Research Of Human Mental Fatigue Detection System Based On HRV

Fatigue is a complex physiological state of the human body, mainly for the mental and physical exhaustion, and the decrease of attention and work efficiency. Nowadays there are many occasions that request operators to be full of energy, such as drivers’ driving, pilots’ high-altitude operations, surgeon and so on. Otherwise, serious accidents could occur. Therefore, it is essential to detect the fatigue of the human body.In this thesis, literature review about research on human fatigue detection was firstly conducted. The formation mechanism and physiological characteristics of the ECG signal were then investigated. On this basis, Fatigue index based on HRV was finally proposed.. Besides, a system was finally designed including ECG acquisition and ECG analysis.The acquisition program commonly uses two-system designs:one is the chip-level design based on integrated circuit system; the other is to utilize the rich resources of existing sensors and computer hardware and software to build systems. Considering the long development period and high cost of the former one, we selected the latter design. Choosing ECG EKG-BTA sensor as ECG amplifier can amplify ECG signal to a state that can be identified by USB6211 data acquisition card. Then the signal went through the A/D conversion, and collected and analysis by the computer. Unlike electrode with conductive fabric in conventional ECG machine, the non-contact electrodes were mounted on the seat, not in direct contact with the skin, which can easily measure the ECG. The study designed a non-contact ECG acquisition system without discomfort, and long-term usage of the system will not cause skin allergies and side effects.The analysis of ECG was performed in the platform of Lab VIEW based on G graphical programming language software of NI Company, the United States, which has powerful processing capabilities, ensuring the process and analysis of the traditional ECG data to be completed in computer. By analysing noise sources of the heart signal, the noise removal mechanism through the use of classical filters and wavelet transform signal methods respectively was analysis and compared. Then the parameters of the ECG R-wave were detected. The R-wave detection results were validated with marked R wave position results in the annotation file of arrhythmia database (MIT-BIH Arrhythmia Database).The validation have proved the proposed QRS complex detection algorithm achieve a 99.59% detection sensitivity. The detected R-wave was used to calculate the heart rate and RR interval, and thus the frequency domain analysis for HRV was carried out, which lay the foundation for HRV analysis of ECG detection of human mental fatigue. The frequency indicators, SDNN, TP, LF, HF, LF/HF from HRV analysis may be used to detect the human mental fatigue.Finally, a system was designed and realized by LabVIEW, with functions of real-time display, save and play back, and start with the user login.