Confined space physiological fatigue measurement based on photoplethysmography pulse wave signal
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Abstract
Confined spaces are extremely common in industrial production and emergency rescue situations, and are also widely found in the fields of mining, chemistry, metallurgy, construction, aviation, submarines, emergency hedging, and others. Confined space operations and living environments are characterized by small spaces, poor ventilation, lack of oxygen, high temperatures and humidity, and poor lighting and communication. Exposure to this operating environment over even short periods of time causes thermal stress and changes in the oxygen content of the human body, which lead to physical discomforts such as increased heart rate, increased blood pressure, and body temperature changes. As exposure time increases, the human body experiences fatigue, confusion, and other symptoms. The physical fatigue caused by the human body being exposed to confined space environments is the main causal factor in safety accidents. Therefore, a method must be developed to enable objective measurement and rapid determination of physiological fatigue. A 100-min-limit manned experiment was conducted in a confined space to test an objective fatigue measurement method based on the photoplethysmography pulse wave (PPG). An algorithm was then developed to extract PPG signal feature parameters to determine the hemodynamics and circulatory system changes that characterize physiological fatigue. As the most basic physiological signal of the human body, the PPG contains abundant information about hemodynamics and autonomic nervous system circulation. This information is reflected in parameters such as the wave shape, speed, and rhythm. The results indicate that when the human body experiences physiological fatigue, the average period of the PPG signal is significantly greater than that when it is non-fatigued (p<0.001), the vascular resistance increases, and the stroke volume per stroke is significantly decreased. The two types of complexity (KC complexity, high-order KC complexity) of PPG signals were calculated under fatigue and non-fatigue conditions. The calculation results was found for these two complexities to be the same, and the waveforms to be more stable when the body is not fatigued. Therefore, the results demonstrate that the PPG signal can capture the physiological changes of the fatigue state and provide objective measurement and enable rapid judgment regarding physiological fatigue.
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