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.
For example, REF proposed a Lempel-Ziv complexity analysis-based approach to classify seven pulse patterns that exhibit different rhythms.
Arrhythmic Pulses Detection Using Lempel-Ziv Complexity Analysis
EURASIP Journal on Advances in Signal Processing
Computer Science