Laboratory of Welfare Technologies-Telehealth & Telerehabilitation, SMI, Department of Health Science and Technology, Aalborg University, Aalborg 9100, Denmark.
Medical Informatics Group, Department of Health Science and Technology, Aalborg University, Aalborg 9100, Denmark.
Sensors (Basel). 2017 Jan 22;17(1):211. doi: 10.3390/s17010211.
Commercial self-monitoring devices are becoming increasingly popular, and over the last decade, the use of self-monitoring technology has spread widely in both consumer and medical markets. The purpose of this study was to evaluate five commercially available self-monitoring devices for further testing in clinical applications. Four activity trackers and one sleep tracker were evaluated based on step count validity and heart rate validity.
The study enrolled 22 healthy volunteers in a walking test. Volunteers walked a 100 m track at 2 km/h and 3.5 km/h. Steps were measured by four activity trackers and compared to gyroscope readings. Two trackers were also tested on nine subjects by comparing pulse readings to Holter monitoring.
The lowest average systematic error in the walking tests was -0.2%, recorded on the Garmin Vivofit 2 at 3.5 km/h; the highest error was the Fitbit Charge HR at 2 km/h with an error margin of 26.8%. Comparisons of pulse measurements from the Fitbit Charge HR revealed a margin error of -3.42% ± 7.99% compared to the electrocardiogram. The Beddit sleep tracker measured a systematic error of -3.27% ± 4.60%.
The measured results revealed the current functionality and limitations of the five self-tracking devices, and point towards a need for future research in this area.
商业自主监测设备正日益普及，在过去十年中，自我监测技术在消费者和医疗市场中得到了广泛应用。本研究旨在评估五款市售自主监测设备，以进一步在临床应用中进行测试。四项活动追踪器和一项睡眠追踪器基于计步准确性和心率准确性进行评估。
本研究招募了 22 名健康志愿者进行步行测试。志愿者以 2 公里/小时和 3.5 公里/小时的速度在 100 米轨道上行走。通过四个活动追踪器测量步数，并与陀螺仪读数进行比较。另外两个追踪器在 9 名受试者身上进行测试，通过将脉搏读数与 Holter 监测进行比较。
在步行测试中，Garmin Vivofit 2 的平均系统误差最低，为-0.2%，在 3.5 公里/小时时记录；在 2 公里/小时时，Fitbit Charge HR 的误差最大，为 26.8%。与心电图相比，Fitbit Charge HR 的脉搏测量比较显示出-3.42%±7.99%的偏差误差。Beddit 睡眠追踪器测量的系统误差为-3.27%±4.60%。
测量结果揭示了这五款自主追踪设备的当前功能和局限性，并指出了该领域未来研究的必要性。
