidrag (Refereegranskat)
    Abstract [en]

    The frequency with which items are misplaced increases with age, leading to increased frustration and anxiety especially for those who develop cognitive impairments such as dementia. Providing ICT support to assist with relocating items can significantly contribute to sustain independent living. In this paper we present a method for locating RFID tagged items throughout a home environment. Specifically, items are located by comparing and analysing signal strength, received from tagged items, with that received from anumber of fixed location reference tags. This paper presents experiments which have been performed within a typical living environment using homogeneous and practical placement of reference tags. This is performed to consider the feasibility of RFID positioning in such environments. Results obtained indicate that the approach provides acceptable location estimation in pervasive environments with sparsely placed reference tags, however, further investigation is required to accurately quantify its value

  • 47.
    Hong, Xin
    et al.
    Ulster University.
    Nugent, Chris
    Ulster University.
    Finley, Dewar
    Ulster University.
    Chen, Luke
    Ulster University.
    Davies, Richard
    Ulster University.
    Wang, Haiying
    Ulster University.
    Donnelly, Mark
    Ulster University.
    Zheng, Huiru
    Ulster University.
    Mulvenna, Maurice
    Ulster University.
    Hallberg, Josef
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Synnes, Kåre
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    OpenHome: Approaches to Constructing Sharable Datasets within Smart Homes2009Ingår i: CHI '09: Extended Abstracts on Human Factors in Computing Systems, New York: ACM Digital Library, 2009Konferensbidrag (Refereegranskat)
    Abstract [en]

    In this paper we present our initial efforts to develop approaches for structuring and building openly accessible, scalable, shared home behaviour datasets within smart home communities.

  • 48.
    Hallberg, Josef
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Signaler och system.
    Backlund-Norberg, Mia
    Synnes, Kåre
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Nugent, Chris
    Computer Science Research Institute, University of Ulster.
    Profile management for dynamic groups2009Ingår i: Intelligent Patient Management, Berlin: Encyclopedia of Global Archaeology/Springer Verlag, 2009, s. 297-313Kapitel i bok, del av antologi (Refereegranskat)
    Abstract [en]

    There is a growing need in supporting social networking for groups who often become isolated, such as elders living at home. In a social network people with similar diseases and ailments can find each other and share information to improve their understanding of their illness. Group communication tools can help maintain a virtual social network and provide a base for information retrieval. Nevertheless, they often lack the strengths of the social networking tools and vice versa. Within this work we have developed a new concept called dynamic groups. Dynamic groups make creation, management, and usage of groups for communication and social networking easy. Nevetheless, for this to work the profile management system is required to handle more than just user information, it is required to provide users with control over their data and offer privacy and customisation capabilities. This article presents HomeCom, a model for profile management in dynamic groups. It also presents the solutions for making queries, as well as the solutions for privacy and customisation using multiple profiles and an integrated rule engine.

  • 49.
    Hallberg, Josef
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Signaler och system.
    Kikhia, Basel
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Bengtsson, Johan
    InterNIT.
    Sävenstedt, Stefan
    Luleå tekniska universitet, Institutionen för hälsovetenskap, Omvårdnad.
    Synnes, Kåre
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Reminiscence processes using life-log entities for persons with mild dementia2009Ingår i: Proceedings of the First International Workshop on Reminiscence Systems (RSW-2009): Cambridge, UK, 5 September, 2009, 2009, s. 16-21Konferensbidrag (Refereegranskat)
    Abstract [en]

    In this paper we present the reminiscence process in a prototype memory support tool for persons with mild dementia. The purpose is to promote autonomy for persons with mild dementia by supporting actualization and maintenance of episodic memories, and real-time access to a context-annotated life log.  The main research challenges are defined with a user scenario, Suitable reminiscence methods and memory entitities to reperesent life logs are described, and a preliminary architecture is presented. Finally an early design of a concrete ReviewClient is shown, to solicit feedback on the reminiscence methods, entitites chosen, architecture and the usability of the proposed interface.

  • 50.
    Nugent, Chris
    et al.
    University of Ulster.
    Hong, Xin
    University of Ulster.
    Hallberg, Josef
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Signaler och system.
    Finlay, Dewar
    University of Ulster.
    Synnes, Kåre
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Assessing the impact of individual sensor reliability within smart living environments2008Ingår i: IEEE International Conference onAutomation Science and Engineering: CASE 2008, Piscataway, NJ: IEEE Communications Society, 2008, s. 685-690Konferensbidrag (Refereegranskat)
    Abstract [en]

    The potential of smart living environments to provide a form of independent living for the ageing population is becoming more recognised. These environments are comprised of sensors which are used to assess the state of the environment, some form of information management to process the sensor data and finally a suite of actuators which can be used to change the state of the environment. When providing a form of support which may impinge upon the well being of the end user it is essential that a high degree of reliability can be maintained. Within this paper we present an information management framework to process sensor based data within smart environments. Based on this framework we assess the impact of sensor reliability on the classification of activities of daily living. From this assessment we show how it is possible to identify which sensors within a given set of experiments can be considered to be the most critical and as such consider how this information may be used to propose a set of guidelines which may be adopted for managing sensor reliability from a practical point of view.

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