Estimation of Instantaneous Oxygen Uptake During Exercise and Daily Activities Using a Wearable Cardio-Electromechanical and Environmental Sensor.
Estimation of Instantaneous Oxygen Uptake During Exercise and Daily Activities Using a Wearable Cardio-Electromechanical and Environmental Sensor.
复制标题
使用可穿戴式机电和环境传感器估计运动和日常活动期间的瞬时摄氧量。
DOI：
10.1109/jbhi.2020.3009903
复制
发表时间：
2021-03
影响因子：
7.7
通讯作者：
Inan OT
中科院分区：
文献类型：
--
作者：
Shandhi MMH;Bartlett WH;Heller JA;Etemadi M;Young A;Plotz T;Inan OT
在运动和日常活动中使用小型低成本可穿戴传感器估计瞬时摄氧量（VO 2），以便在不受控制的环境中监测能量消耗（EE）。我们的目标是使用从最小干扰的可穿戴设备获得的心震图（SCG）、心电图（ECG）和大气压（AP）信号的组合来实现这一点。在这项研究中，受试者在受控环境中执行跑步机协议，在非受控环境中执行户外步行协议。在测试过程中，COSMED K5代谢系统收集了黄金标准的逐呼吸（BxB）数据，并在胸骨中部放置了一个定制的可穿戴贴片，收集了SCG，ECG和AP信号。我们从这些信号中提取特征来估计从COSMED系统获得的BxB VO 2数据。在估计瞬时VO 2时，我们使用SCG（频率）和AP特征的组合在跑步机方案上获得了最佳结果（RMSE为3.68±0.98 ml/kg/min，R2为0.77）。对于外部协议，我们使用SCG（频率），ECG和AP特征的组合实现了最佳结果（RMSE为4.3±1.47 ml/kg/min，R2为0.64）。在估计VO 2消耗超过一分钟的时间间隔在协议期间，我们的中位数百分比误差为15.8%的跑步机协议和20.5%的外部协议。来自小型可穿戴贴片的SCG、ECG和AP信号可以在受控和非受控设置下准确估计瞬时VO 2。捕获心脏机械过程中变化的SCG信号、AP信号和最先进的机器学习模型对瞬时VO 2的准确估计做出了重大贡献。使用低成本、最小干扰的可穿戴贴片准确估计VO 2可以在日常环境中监测VO 2和EE，并使这些测量的许多应用更容易为公众所用。
To estimate instantaneous oxygen uptake (VO2) with a small, low-cost wearable sensor during exercise and daily activities in order to enable monitoring of energy expenditure (EE) in uncontrolled settings. We aim to do so using a combination of seismocardiogram (SCG), electrocardiogram (ECG) and atmospheric pressure (AP) signals obtained from a minimally obtrusive wearable device. In this study, subjects performed a treadmill protocol in a controlled environment and an outside walking protocol in an uncontrolled environment. During testing, the COSMED K5 metabolic system collected gold standard breath-by-breath (BxB) data and a custom-built wearable patch placed on the mid-sternum collected SCG, ECG and AP signals. We extracted features from these signals to estimate the BxB VO2 data obtained from the COSMED system. In estimating instantaneous VO2, we achieved our best results on the treadmill protocol using a combination of SCG (frequency) and AP features (RMSE of 3.68±0.98 ml/kg/min and R2 of 0.77). For the outside protocol, we achieved our best results using a combination of SCG (frequency), ECG and AP features (RMSE of 4.3±1.47 ml/kg/min and R2 of 0.64). In estimating VO2 consumed over one minute intervals during the protocols, our median percentage error was 15.8% for the treadmill protocol and 20.5% for the outside protocol. SCG, ECG and AP signals from a small wearable patch can enable accurate estimation of instantaneous VO2 in both controlled and uncontrolled settings. SCG signals capturing variation in cardio-mechanical processes, AP signals, and state of the art machine learning models contribute significantly to the accurate estimation of instantaneous VO2. Accurate estimation of VO2 with a low cost, minimally obtrusive wearable patch can enable the monitoring of VO2 and EE in everyday settings and make the many applications of these measurements more accessible to the general public.