An intelligent framework for workouts in gymnasium: M-Health perspective

作者：Bhatia Munish^*; Sood Sandeep K

来源：Computers & Electrical Engineering, 2018, 65: 292-309.

DOI：10.1016/j.compeleceng.2017.07.018

• Artificial Neural Networks
• Cloud Centric Internet of Things
• Smart gym
• Mobile healthcare
• Temporal data

The Internet of Things (IoT) Technology has the potential to capture real-time health related parameters everywhere. Henceforth, in this paper, the Cloud Centric IoT (CCIoT) Technology is utilized to assess the health related attributes of a trainee during exercise sessions in a gymnasium. The proposed system have the capabilities to predict the probabilistic vulnerability to health parameters of a trainee during workouts. For this purpose, back-propagation based Artificial Neural Network (ANN) technique is used as a prediction model, layered into three stages, i.e. Monitoring, Learning, and Prediction. Also, the probabilistic vulnerability is represented in real-time using color-coded technique, depicting the health state of the trainee. The proposed system has been validated using an experiment in which five people were monitored for six days at different gymnasiums. Results are compared with different state-of-the-art techniques for determining the overall effectiveness of the proposed system.

• 出版日期2018-1