TY - GEN
T1 - Application of a MEMS blood flowmeter for power spectrum analysis of heart rate variability
AU - Akiyama, Terukazu
AU - Miyazaki, Tatsuya
AU - Ito, Hiroki
AU - Nogami, Hirofumi
AU - Sawada, Renshi
N1 - Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2015
Y1 - 2015
N2 - 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, 0.8026, 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.
AB - 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, 0.8026, 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.
UR - http://www.scopus.com/inward/record.url?scp=84938880391&partnerID=8YFLogxK
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U2 - 10.5220/0005213302110218
DO - 10.5220/0005213302110218
M3 - Conference contribution
AN - SCOPUS:84938880391
T3 - BIOSIGNALS 2015 - 8th International Conference on Bio-Inspired Systems and Signal Processing, Proceedings; Part of 8th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2015
SP - 211
EP - 218
BT - BIOSIGNALS 2015 - 8th International Conference on Bio-Inspired Systems and Signal Processing, Proceedings; Part of 8th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2015
A2 - Loose, Harald
A2 - Fred, Ana
A2 - Gamboa, Hugo
A2 - Elias, Dirk
PB - SciTePress
T2 - 8th International Conference on Bio-Inspired Systems and Signal Processing, BIOSIGNALS 2015
Y2 - 12 January 2015 through 15 January 2015
ER -