title: Neural network study for standardizing pulse-taking depth by the width of artery.
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.
authors.affiliation: Department of Electrical Engineering, National Cheng Kung University, Tainan 70101, Taiwan. Electronic address: n28991293@mail.ncku.edu.tw.
authors.forename: Cheng-Ying
authors.initials: CY
authors.lastname: Chung
authors.affiliation: Department of Electrical Engineering, National Cheng Kung University, Tainan 70101, Taiwan. Electronic address: hookeson823@hotmail.com.
authors.forename: Yu-Wei
authors.initials: YW
authors.lastname: Cheng
authors.affiliation: Department of Electrical Engineering, National Cheng Kung University, Tainan 70101, Taiwan; Institute of Medical Science and Technology, National Sun Yat-sen University, KaoHsiung 80424, Taiwan. Electronic address: robinluo@mail.ncku.edu.tw.
authors.forename: Ching-Hsing
authors.initials: CH
authors.lastname: Luo
mesh_terms: D000328:Adult; D000465:Algorithms; D001158:Arteries / Q000502:physiology; D006339:Heart Rate / Q000502:physiology*; D006801:Humans; D008297:Male; D008516:Medicine, Chinese Traditional / Q000379:methods*; D016571:Neural Networks, Computer; D010808:Physical Examination / Q000295:instrumentation / Q000379:methods*; D012815:Signal Processing, Computer-Assisted; D055815:Young Adult
keywords: Neural Network; Pulse diagnosis instrument (PDI); Pulse-taking depth; Three positions and nine indicators (TPNI); Traditional Chinese medicine (TCM)