Abstract
To discuss the judgment for the variation of the human body fatigue under the weight-bearing walking condition and based on the characteristics of the indexes of heart rate, heart rate variability, etc., the paper uses the LabVIEW software to realize the preprocessing of ECG signals, detection of R wave, and HRV analysis, which is based on confirming the relativity of the ECG signal index and human body weight-bearing fatigue. Results indicate through the analysis of ECG characteristic indexes, with the increase of the weight-bearing walking time and the increase of the human body fatigue, HRmean, RMSSD, HFnorm, LF/HF, and sample entropies clearly change, wherein HRmean, HFnorm, LF/HF, and sample entropies are sensitive to the fatigue variation, and then does the RMSSD. The principal component analysis (PCA) method is used for establishing the ECG comprehensive index which is the basis for judging that under the condition of the weight-bearing walking experiment of the paper, the volunteers are clearly fatigue in stage 3, and the fatigue is significantly increased in stage 5.
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Compliance with Ethical Standards
The study was approved by the Logistics Department for Civilian Ethics Committee of School of Biological Science and Medical Engineering of Beihang University.
All subjects who participated in the experiment were provided with and signed an informed consent form.
All relevant ethical safeguards have been met with regard to subject protection.
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Hao, X., Zhou, Q., Liu, Z. (2018). Experiment Study of Weight-Bearing Walking Fatigue of Human Body Based on ECG Signal Characteristics. In: Long, S., Dhillon, B. (eds) Man–Machine–Environment System Engineering. MMESE 2017. Lecture Notes in Electrical Engineering, vol 456. Springer, Singapore. https://doi.org/10.1007/978-981-10-6232-2_32
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DOI: https://doi.org/10.1007/978-981-10-6232-2_32
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