Neural network study for standardizing pulse-taking depth by the width of artery. (1st February 2015)

• Record Type: Journal Article
• Authors: Chung, Cheng-Ying; Cheng, Yu-Wei; Luo, Ching-Hsing
• Is Part Of: Computers in biology and medicine. Volume 57(2015)
• Page Start: 26
• Page End: 31
• Publication Date: 2015-02-01
• Subjects: Pulse-taking depth -- Pulse diagnosis instrument (PDI) -- Traditional Chinese medicine (TCM) -- Three positions and nine indicators (TPNI) -- Neural Network; Medicine -- Data processing -- Periodicals; Biology -- Data processing -- Periodicals; 610.285
• DOI: 10.1016/j.compbiomed.2014.10.016
• Languages: English
• ISSNs: 0010-4825

Abstract

Abstract: To carry out a pulse diagnosis, a traditional Chinese medicine (TCM) physician presses the patient's wrist artery at three incremental depths, namely Fu (superficial), Zhong (medium), and Chen (deep). However, the definitions of the three depths are insufficiently clear for use with modern pulse diagnosis instruments (PDIs). In this paper, a quantitative method is proposed to express the pulse-taking depths based on the width of the artery (WA). Furthermore, an index, α, is developed for estimating WA for PDI application. The α value is obtained using an artificial neural network (ANN) model with contact pressure (CP) and sensor displacement (SD) as the inputs. The WA and SD data from an ultrasound instrument and CP and SD data from a PDI were analyzed. The results show that the mean prediction error and the standard deviation (STD) of the ANN model was 1.19% and 0.0467, respectively. Comparing the ANN model with the SD model by statistical method, it showed significant difference and the improvement in the mean prediction error and the STD was 71.62% and 29.78%, respectively. The α value can thus map WA with less individual variation than that of the values estimated directly using the SD model. Pulse signals at different depths thus can be acquired according to α value while using a PDI, providing TCM physicians with more reliable pulse information. Highlights: Pulse-taking depths could be expressed based on the width of the artery (WA). Two models for estimating WA were compared; the ANN model was better performance. The ANN model had two inputs (SD and CP) and one output, α . (i.e., estimated WA). Pulse signals at different depths could be acquired by α value for PDI application. The method made the description of pulse-taking depth modernized and scientized.