An intelligent fitness diagnosis system using electroencephalogram with biomedical signals

Abstract

This paper proposes an intelligent fitness diagnosis system (IFDS), which integrates the electroencephalogram (EEG) and electrocardiogram (ECG) biomedical signals and fitness data. IFDS detects the voltage and current produced by the users under different states of attention and meditation during exercise. Based on EEG, ECG, and fitness data, the extension method is applied to distinguish the physical and mental conditions of the users during exercise. The brainwave training system, designed by LabVIEW, analyzes the α and θ wave bands of EEG, and plots the waveforms under different states of attention and meditation simultaneously to effectively improve the users' attention. Ten subjects were included to exercise for 15 times, lasting 3 min each. The accuracy of IFDS reaches 91%. Meanwhile, IFDS indirectly diagnoses the symptoms of some diseases in the users. © 2016 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.