Sensing and wireless technologies have made remarkable advance recently, so wireless vital sensors for medical use, which are light-weight but accurate, have been commercially available. However, because of the low reliability of the wireless data transmission, sensed vital data are often lost in the wireless channel and this is a fatal drawback of the devices for continuous monitoring of patients in hospitals. This paper investigates the effect of using multiple receivers (receiver diversity technique) on the improvement of data loss rate for wireless vital data gathering. Experiments with a wireless vital sensor in hospital rooms reveal that putting receivers to higher positions such as ceiling is advantageous and the use of three receivers can sufficiently improve the data loss rate as compared with the use of a single receiver.

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For ubiquitous health care systems which continuously monitor a person's vital signs such as electrocardiogram (ECG), body surface temperature and three-dimensional (3D) acceleration by wireless, it is important to accurately detect the occurrence of an abnormal event in the data and immediately inform a medical doctor of its detail. In this paper, we introduce a remote health care system, which is composed of a wireless vital sensor, multiple receivers and a triage engine installed in a desktop personal computer (PC). The middleware installed in the receiver, which was developed in C++, supports reliable data handling of vital data to the ethernet port. On the other hand, the human interface of the triage engine, which was developed in JAVA, shows graphics on his/her ECG data, 3D acceleration data, body surface temperature data and behavior status in the display of the desktop PC and sends an urgent e-mail containing the display data to a pre-registered medical doctor when it detects the occurrence of an abnormal event. In the triage engine, the lethal arrhythmia detection algorithm based on short time Fourier transform (STFT) analysis can achieve 100 % sensitivity and 99.99 % specificity, and the behavior recognition algorithm based on the combination of the nearest neighbor method and the Naive Bayes method can achieve more than 71 % classification accuracy.

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This paper introduces the concept of an online medical diagnosis system for ubiquitous health care using a wireless ECG sensor. To confirm the feasibility ofthe system, we conducted clinical tests by 67 subjects with a wireless ECG sensor and a Holter ECG monitor simultaneously for comparison purpose. We made five types of evaluations such as analyses on data loss rate, burst data loss length, ECG waveforms comparison, normalized cross-correlation and heart rate variability (HRV) by RR50. The results show that, as long as the sensed data are successfully received at a receiver, the wireless ECG sensor has a comparable performance with the Holter ECG monitor.