Abstract
The field of medical monitoring has a lot of room for growth for wearable optical fibre sensors. The development of wearable optical fibre sensors is progressively satisfying the need for new medical monitoring devices to be more small, comfortable, accurate, and have other capabilities. Through the use of sensors to monitor posture, dance instruction progressively teaches the concept of “digital dance,” alleviating the burden of teaching on educators. The non-wearable monitoring approach has strict criteria for the measuring scene, but it does not require touch with patient as well as usually uses pictures or signal waves for placement. This study suggests a unique method for dancing motion detection utilising optical wearable sensors and a quantum machine learning model in a health monitoring system. Here, we examine several deep learning approaches for data collected by optical wearable sensors that track dancing moves. Next, we examine the best approach for the health monitoring system. Accuracy is used to determine which approach is best. To confirm use of wearables based on deep learning (DL) in emotional dance instruction, a gadget is capable of recognising dance moves.
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Hou, Y. Optical wearable sensor based dance motion detection in health monitoring system using quantum machine learning model. Opt Quant Electron 56, 686 (2024). https://doi.org/10.1007/s11082-023-06143-3
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DOI: https://doi.org/10.1007/s11082-023-06143-3