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This paper proposes a technique for frequency-partitioned spectrum estimation (FPSE), which is used in the National Taiwan University Wireless Health Advanced Monitoring Bio-Diagnosis System for electrocardiogram analysis. A process for analyzing the RR interval (which is a time series formed by the heat-beat duration that represents heart-rate variations) in conjunction with the fuzzy clustering technique is proposed for arrhythmia recognition. FPSE helps reduce data transmission errors and allows the computational load to be moved to a remote server; however, it suffers from waveform deterioration during reconstruction of the signal power spectrum. To compensate for this problem, this paper proposes a modified FPSE approach that imposes an additional boundary constraint to ensure that the estimated spectrum is smooth. The simulation results show that the proposed algorithm is more effective at recovering the original frequency information and achieves a globally asymptotic trend. The proposed arrhythmia recognition procedure was applied to the Massachusetts Institute of Technology-Boston's Beth Israel Hospital (MIT-BIH) database (developed by MIT and Boston's Beth Israel Deaconess Medical Center), which demonstrated that it is both very convenient and efficient. [ABSTRACT FROM AUTHOR]