An Optimal Pulse System Design by Multichannel Sensors Fusion

Dimin Wang, Dapeng Zhang, Guangming Lu

Research output: Journal article publicationJournal articleAcademic researchpeer-review

34 Citations (Scopus)


Pulse diagnosis, recognized as an important branch of traditional Chinese medicine (TCM), has a long history for health diagnosis. Certain features in the pulse are known to be related with the physiological status, which have been identified as biomarkers. In recent years, an electronic equipment is designed to obtain the valuable information inside pulse. Single-point pulse acquisition platform has the benefit of low cost and flexibility, but is time consuming in operation and not standardized in pulse location. The pulse system with a single-type sensor is easy to implement, but is limited in extracting sufficient pulse information. This paper proposes a novel system with optimal design that is special for pulse diagnosis. We combine a pressure sensor with a photoelectric sensor array to make a multichannel sensor fusion structure. Then, the optimal pulse signal processing methods and sensor fusion strategy are introduced for the feature extraction. Finally, the developed optimal pulse system and methods are tested on pulse database acquired from the healthy subjects and the patients known to be afflicted with diabetes. The experimental results indicate that the classification accuracy is increased significantly under the optimal design and also demonstrate that the developed pulse system with multichannel sensors fusion is more effective than the previous pulse acquisition platforms.
Original languageEnglish
Article number7010923
Pages (from-to)450-459
Number of pages10
JournalIEEE Journal of Biomedical and Health Informatics
Issue number2
Publication statusPublished - 1 Mar 2016


  • Information measurement
  • multichannel sensors fusion
  • optimal wrist pulse system design
  • sphygmology

ASJC Scopus subject areas

  • Biotechnology
  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Health Information Management


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