Presentation information

Organized Session

Organized Session » OS-5

[3I3-OS-5a] 生体信号を活用した医療・ヘルスケアAI(1/2)

Thu. Jun 16, 2022 1:30 PM - 3:10 PM Room I (Room I)

オーガナイザ:藤原 幸一(名古屋大学)[現地]、久保 孝富(奈良先端科学技術大学院大学)

1:50 PM - 2:10 PM

[3I3-OS-5a-02] A Study of Automatic Selection Algorithm for Optimal Attachment Position of Patch Type Wireless R-R Interval Telemeter

〇Aoi Noguchi1, Tomoyuki Takano1, Toshitaka Yamakawa1 (1. Kumamoto University)

Keywords:HRV, ECG, Optimal position selection algorithm

Heart rate variability (HRV) is an indicator of changes in the interval between continuous R waves (R-R interval; RRI) on the electrocardiogram (ECG) caused by autonomic nervous system activity. Measurement of the RRI is useful for detecting diseases related to autonomic nervous system activity and for predicting seizures. This study aimed to improve a heart rate measurement system that combines a highly accurate, compact, and inexpensive patch-type R-R interval telemeter and a smartphone application that automatically selects a suitable measurement position for non-experts. To evaluate the measurement accuracy, RRIs of 10 healthy male and 10 healthy female subjects in four postures (supine, sitting, standing, and walking (3 km/h)) were measured simultaneously using the system and a reference ECG measurement system, and the results were compared. R-wave detection rate and Bland-Altman analysis analyzed the measurement accuracy of this system. The accuracy showed the measurement accuracy was sufficient for HRV analysis.

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