Authors:
Terukazu Akiyama
;
Tatsuya Miyazaki
;
Hiroki Ito
;
Hirofumi Nogami
and
Renshi Sawada
Affiliation:
Kyushu University, Japan
Keyword(s):
MEMS Blood Flowmeter, Heart Rate Variability, Autonomic Nervous System.
Related
Ontology
Subjects/Areas/Topics:
Applications and Services
;
Biomedical Engineering
;
Biomedical Signal Processing
;
Cardiovascular Signals
;
Computer Vision, Visualization and Computer Graphics
;
Devices
;
Health Information Systems
;
Human-Computer Interaction
;
Medical Image Detection, Acquisition, Analysis and Processing
;
Physiological Computing Systems
;
Wearable Sensors and Systems
Abstract:
We investigated the possibility of applying a MEMS blood flowmeter to heart rate variability (HRV) analysis. We conducted simultaneous measurements of HRV by electrocardiogram and MEMS blood flowmeter. TPP for the MEMS blood flowmeter was defined as the interval between peaks, which were designated as where the first-order differential of the signal changes from negative to positive. TRR (i.e., the R-R interval of the electrocardiogram) and TPP were compared by regression analysis. Autonomic indices transformed by power spectrum analysis were also compared by regression analysis. Fast Fourier transform (FFT) and maximum entropy method (MEM) were employed in the frequency analysis. By FFT analysis, the coefficient of determination for the regression between LF%, HF%, and LF/HF derived by TRR versus TPP was 0.8781, 0.8781, and 0.8946, respectively. By MEM analysis, the coefficient of determination for the regression between LF%, HF%, and LF/HF derived by TRR versus TPP was 0.9649, 0.80
26, and 0.9181, respectively. These high correlations suggest that the TPP of the MEMS blood flowmeter is a reliable metric that can be utilized in applications of HRV analysis.
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