DocumentCode :
2978215
Title :
Seismocardiography: Toward heart rate variability (HRV) estimation
Author :
Tadi, Mojtaba Jafari ; Lehtonen, Eero ; Koivisto, Tero ; Pankaala, Mikko ; Paasio, Ari ; Teras, Mika
Author_Institution :
Dept. of Cardiology & Cardiovascular Med., Univ. of Turku, Turku, Finland
fYear :
2015
fDate :
7-9 May 2015
Firstpage :
261
Lastpage :
266
Abstract :
Heart rate variability (HRV), the variation in the beat-to-beat heart rate, is a key indicator of the cardiovascular condition of an individual. The purpose of this study was to cross-validate the beat-by-beat time variations in seismocardiography (SCG) with electrocardiography (ECG) for determining ultra-short term HRV indices. Twenty healthy young volunteers were examined in this study by performing an ultra-short term data acquisition protocol. Kubios HRV software was utilized to assess the HRV parameters. The HRV indices were analyzed in both time-domain and frequency-domain processes. High linear relationship (r>0.98) and agreement was observed between the HRV indexes calculated from SCG and ECG data. In conclusion, SCG and ECG HRV indices were found to be statistically close enough to warrant the use of SCG for estimating HRV.
Keywords :
cardiovascular system; electrocardiography; frequency-domain analysis; medical signal processing; time-domain analysis; ECG data; HRV parameters; Kubios HRV software; SCG data; beat-by-beat time; beat-to-beat heart rate; cardiovascular condition; electrocardiography; frequency-domain processes; heart rate variability estimation; seismocardiography; time-domain processes; ultrashort term HRV indices; ultrashort term data acquisition protocol; Electrocardiography; Estimation; Heart rate variability; Resonant frequency; Software;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Medical Measurements and Applications (MeMeA), 2015 IEEE International Symposium on
Conference_Location :
Turin
Type :
conf
DOI :
10.1109/MeMeA.2015.7145210
Filename :
7145210
Link To Document :
بازگشت