We propose mental fatigue measurement using a wearable eye detection system. The system is capable of acquiring movement of the pupil and blinking from the light reflected from the eye. The reflection is detected by dye-sensitized photovoltaic cells. Since these cells are patterned onto the eyeglass and do not require external input power, the system is notable for its lightweight and low power consumption and can be combined with other wearable devices, such as a head mounted display. We performed experiments to correlate information obtained by the eye detection system with the mental fatigue of the user. Since it is quite difficult to evaluate mental fatigue objectively and quantitatively, we assumed that the National Aeronautics and Space Administration Task Load Index (NASA-TLX) had a strong correlation with te mental fatigue. While a subject was requested to conduct calculation tasks, the eye detection system collected his/her information that included position, velocity and total movement of the eye, and amount and frequency of blinking. Multiple regression analyses revealed the correlation between NASA-TLX and the information obtained for 3 out of 5 subjects.

In the past decade, real-time systems (RTSs), which must maintain time constraints to avoid catastrophic consequences, have been widely introduced into various embedded systems and Internet of Things (IoTs). The RTSs are required to be energy efficient as they are used in embedded devices in which battery life is important. In this study, we investigated the RTS energy efficiency by analyzing the ability of body bias (BB) in providing a satisfying tradeoff between performance and energy. We propose a practical and realistic model that includes the BB energy and timing overhead in addition to idle region analysis. This study was conducted using accurate parameters extracted from a real chip using silicon on thin box (SOTB) technology. By using the BB control based on the proposed model, about 34% energy reduction was achieved.

Our group has developed a wearable eye-tracking system that comprises transparent optical sensors on eyeglasses to detect the reflection from the eye and thus, the position of the eye, where photovoltaic cells are used as the sensors. In this paper, crosstalk, or electric interference, among the photovoltaic cells is discussed. The crosstalk makes the neighboring sensors dependent on each other, which leads to large errors in eye-tracking. We experimentally investigated the source of crosstalk by testing different designs of photovoltaic cells and their interconnection. It was revealed that sharing of the electrolyte by the photovoltaic devices was dominant. In addition, overlapping circuits were found to contribute to the crosstalk. We revised the design of the sensors and successfully reduced the crosstalk and improved the accuracy.

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This research reports the initial werk ofa novel nen-invasive method to evaluate a person's workload (fatigue). Ihis is done by using a non-invasiye optical sensor that will help te assess the subjective workload, Our system uti1izes dye sensitized selar cells (DSSC) as optical sensors. for 1ine-ofisight (LOS) and eye movement detector. Since the workload will be reflected in this ¢ yc movernent. we assess it under NASA Thsk-Load-lndex (TLX) protocol. a multidimensienal scale methodology:3 out of S sulijects were found to have good correlation between the workload and LOS.