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Electronics 2014, 3(2), 205-220; doi:10.3390/electronics3020205
Article

Use of a Wireless Network of Accelerometers for Improved Measurement of Human Energy Expenditure

1,†,* , 2,†
, 2
 and 1
Received: 8 February 2014; in revised form: 12 March 2014 / Accepted: 19 March 2014 / Published: 3 April 2014
(This article belongs to the Special Issue Wearable Electronics)
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Abstract: Single, hip-mounted accelerometers can provide accurate measurements of energy expenditure (EE) in some settings, but are unable to accurately estimate the energy cost of many non-ambulatory activities. A multi-sensor network may be able to overcome the limitations of a single accelerometer. Thus, the purpose of our study was to compare the abilities of a wireless network of accelerometers and a hip-mounted accelerometer for the prediction of EE. Thirty adult participants engaged in 14 different sedentary, ambulatory, lifestyle and exercise activities for five minutes each while wearing a portable metabolic analyzer, a hip-mounted accelerometer (AG) and a wireless network of three accelerometers (WN) worn on the right wrist, thigh and ankle. Artificial neural networks (ANNs) were created separately for the AG and WN for the EE prediction. Pearson correlations (r) and the root mean square error (RMSE) were calculated to compare criterion-measured EE to predicted EE from the ANNs. Overall, correlations were higher (r = 0.95 vs. r = 0.88, p < 0.0001) and RMSE was lower (1.34 vs. 1.97 metabolic equivalents (METs), p < 0.0001) for the WN than the AG. In conclusion, the WN outperformed the AG for measuring EE, providing evidence that the WN can provide highly accurate estimates of EE in adults participating in a wide range of activities.
Keywords: artificial neural network; machine learning; ActiGraph; multi-sensor network; activity measurement; physical activity artificial neural network; machine learning; ActiGraph; multi-sensor network; activity measurement; physical activity
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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MDPI and ACS Style

Montoye, A.H.; Dong, B.; Biswas, S.; Pfeiffer, K.A. Use of a Wireless Network of Accelerometers for Improved Measurement of Human Energy Expenditure. Electronics 2014, 3, 205-220.

AMA Style

Montoye AH, Dong B, Biswas S, Pfeiffer KA. Use of a Wireless Network of Accelerometers for Improved Measurement of Human Energy Expenditure. Electronics. 2014; 3(2):205-220.

Chicago/Turabian Style

Montoye, Alexander H.; Dong, Bo; Biswas, Subir; Pfeiffer, Karin A. 2014. "Use of a Wireless Network of Accelerometers for Improved Measurement of Human Energy Expenditure." Electronics 3, no. 2: 205-220.

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