A Wearable Blink Monitoring Device For VDT Dry Eye

Advances in wireless technology,low-power electronics,the internet of things,and connected health are driving innovation in wearable medical devices at an astonishing rate.Wearable sensor systems composed of flexible and stretchable materials have the potential to better interface to the human skin,whereas silicon-based electronics are extremely efficient in sensor data processing and transmission.Therefore,flexible,and stretchable sensors combined with low-power silicon-based electronics are a viable and efficient approach for medical monitoring.Flexible medical devices designed for monitoring human vital signs,such as body temperature,heart rate,respiration rate,blood pressure,pulse oxygenation,and blood glucose have applications in both fitness monitoring and medical diagnostics.Blink reflex has long been considered closely related to physiological states,from which abundant information on ocular health and activities can be revealed.At present,due to the limitation of sensing input devices,there is no wearable eye blink monitoring system with long-term safety in the market or academia.In order to solve the problem of wearable monitoring of blink signal,this paper mainly carried out the following two studies:(1)Research on wearable blink monitoring device based on flexible sensorsIn this study,we develop a wearable blink monitoring smart glasses,which includes a high sensitivity flexible iontronic sensing(FITS)sensor integrated in the nose pad and data processing circuit.The changes of skin pressure caused by orbicularis oculi muscle movement can be monitored in real time by FITS sensor.Because of the sensing principle and performance of the sensor itself,the eye blink monitoring glasses will not be affected by ambient light or individual facial topological structure.After the signal of skin pressure change at the nose pad during the movement of orbicularis oculi muscle is collected successfully,the feature signal representing the blink pattern can be captured successfully by using the template matching algorithm of variable threshold.Compared with the existing gold standard(video),the accuracy of blink pattern detection reaches 96.3%.(2)Research on VDT dry eye based on wearable blink monitoring deviceAfter obtaining the wearable blink detection device based on FITS sensor which can work stably,the data of healthy people and patients with VDT dry eye were collected for analysis and research.The device is used to distinguish blink characteristics of dry eye patients and healthy controls,and the analysis results are highly consistent with the results of previous studies.Secondly,SVM binary classification model is established to classify dry eye patients and healthy people according to blink frequency,maximum blink interval and maximum blink duration.The accuracy of the model is 93.3%.