Calibration and Validation of Wearable Monitors

被引:210
作者
Bassett, David R., Jr. [1 ]
Rowlands, Alex [2 ]
Trost, Stewart G. [3 ]
机构
[1] Univ Tennessee, Knoxville, TN 37919 USA
[2] Univ Exeter, Exeter, Devon, England
[3] Oregon State Univ, Corvallis, OR 97331 USA
基金
美国国家卫生研究院;
关键词
ACCELEROMETER; HR; MOTION SENSOR; PHYSICAL ACTIVITY; ENERGY EXPENDITURE; PATTERN RECOGNITION; ARTIFICIAL NEURAL-NETWORK; ENERGY-EXPENDITURE; PHYSICAL-ACTIVITY; HEART-RATE; ACCELEROMETRY; VALIDITY; MOTION;
D O I
10.1249/MSS.0b013e3182399cf7
中图分类号
G8 [体育];
学科分类号
04 ; 0403 ;
摘要
BASSETT D. R. JR., A. ROWLANDS, and S. G. TROST. Calibration and Validation of Wearable Monitors. Med. Sci. Sports Exerc., Vol. 44, No. 1S, pp. S32-S38, 2012. Background: Wearable monitors are increasingly being used to objectively monitor physical activity in research studies within the field of exercise science. Calibration and validation of these devices are vital to obtaining accurate data. This article is aimed primarily at the physical activity measurement specialist, although the end user who is conducting studies with these devices also may benefit from knowing about this topic. Best Practices: Initially, wearable physical activity monitors should undergo unit calibration to ensure interinstrument reliability. The next step is to simultaneously collect both raw signal data (e. g., acceleration) from the wearable monitors and rates of energy expenditure, so that algorithms can be developed to convert the direct signals into energy expenditure. This process should use multiple wearable monitors and a large and diverse subject group and should include a wide range of physical activities commonly performed in daily life (from sedentary to vigorous). Future Directions: New methods of calibration now use "pattern recognition" approaches to train the algorithms on various activities, and they provide estimates of energy expenditure that are much better than those previously available with the single-regression approach. Once a method of predicting energy expenditure has been established, the next step is to examine its predictive accuracy by cross-validating it in other populations. In this article, we attempt to summarize the best practices for calibration and validation of wearable physical activity monitors. Finally, we conclude with some ideas for future research ideas that will move the field of physical activity measurement forward.
引用
收藏
页码:S32 / S38
页数:7
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