In this paper we study the prediction of heart rate from acceleration using a wrist worn wearable. Although existing photoplethysmography (PPG) heart rate sensors provide reliable measurements, they use considerably more energy than accelerometers and have a major impact on battery life of wearable devices. By using energy-efficient accelerometers to predict heart rate, significant energy savings can be made. Further, we are interested in understanding patient recovery after a heart rate intervention, where we expect a variation in heart rate over time. Therefore, we propose an online approach to tackle the concept as time passes. We evaluate the methods on approximately 4 weeks of free living data from three patients over a number of months. We show that our approach can achieve good predictive performance (e.g., 2.89 Mean Absolute Error) while using the PPG heart rate sensor infrequently (e.g., 20.25% of the samples).

本研究探讨使用手腕佩戴式可穿戴设备从加速度中预测心率，通过能量高效的加速度计实现较大的节能，同时使用在线方法了解心率变化以及患者康复，结果显示我们的方法可以在较少使用心率传感器（例如样本的20.25%）的情况下实现良好的预测性能（如2.89的平均绝对误差）以及很好的患者康复情况.

利用手腕佩戴可穿戴设备的加速度进行在线心率预测