An intelligent fitness diagnosis system using electroencephalogram with biomedical signals

作者：Wang Meng Hui; Huang Mei Ling^*; Li Chien Shun

来源：IEEJ Transactions on Electrical and Electronic Engineering, 2016, 11(6): 714-719.

DOI：10.1002/tee.22296

• EEG
• psychosomatic diagnosis
• attention
• meditation
• heartbeat rate
• extension theory

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 and 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.

• 出版日期2016-11