Key result
Lempel-Ziv complexity analysis achieved a recognition accuracy of 97.1% for detecting seven distinct pulse patterns compared to expert assessment in traditional Chinese medicine.
A novel approach using Lempel-Ziv complexity analysis can accurately detect and classify arrhythmic pulse patterns based on traditional Chinese medicine principles.
Lempel-Ziv analysis may enable objective TCM pulse classification; leaves open clinical adoption in arrhythmia assessment pending prospective validation.
Computerized pulse analysis based on traditional Chinese medicine (TCM) is relatively new in the field of automatic physiological signal analysis and diagnosis. Considerable researches have been done on the automatic classification of pulse patterns according to their features of position and shape, but because arrhythmic pulses are difficult to identify, until now none has been done to automatically identify pulses by their rhythms. This paper proposes a novel approach to the detection of arrhythmic pulses using the Lempel-Ziv complexity analysis. Four parameters, one lemma, and two rules, which are the results of heuristic approach, are presented. This approach is applied on 140 clinic pulses for detecting seven pulse patterns, not only achieving a recognition accuracy of 97.1% as assessed by experts in TCM, but also correctly extracting the periodical unit of the intermittent pulse.
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Xu et al. (2006) studied Arrhythmic pulses (n=140). Lempel-Ziv complexity analysis vs. Expert assessment in traditional Chinese medicine was evaluated on Recognition accuracy of pulse patterns. Lempel-Ziv complexity analysis achieved a recognition accuracy of 97.1% for detecting seven distinct pulse patterns compared to expert assessment in traditional Chinese medicine.
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