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An Association Rule Analysis of the Acupressure Effect on Sleep Quality
Author(s) -
Chih-Hung Lin,
Ya-Hsuan Lin,
IShiang Tzeng,
ChanYen Kuo
Publication year - 2021
Publication title -
evidence-based complementary and alternative medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.552
H-Index - 90
eISSN - 1741-4288
pISSN - 1741-427X
DOI - 10.1155/2021/1399258
Subject(s) - pittsburgh sleep quality index , sleep (system call) , acupressure , sleep quality , medicine , association rule learning , artificial intelligence , computer science , insomnia , psychiatry , alternative medicine , pathology , operating system
Background Sleep is recognized as an all-important physiological process, which also contributes to maintaining several bodily functions and systems. According to the Pittsburgh Sleep Quality Index (PSQI), also known as the most widely used tool in the field of subjective assessment of self-perceived sleep quality, a combination of acupoints could be more effective than single acupoint treatment in improving sleep quality.Methods The present study was based on the extracted eligible studies rooted in a previous meta-analysis that worked on the basis of association rule mining and examined the potential kernel acupoint combinations for improving sleep quality.Results Depending on the Apriori algorithm, we summarized 26 acupoints as binary data from the 32 eligible studies based on a previous meta-analysis and analyzed them. The top 10 most frequently selected acupoints were HT7, SP6, PC6, KI1, GV20, EM5, EX-HN3, EX-HN16, KI3, and MA-TF1. Furthermore, as deduced from 21 association rules, the primary relevant rules in the combination of acupoints are (EX-HN3, EX-HN16)=>(GV20) and (HT7, KI1)=>(PC6).Conclusions In order to use acupuncture to improve sleep quality, integrating (EX-HN3, EX-HN16, GV20) with (HT7, KI1, PC6) acupoints could be deemed as the kernel acupoint combination.

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