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首页> 外文期刊>IEEE sensors journal >Robust Heart Rate Monitoring by a Single Wrist-Worn Accelerometer Based on Signal Decomposition
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Robust Heart Rate Monitoring by a Single Wrist-Worn Accelerometer Based on Signal Decomposition

机译:基于信号分解的单个腕带加速度计的强大心率监测

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Monitoring heart rate (HR) by a single wristworn accelerometer would provide many advantages over electrocardiogram (ECG) or photoplethysmography (PPG), such as wearing comfortability, saving power, tiny footprint and automatic motion artifact removal. However, like ECG, accelerometry was mostly implemented on the chest, named seismocardiogram (SCG), and PPG was dominating the wrist worn format. Pulse condition detection in Traditional Chinese Medicine or sphygmography was engineered into a wearable format in this work, and a wrist-worn HR monitor by a single accelerometer was demonstrated. A major limitation of wristworn device is that motion artifacts and noise severely corrupt the signal integrity. In this study, with raw data segments including hundreds of random finger or hand motions, several signal decomposition algorithms were compared, such as independent component analysis (ICA), variable mode decomposition (VMD), wavelet synchrosqueezed transform (WSST), and singular spectrum analysis (SSA), and Kalman smoothing was implemented to track HR continuously. Our method was tested on 20 subjects during random finger tapping or hand swinging. Without knowing properties of noise or motion beforehand or requirement of an extra sensor as reference, our method provides a significant removal of motion artifacts and noise from three-dimensional acceleration signals, with 95% of HR estimation within +/- 8.86 bpm, much longer battery life and better wearing comfort than PPG. It would broaden the working conditions, and thus provide a more holistic assessment of HR during everyday life.
机译:通过单个腕带加速度计监测心率(HR)将提供诸多优于心电图(ECG)或光学仪描绘(PPG),例如穿着舒适性,节省电力,微小的占地面积和自动运动伪影去除。然而,与ECG一样,加速度大部分在胸部上实施,命名为SeisModarcoiogram(SCG),并且PPG占据了腕带的磨损格式。在这项工作中,将脉冲条件检测或血压术中的脉冲术检测成可穿戴格式,并证明了单个加速度计的手腕磨损的HR监视器。腕带设备的一个主要限制是运动伪影和噪声严重破坏了信号完整性。在这项研究中,利用包括数百个随机手指或手动运动的原始数据段,比较了几种信号分解算法,例如独立分量分析(ICA),可变模式分解(VMD),小波同步调节变换(WSST)和奇异谱分析(SSA)和卡尔曼平滑的实施方式持续跟踪HR。我们的方法在随机手指敲击或摇摆时在20个受试者上进行了测试。在不知道噪声或运动的性质预先或需要额外的传感器作为参考的情况下,我们的方法可以显着地去除来自三维加速信号的运动伪影和噪声,95%的HR估计在+/- 8.86bpm内,更长电池寿命和比PPG更好的舒适。它将拓宽工作条件,从而在日常生活期间对人力资源部进行更全面的评估。

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