Jarchi Delaram, Casson Alexander J
Annu Int Conf IEEE Eng Med Biol Soc. 2016 Aug;2016:3155-2158. doi: 10.1109/EMBC.2016.7591398.
This paper presents a new method for estimating the average heart rate from a foot/ankle worn photoplethysmography (PPG) sensor during fast bike activity. Placing the PPG sensor on the lower half of the body allows more energy to be collected from energy harvesting in order to give a power autonomous sensor node, but comes at the cost of introducing significant motion interference into the PPG trace. We present a normalised least mean square adaptive filter and short-time Fourier transform based algorithm for estimating heart rate in the presence of this motion contamination. Results from 8 subjects show the new algorithm has an average error of 9 beats-per-minute when compared to an ECG gold standard.
本文提出了一种在快速骑行活动期间从佩戴于足部/脚踝的光电容积脉搏波描记法（PPG）传感器估计平均心率的新方法。将PPG传感器放置在身体下半部可从能量收集获取更多能量，从而实现功率自主的传感器节点，但代价是会在PPG信号轨迹中引入显著的运动干扰。我们提出了一种基于归一化最小均方自适应滤波器和短时傅里叶变换的算法，用于在存在这种运动干扰的情况下估计心率。8名受试者的结果表明，与心电图金标准相比，新算法的平均误差为每分钟9次心跳。
