U-healthcare System using Smart Headband.

The wearable healthcare system should be not only small and easy for users to wear them but accurate in measuring physiological signals in daily life without any inconvenience. To meet these requirements, we propose the U-healthcare System which consists of a Smart Headband and a Health-state Monitor program. It can monitor the health-state in walking and running. The Smart Headband measures a photo-plethysmography (PPG) signal at the forehead for monitoring the heart rate and acceleration signals. The Health-state Monitor program is developed to show the health-state. Health-state Monitor program is operated in the handheld computer, such like (Ultra Mobile Personal Computer (UMPC). It provides the user PPG, heart rate and steps for the precise measurement, Adaptive Noise Cancellation (ANC) is introduced. The Smart Headband and the Health-state Monitor program are communicated by the WPAN using Zigbee protocol. If the heart rate is higher or lower than usual, the Health-state Monitor program sends the SMS message to the designated person, such as family or the attending physician in the medical center, to inform the emergency situation.

Adaptive noise cancellation using accelerometers for the PPG signal from forehead.

For the upcoming ubiquitous computing environments in the u-health areas involve the measurement of physiological signals in the daily life. However, the measurement of those signals, such as the photoplethysmorgraphy (PPG), and the electrocardiogram (ECG), requires being still tight during the measurement in order to get the accurate result preventing noises caused by the casual movement. In this paper, we propose a method to obtain the accurate physiological signals in the situation where the little movement is allowed. By measuring PPG and motion signals at the forehead during in motion, we calibrate the distorted PPG signal with the motion signals. We show that the calibrated PPG signal is accurate enough by comparing with the result that is measured at the finger without any movement.

Wearable Systems for Service based on Physiological Signals.

Many researches for useful status information on humans have been done using the bio-signals. The bio-signal acquisition systems can be used to connect a user and a ubiquitous computing environment. The ubiquitous computing environment has to give various services anywhere, anytime. Consequently, ubiquitous computing requires new technology, such as a new user interface, dynamic service mechanism based on context and mobility support, which is different from technology used in desktop environment. To do this, we developed a wearable system, which can sense physiological data, determine emotional status and execute service based on the emotion. In this paper, we described wearable systems for personalized service based on physiological signals. The wearable system is composed of three subsystems, the physiological data sensing subsystem, the human status awareness subsystem and the service management subsystem. The physiological data sensing subsystem senses PPG, GSR and SKT signals from the data glove and sends the data to a wearable system using Bluetooth. The human status awareness subsystem in the wearable system receives the data from bio-sensors and determines emotional status using nonlinear mapping and rule-base. After determining emotion, the service management subsystem activates proper service automatically, and the service management subsystem can provide personalized service for users based on acquired bio-signals. Also, we presented various feature extraction using bio-signals such as PPG, GSR, SKT considering mobility, and emotion recognition of human status for the ubiquitous computing service.