Fatigue Assessment by Blink Detected with Attachable Optical Sensors of Dye-Sensitized Photovoltaic Cells.

Ryogo Horiuchi,Tomohito Ogasawara,Norihisa Miki

doi:10.3390/mi9060310

Abstract

This paper demonstrates fatigue assessment based on eye blinks that are detected by dye-sensitized photovoltaic cells. In particular, the sensors were attached to the temple of eyeglasses and positioned at the lateral side of the eye. They are wearable, did not majorly disturb the user’s eyesight, and detected the position of the eyelid or the eye state. The optimal location of the sensor was experimentally investigated by evaluating the detection accuracy of blinks. We conducted fatigue assessment experiments using the developed wearable system, or smart glasses. Several parameters, including the frequency, duration, and velocity of eye blinks, were extracted as fatigue indices. Successful fatigue assessment by the proposed system will be of great benefit for maximizing performance and maintenance of physical/mental health.

Highlights

Fatigue assessment is crucial to secure safety and efficiency in operation
The number of blinks and blink bursts showed good correlation with the number of U–K tests, which showed good agreement with the fatigue symptoms that were deduced from subjective questionnaires
The measurement of the number of blinks can be achieved via simple processes, which can contribute to real-time fatigue assessment

Summary

Introduction

Fatigue assessment is crucial to secure safety and efficiency in operation. For such applications, the assessment system itself should provide the users’ minimum physical and mental stress; the whole system should be light enough to be wearable, and should not disturb the users’ activities and eyesight. Real-time process is an important requirement, which encourages us to discover fatigue indices that can be measured as well as processed. Heart rate variance (HRV) uses an R-R interval, or RRI, of an electrocardiogram (ECG). The RRI is deduced from the measured ECG and Fourier transformed to calculate the autonomic nerve index as the power ratio of the low-frequency (0.05–0.15 Hz) and high-frequency (0.15–0.40 Hz) bands. Heart rate variance increases with fatigue and decreases during recovery [1,2]

Results

Discussion

Conclusion