Separation of Doppler radar-based respiratory signatures.
Respiration detection using microwave Doppler radar has attracted significant interest primarily due to its unobtrusive form of measurement. With less preparation in comparison with attaching physical sensors on the body or wearing special clothing, Doppler radar for respiration detection and monito...
| Publicado en: | Medical & Biological Engineering & Computing Vol. 54; no. 8; pp. 1169 - 1180 |
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| Autores principales: | , , , , , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Aug2016
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=117360504&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 117360504 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01400118 PO0 jtl: Medical & Biological Engineering & Computing issn: 01400118 maglogo: N pubinfo: dt: Aug2016 vid: 54 iid: 8 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 117360504 117360504 NLM26358241 10.1007/s11517-015-1379-3 NLM26358241 117360504 ppf: 1169 ppct: 11 formats: fmt: @attributes: type: P tig: atl: Separation of Doppler radar-based respiratory signatures. aug: au: Lee, Yee Pathirana, Pubudu Evans, Robin Steinfort, Christopher Lee, Yee Siong Pathirana, Pubudu N Evans, Robin J Steinfort, Christopher L affil: School of Engineering , Deakin University , Geelong Australia sug: subj: Telemetry Equipment and Supplies Respiration Monitoring, Physiologic Equipment and Supplies Signal Processing, Computer Assisted Telecommunications Equipment Design Algorithms Microwaves Scales ab: Respiration detection using microwave Doppler radar has attracted significant interest primarily due to its unobtrusive form of measurement. With less preparation in comparison with attaching physical sensors on the body or wearing special clothing, Doppler radar for respiration detection and monitoring is particularly useful for long-term monitoring applications such as sleep studies (i.e. sleep apnoea, SIDS). However, motion artefacts and interference from multiple sources limit the widespread use and the scope of potential applications of this technique. Utilising the recent advances in independent component analysis (ICA) and multiple antenna configuration schemes, this work investigates the feasibility of decomposing respiratory signatures into each subject from the Doppler-based measurements. Experimental results demonstrated that FastICA is capable of separating two distinct respiratory signatures from two subjects adjacent to each other even in the presence of apnoea. In each test scenario, the separated respiratory patterns correlate closely to the reference respiration strap readings. The effectiveness of FastICA in dealing with the mixed Doppler radar respiration signals confirms its applicability in healthcare applications, especially in long-term home-based monitoring as it usually involves at least two people in the same environment (i.e. two people sleeping next to each other). Further, the use of FastICA to separate involuntary movements such as the arm swing from the respiratory signatures of a single subject was explored in a multiple antenna environment. The separated respiratory signal indeed demonstrated a high correlation with the measurements made by a respiratory strap used currently in clinical settings. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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