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Photoplethysmographic Time-Domain Heart Rate Measurement Algorithm for Resource-Constrained Wearable Devices and its Implementation

机译:资源受限可穿戴设备的光电容积描记法时域心率测量算法及其实现

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摘要

This paper presents an algorithm for the measurement of the human heart rate, using photoplethysmography (PPG), i.e., the detection of the light at the skin surface. The signal from the PPG sensor is processed in time-domain; the peaks in the preprocessed and conditioned PPG waveform are detected by using a peak detection algorithm to find the heart rate in real time. Apart from the PPG sensor, the accelerometer is also used to detect body movement and to indicate the moments in time, for which the PPG waveform can be unreliable. This paper describes in detail the signal conditioning path and the modified algorithm, and it also gives an example of implementation in a resource-constrained wrist-wearable device. The algorithm was evaluated by using the publicly available PPG-DaLia dataset containing samples collected during real-life activities with a PPG sensor and accelerometer and with an ECG signal as ground truth. The quality of the results is comparable to the other algorithms from the literature, while the required hardware resources are lower, which can be significant for wearable applications.
机译:本文提出了一种使用光体积描记法(PPG)来测量人心率的算法,即检测皮肤表面的光。 PPG传感器发出的信号在时域中处理。通过使用峰值检测算法实时检测心率,可以检测预处理和调节后的PPG波形中的峰值。除PPG传感器外,加速度计还用于检测人体运动并指示PPG波形可能不可靠的时刻。本文详细描述了信号调理路径和改进的算法,并给出了在资源受限的腕戴式设备中的实现示例。通过使用公共可用的PPG-DaLia数据集对算法进行评估,该数据集包含在实际活动中使用PPG传感器和加速度计以及以ECG信号作为地面真实情况收集的样本。结果的质量可与文献中的其他算法相媲美,而所需的硬件资源则较低,这对于可穿戴应用而言可能非常重要。

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