Remote sensing of patterns of cardiac activity on an ambulatory subject using millimeter-wave interferometry and statistical methods.
Using a 94-GHz millimeter-wave interferometer, we are able to calculate the relative displacement of an object. When aimed at the chest of a human subject, we measure the minute motions of the chest due to cardiac activity. After processing the data using a wavelet multiresolution decomposition, we...
| Publicado en: | Medical & Biological Engineering & Computing Vol. 51; no. 1/2; pp. 135 - 143 |
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| Autores principales: | , , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Feb2013
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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=104068497&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 104068497 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01400118 PO0 jtl: Medical & Biological Engineering & Computing issn: 01400118 maglogo: N pubinfo: dt: Feb2013 vid: 51 iid: 1/2 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 104068497 NLM23099554 2012019391 10.1007/s11517-012-0977-6 NLM23099554 104068497 ppf: 135 ppct: 8 formats: fmt: @attributes: type: P tig: atl: Remote sensing of patterns of cardiac activity on an ambulatory subject using millimeter-wave interferometry and statistical methods. aug: au: Mikhelson, Ilya V Bakhtiari, Sasan Elmer 2nd, Thomas W Sahakian, Alan V Elmer, Thomas W 2nd affil: Electrical Engineering and Computer Science, Northwestern University, Evanston, IL, 60208, USA, i-mikhelson@u.northwestern.edu. sug: subj: Heart Physiology Interferometry Methods Monitoring, Physiologic Methods Telemetry Methods Statistics Methods Adult Algorithms Electrocardiography Female Heart Rate Physiology Male Middle Age Movement Young Adult Adult: 19-44 years Middle Aged: 45-64 years Female Male ab: Using a 94-GHz millimeter-wave interferometer, we are able to calculate the relative displacement of an object. When aimed at the chest of a human subject, we measure the minute motions of the chest due to cardiac activity. After processing the data using a wavelet multiresolution decomposition, we are able to obtain a signal with peaks at heartbeat temporal locations. In order for these heartbeat temporal locations to be accurate, the reflected signal must not be very noisy. Since there is noise in all but the most ideal conditions, we created a statistical algorithm in order to compensate for unconfident temporal locations as computed by the wavelet transform. By analyzing the statistics of the peak locations, we fill in missing heartbeat temporal locations and eliminate superfluous ones. Along with this, we adapt the processing procedure to the current signal, as opposed to using the same method for all signals. With this method, we are able to find the heart rate of ambulatory subjects without any physical contact. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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