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Many reports show that there are a lot of traffic accidents due to sleeping while driving. Then, demand for measuring electrocardiogram (ECG) to estimate drowsiness of drivers has increased to prevent these accidents. In this paper, we propose an ECG monitoring system of a car driver using capacitively-coupled electrode. This capacitively-coupled electrode on which an operational amplifier (OP amp) was mounted was embedded inside a seat for measuring ECG signal. A ground electrode was placed on a steering wheel, i.e. ECG signal was amplified by a single-ended amplifier. Subjects wore their regular suits and pants made of wool, and ECG was obtained during driving at low speed on a rough road with one corner. Results show that our system can be used to obtain ECG while driving at low speed except some motion artifacts caused by the steering operation, road surface, braking, and accelerating.

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Sleep disruption from causes, such as changes in lifestyle, stress from aging, family issues, or life pressures are a growing phenomenon that can lead to serious health problems. As such, sleep disorders need to be identified and addressed early on. In recent years, studies have investigated sleep patterns through body movement information collected by wristwatch-type devices or cameras. However, these methods capture only the individual’s awake and sleep states and lack sufficient information to identify specific sleep stages. The aim of this study was to use a 3-axis accelerometer attached to an individual’s head to capture information that can identify three specific sleep stages: rapid eye movement (REM) sleep, light sleep, and deep sleep. These stages are measured by heart rate features captured by a ballistocardiogram and body movement. The sleep experiment was conducted for two nights among eight healthy adult men. According to the leave-one-out cross-validation results, the F-scores were: awake 76.6%, REM sleep 52.7%, light sleep 78.2%, and deep sleep 67.8%. The accuracy was 74.6% for the four estimates. This proposed measurement system was able to estimate the sleep stages with high accuracy simply by using the acceleration in the individual’s head.

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