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This paper proposes a mobile patient monitoring system, which integrates current personal digital assistant (PDA) technology and wireless local area network (WLAN) technology. At the patient's location, a wireless PDA-based monitor is used to acquire continuously the patient's vital signs, including heart rate, three-lead electrocardiography, and SpO/sub 2/. Through the WLAN, the patient's biosignals can be transmitted in real-time to a remote central management unit, and authorized medical staffs can access the data and the case history of the patient, either by the central management unit or the wireless devices. A prototype of this system has been developed and implemented. The system has been evaluated by technical verification, clinical test, and user survey. The evaluation of performance yields a high degree of satisfaction (mean=4.64, standard deviation-SD=0.53 in a five-point Likert scale) of users who used the PDA-based system for intrahospital transport. The results also show that the wireless PDA model is superior to the currently used monitors both in mobility and in usability, and is, therefore, better suited to patient transport.

The method of truncated singular value decomposition (SVD) is proposed for electrocardiogram (ECG) data compression. The signal decomposition capability of SVD is exploited to extract the significant feature components of the ECG by decomposing the ECG into a set of basic patterns with associated scaling factors. The signal informations are mostly concentrated within a certain number of singular values with related singular vectors due to the strong interbeat correlation among ECG cycles. Therefore, only the relevant parts of the singular triplets need to be retained as the compressed data for retrieving the original signals. The insignificant overhead can be truncated to eliminate the redundancy of ECG data compression. The Massachusetts Institute of Technology-Beth Israel Hospital arrhythmia database was applied to evaluate the compression performance and recoverability in the retrieved ECG signals. The approximate achievement was presented with an average data rate of 143.2 b/s with a relatively low reconstructed error. These results showed that truncated SVD method can provide an efficient coding with high-compression ratios. The computational efficiency of the SVD method in comparing with other techniques demonstrated the method as an effective technique for ECG data storage or signals transmission. Index Terms-Data compression, electrocardiogram, feature extraction, quasi-periodic signal, singular value decomposition.