MOD-Net-based eye movement parameter monitoring fatigue detecting and consciousness promoting system

Abstract

The invention discloses an MOD-Net-based eye movement parameter monitoring fatigue detecting and consciousness promoting system. The system comprises a glasses body, an image collecting module for collecting side eye image data of a wearer, a consciousness promoting module, a power module and a background processing module which comprises an MOD-Net eye movement data analysis module, a fatigue degree analysis module and a master control module. Due to eye movement data analysis, the human body fatigue degree can be determined automatically in real time, an early alarm is given according to thehuman fatigue degree, consciousness promoting stimulus with combination of sound, light and vibration is applied, the human fatigue degree is lowered, and the human awareness degree and operating ability are improved; eye movement data is analyzed by adopting the MOD-Net eye movement data analysis module, the good anti-noise, anti-rotation and anti-scale-change capability is achieved, the fuzzy eye region can be captured, and the fatigue detection accuracy can be improved.

Description

technical field [0001] The invention relates to the technical field of fatigue detection and awakening stimulation, in particular to a fatigue detection and awakening promotion system based on MOD-Net network eye movement parameter monitoring. Background technique [0002] With the development of random society, the automation level of the current work is improving. Various jobs require staff such as pilots to maintain a high degree of alertness and abundant energy and attention to ensure that high-end equipment is operated without errors and related operations are carried out smoothly. However, Continuous, high-intensity, non-scheduled operations affect the staff's judgment, decision-making and combat execution capabilities. Therefore, it is necessary to accurately evaluate the influence of temporal biorhythm and its functional state on related working ability under continuous working conditions, and provide scientific intervention to improve the working efficiency of relev...

AI Technical Summary

Problems solved by technology

The RCNN series algorithm uses the 2-stage method for target detection, which has high detection accuracy for multi-target and fine-grained targets, but it still has defects, such as its large amount of calculation, and cannot achieve real-time performance, etc.

And at present, the relevant equipment on the market is mainly focused on the research and development of driving fatigue detection devices, lack of research on related fields such as personal work ability improvement, and lack of portable wearable devices that integrate fatigue detection, early warning and wake-up stimulation. device

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