Authors:
Sebastijan Šprager
;
Aleš Holobar
and
Damjan Zazula
Affiliation:
University of Maribor and Faculty of Electrical Engineering and Computer Science, Slovenia
Keyword(s):
Heat Rate Estimation, Optical Interferometer, Unobtrusive Monitoring of Human Vital Signs, Biomedical Signal Processing, Latent Variable Analysis, Convolution Kernel Compensation.
Related
Ontology
Subjects/Areas/Topics:
Applications and Services
;
Biomedical Engineering
;
Biomedical Signal Processing
;
Computer Vision, Visualization and Computer Graphics
;
Detection and Identification
;
Medical Image Detection, Acquisition, Analysis and Processing
;
Monitoring and Telemetry
Abstract:
In this paper, a feasibility of detecting heartbeat from optical interferometric signal by using convolution kernel compensation (CKC) latent variable analysis (LVA) approach is examined. Optical interferometer is a very sensitive device that detects physical elongation of the optical fibre. When used as bed or body sensor, mechanical and audible activity of the heart produce perturbations in the detected signal that, when extracted by LVA, allows completely unobtrusive monitoring of heartbeat. We performed an experiment with fourteen young healthy participants. They exercised on a cycle ergometer until they reached their submaximal heart rate (85 % of maximal heart rate). During resting period after the exercise optical interferometric signal was acquired along with the referential ECG signal. CKC-based decomposition of 1-minute-long signal segments was performed. The obtained efficiency (sensitivity of 97.8 ± 3.0 %, precision of 93.6 ± 7.6 %) and accuracy (reference-to-detected bea
t delay of 167 ± 65 ms) are within acceptable limits indicating that unobtrusive heartbeat detection using the proposed approach is feasible.
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