The set partitioning in hierarchical trees (SPIHT) algorithm is very effective and computationally simple technique for image and signal compression. Here the author modified the algorithm which provides even better performance than the SPIHT algorithm. The enhanced set partitioning in hierarchical trees (ESPIHT) algorithm has performance faster than the SPIHT algorithm. In addition, the proposed algorithm reduces the number of bits in a bit stream which is stored or transmitted. I applied it to compression of multichannel ECG data. Also, I presented a specific procedure based on the modified algorithm for more efficient compression of multichannel ECG data. This method employed on selected records from the MIT-BIH arrhythmia database. According to experiments, the proposed method attained the significant results regarding compression of multichannel ECG data. Furthermore, in order to compress one signal which is stored for a long time, the proposed multichannel compression method can be utilized efficiently.
Ultra-Wideband (UWB) technology provides a convenient approach for remote biomedical sensing and vital signs monitoring in humans. In this paper, a specific algorithm is proposed to improve the ability of Heart Rate (HR) detection. Unlike previous methods for remote HR detection, the proposed method provides an adaptive filter based on respiration and heart rate parameters obtained from UWB waveforms. The algorithm is capable of detecting heart rate by changing the adaptive filter parameters accordingly. The proposed method is employed on real life data collected by UWB transceiver. According to experiments, it is concluded that the proposed technique is able to handle remote detection of different heart rates accurately.
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