Abstract
Tele-Health services provide people with healthcare assistance and help to establish accessible and high-quality monitoring. Telematic healthcare administration offers direct aid through the Internet of Things (IoT), which is better than current methods involving physical presence. The IoT and sensor networks currently enable remote monitoring of an individual or community. There are different Energy Level (EL) estimation methods for aerobics using body-worn sensors; however, quantification of error estimation differences is lacking. In this article, the Internet of Things based Energy Level Estimation method (IoT-ELEM) has been proposed for determining energy rates. The latter two forms of calculation are accompanied by a list of behaviors and EL approximations. Likewise, the amount and location of accelerometer sensors have been examined to achieve maximal EL estimates in aerobic players. The device is built on a distributed design that gathers a person's physiological data from various sensors data and conducts a standardization phase. These results are all transmitted to the cloud for storing and further processing. The cloud device manages the obtained details and performs a data fusion procedure to display the EL of the user at all stages. The IoT-ELEM system has been evaluated and achieves a high accuracy ratio of 98.6%, a prediction ratio of 96.4%, a performance ratio of 97.8, a less error rate of 9.4%, and an F1 score ratio of 94.6%.
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Fan, Y., Man, M., Ramanathan, L. et al. Aerobics player’s energy level monitoring using IoT. J Ambient Intell Human Comput (2021). https://doi.org/10.1007/s12652-021-03139-3
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DOI: https://doi.org/10.1007/s12652-021-03139-3