Parak Jakub, Uuskoski Maria, Machek Jan, Korhonen Ilkka
BioMediTech Institute, Faculty of Biomedical Sciences and Engineering, Tampere University of Technology, Tampere, Finland.
PulseOn Oy, Espoo, Finland.
JMIR Mhealth Uhealth. 2017 Jul 25;5(7):e97. doi: 10.2196/mhealth.7437.
Wearable sensors enable long-term monitoring of health and wellbeing indicators. An objective evaluation of sensors' accuracy is important, especially for their use in health care.
The aim of this study was to use a wrist-worn optical heart rate (OHR) device to estimate heart rate (HR), energy expenditure (EE), and maximal oxygen intake capacity (VO) during running and to evaluate the accuracy of the estimated parameters (HR, EE, and VO) against golden reference methods.
A total of 24 healthy volunteers, of whom 11 were female, with a mean age of 36.2 years (SD 8.2 years) participated in a submaximal self-paced outdoor running test and maximal voluntary exercise test in a sports laboratory. OHR was monitored with a PulseOn wrist-worn photoplethysmographic device and the running speed with a phone GPS sensor. A physiological model based on HR, running speed, and personal characteristics (age, gender, weight, and height) was used to estimate EE during the maximal voluntary exercise test and VO during the submaximal outdoor running test. ECG-based HR and respiratory gas analysis based estimates were used as golden references.
OHR was able to measure HR during running with a 1.9% mean absolute percentage error (MAPE). VO estimated during the submaximal outdoor running test was closely similar to the sports laboratory estimate (MAPE 5.2%). The energy expenditure estimate (n=23) was quite accurate when HR was above the aerobic threshold (MAPE 6.7%), but MAPE increased to 16.5% during a lighter intensity of exercise.
The results suggest that wrist-worn OHR may accurately estimate HR during running up to maximal HR. When combined with physiological modeling, wrist-worn OHR may be used for an estimation of EE, especially during higher intensity running, and VO even during submaximal self-paced outdoor recreational running.
可穿戴传感器能够对健康和幸福指标进行长期监测。对传感器准确性进行客观评估很重要,尤其是在医疗保健领域的应用。
本研究旨在使用腕戴式光学心率(OHR)设备来估计跑步过程中的心率(HR)、能量消耗(EE)和最大摄氧量(VO),并对照黄金参考方法评估估计参数(HR、EE和VO)的准确性。
共有24名健康志愿者(其中11名女性)参与了次最大强度的自定节奏户外跑步测试以及在体育实验室进行的最大自主运动测试,平均年龄为36.2岁(标准差8.2岁)。使用PulseOn腕戴式光电容积脉搏波描记设备监测OHR,并使用手机GPS传感器监测跑步速度。在最大自主运动测试期间,基于心率、跑步速度和个人特征(年龄、性别、体重和身高)的生理模型用于估计EE;在次最大强度户外跑步测试期间,用于估计VO。基于心电图的心率和基于呼吸气体分析的估计值用作黄金参考。
OHR能够在跑步过程中测量心率,平均绝对百分比误差(MAPE)为1.9%。在次最大强度户外跑步测试期间估计的VO与体育实验室的估计值非常接近(MAPE为5.2%)。当心率高于有氧阈值时,能量消耗估计值(n = 23)相当准确(MAPE为6.7%),但在运动强度较低时,MAPE增加到16.5%。
结果表明,腕戴式OHR在跑步直至最大心率期间可能准确估计心率。当与生理模型相结合时,腕戴式OHR可用于估计EE,尤其是在高强度跑步期间,甚至在次最大强度的自定节奏户外休闲跑步期间也可用于估计VO。