Abstract:
:Arrhythmia diagnosis is very significant to ensure human health. In this paper, a new model is developed for arrhythmia diagnosis. A salient feature of the algorithm is a synergistic combination of statistical and fuzzy set-based techniques. It is distribution-free and is realized in an unsupervised mode. Arrhythmia diagnosis is viewed as a certain statistical hypothesis testing. 'Abnormal' is typically a much complex concept, so it can be described with the technology of fuzzy sets which bring a facet of robustness to the overall scheme and play an important role in the successive step of hypothesis testing. Intensive fuzzification is engaged in parameters determination which is self-adaptive and no parameter needs to be specified by the user. The algorithm is validated with a number of experiments, which prove its effectiveness for arrhythmia diagnosis.
journal_name
Biomed Mater Engjournal_title
Bio-medical materials and engineeringauthors
Li F,Zheng D,Zhao Tdoi
10.3233/BME-151400subject
Has Abstractpub_date
2015-01-01 00:00:00pages
S1045-52eissn
0959-2989issn
1878-3619pii
BME1400journal_volume
26 Suppl 1pub_type
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