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Sparse Coding of Cardiac Signals for Automated Component Selection after Blind Source Separation
Institute of Biomedical Engineering, TU Dresden.
Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.ORCID-id: 0000-0002-6032-6155
Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.ORCID-id: 0000-0003-0069-640X
Institute of Biomedical Engineering, TU Dresden.
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Antal upphovsmän: 62016 (Engelska)Ingår i: Computing in cardiology, ISSN 2325-8861, E-ISSN 2325-887X, Vol. 43, s. 785-788, artikel-id 7868860Artikel i tidskrift (Refereegranskat) Published
Abstract [en]

Wearable sensor technology like textile electrodes provides novel ambulatory health monitoring solutions but most often goes along with low signal quality. Blind Source Separation (BSS) is capable of extracting the Electrocardiogram (ECG) out of heavily distorted multichannel recordings. However, permutation indeterminacy has to be solved, i.e. the automated selection of the desired BSS output. Accordingly, we exploit the sparsity of the ECG modeled as a spike train of successive heartbeats. A binary code derived from a two-item dictionary fpeak, no peakg and physiological a-priori information temporally represents every BSS output component. The (best) ECG component is automatically selected based on a modified Hamming distance comparing the components’ code with the expected code behavior. Non-standard ECG recordings from ten healthy subjects performing common motions while wearing a sensor garment were subsequently processed in 10 s segments with spatio-temporal BSS. Our sparsity-based selection RCODE achieved 98.1% heart beat detection accuracy (ACC) by selecting a single component each after BSS. Traditional component selection based on higher-order statistics (e.g. skewness) achieved only 67.6% ACC.

Ort, förlag, år, upplaga, sidor
2016. Vol. 43, s. 785-788, artikel-id 7868860
Nationell ämneskategori
Datavetenskap (datalogi)
Forskningsämne
Kommunikations- och beräkningssystem
Identifikatorer
URN: urn:nbn:se:ltu:diva-30791ISI: 000405710400197Lokalt ID: 4bd094ff-5500-4fe0-8625-c36cf20b2916OAI: oai:DiVA.org:ltu-30791DiVA, id: diva2:1004020
Konferens
43rd Computing in Cardiology Conference (CinC), Vancouver, 11-14 September 2016
Anmärkning

2017-03-27 (andbra);Konferensartikel i tidskrift

Tillgänglig från: 2016-09-30 Skapad: 2016-09-30 Senast uppdaterad: 2019-10-10Bibliografiskt granskad

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http://www.cinc2016.org/images/ProgramWithAbstracts.pdf

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Kleyko, DenisOsipov, Evgeny

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