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Title
Japanese: 
English:Lightweight and High Accurate RR Interval Compensation for Signals from Wearable ECG Sensors 
Author
Japanese: 橋本優生.  
English: Yuki Hashimoto.  
Language English 
Journal/Book name
Japanese: 
English:IEEE Sensors Letters 
Volume, Number, Page         pp. 1-4
Published date May 8, 2024 
Publisher
Japanese: 
English:IEEE 
Conference name
Japanese: 
English: 
Conference site
Japanese: 
English: 
Official URL https://ieeexplore.ieee.org/abstract/document/10522897
 
DOI https://doi.org/10.1109/LSENS.2024.3398251
Abstract This paper presents a new lightweight and high accurate RR intervals (RRIs) compensation technique suitable for wearable electrocardiogram (ECG) sensors. RRIs are among the important features of ECG signals and are thus widely used in medical and healthcare applications, and their estimation is commonly implemented in wearable ECG sensors. The data sampling rate is one of the factors influencing on the RRI accuracy from ECG signals acquired by wearable sensors. However, in wearable sensors, high sampling rates consume substantial electrical power, leading to a trade-off between power consumption and RRI accuracy. A spline interpolation is one of the conventional compensation methods obtaining high-resolution RRI at low sampling rates. However, the method requires heavy computational processing for high-order interpolation. Therefore, a method that achieves highly accurate RRI interpolation with lightweight computational processing is desirable for low power consumption in wearable measurement. Here, we developed a novel lightweight and high-accurate RRI compensation method suitable for wearable ECG sensors. The method is specifically designed for algorithms commonly used for R wave detection in wearable ECG sensors. Validation results using simulated ECG signals confirm that the proposed method enables accurate RRI estimation for sampling rates ranging from 50 to 1000 samples/s, demonstrating superior performance compared to the conventional cubic spline interpolation. Furthermore, the proposed method was confirmed to meet the accuracy requirements for heart rate variability analysis even at a low sampling rate of 66.7 samples/s. In addition, the effectiveness of the proposed method was experimentally confirmed during specific actions with various motion artifacts. These results demonstrate the effectiveness of the proposed method for RRI compensation in wearable ECG sensors. With the future introduction of wearable ECG devices, we expect our method to provide a needed balance between low power consumption and high resolution.

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