脈診是中醫診斷中最為神祕的手法，最早紀載於2000多年前的黃帝內經，隨後不斷的演變成為中國的主要診斷手法之一。然而隨著西方醫學的興盛，脈診主觀性的診斷方式逐漸消逝中。有鑒於此，許多學者開始了脈診現代化的研究，其中第一步，也是最重要的關鍵就是脈診儀的開發。機械自動化的取脈方法，可排除人為主觀因素，客觀並可靠的呈現出人體脈象。近幾十年來，脈診儀的發展以單點取脈為主，由於單點取脈無法直接對應於脈象，更忽略中醫兩千年來三部九候取脈對應於全身臟腑的優勢，造成脈診儀大都不被中醫學界所接受，而使得脈診科學化停滯不前，對中醫現代化影響甚鉅。
三部九候之寸口診法為脈診的基本概念，寸口(手腕部)分為寸、關、尺三部，每部分為浮、中、沉三候，是為三部九候。寸、關、尺三部以手腕部突骨定關(prominent bone)已廣泛被現代學者所接受，然而，浮、中、沉卻鮮少被探討，以至於到目前為止皆無明確之規範，使得把脈手法沒有一套可被科學化接受的標準程序。本研究提出以橈動脈血管寬度來定義浮、中、沉。依據解剖生理學角度，為浮、中、沉提出合理的量化方法，使得每個人都能在同一參數值之下，進行脈象的比對。由於血管寬度需要以超音波或紅外線的技術進行量測，而脈象一般以壓力感測為主，為使得脈診儀的製作簡化，本研究提出兩種模型來預測橈動脈血管寬度，一是感測器下壓深度模型，另一個則是以下壓深度與感測器接觸壓力此兩參數為輸入的類神經網路模型。透過脈診儀與超音波儀進行實驗，可計算此二模型之估測血管寬度誤差。
在把脈有參考標準之後，擷取脈象特徵參數是為脈象辨識之前置研究。早期脈診儀皆屬於單點感測的取脈，其資訊並無法將28脈象中的三維脈形表現出來，因此具二維感測陣列之脈診儀蘊育而生。二維感測陣列可將脈波資訊可視化成為三維脈波圖譜(three-dimensional pulse map, 3DPM)的脈象資訊，如此更加逼真於中醫師臨床診斷的手感。本文依據中醫脈診文獻中對於脈象之描繪，以形態學的角度，提出曲面特徵參數擷取方法，來進行3DPM之參數分析，做為中醫臨床診斷的參考。
研究結果顯示，在血管寬度定義15%，45%與75%(相對於血管全寬)為浮、中、沉之條件下，類神經網路模型之預測準確度與精密度分別為1.19%與0.0467相對於下壓深度模型改善了71.62%與29.78%。如此，藉由類神經網路模型的輔助，便可獨立使用脈診儀在預設的血管寬度之下，取得脈搏訊號。
脈搏訊號經由二維陣列壓力感測器偵測便可得到3DPM。為了特徵參數擷取，實驗量取一名健康受測者之3DPM，並利用適當的訊號前處理與曲面擬合技術得此3DPM之擬合多項式。分析此多項式可得到此脈波特徵參數包含：脈波峰值(相對值)與其坐標位置；正規化之脈長與脈寬與一曲率分佈之對應圖譜。另外，應用此方法模擬動脈(指下滑數如珠，狀如大豆)與正常脈之辨識，結果顯示，以3DPM峰值部位的曲率作為鑑別參數，在400組測試樣本中，其正確辨識率可達92.75 %。
現代脈診研究迄今已有30多年的歷史，雖然在各方面已有長足的進步，但大多數仍無法被中醫和西醫所認同。本文以內經、難經、脈經一脈相承為依歸，提出科學化的量化取脈深度與分析3DPM脈象之特徵參數，使得脈診儀的取脈方法有標準規範可依循，為後續脈診研究奠定可靠之根基，脈象研究有疊加之科學進展，對中醫脈診科學化有顯著的貢獻。

Pulse diagnosis (PD) is the most mysterious technique used in traditional Chinese medicine (TCM). The earliest records of PD go back to (Huangdi’s) internal classic, published two thousand years ago. With continuous evolution, it has become one of the major diagnostic techniques in China. However, the subjective nature of PD and the rise of Western medicine have made PD gradually disappear. Many researchers have thus started to promote PD modernization. An important step is the development of a pulse diagnosis instrument (PDI). Pulses can be objectively and reliably measured using robotic fingers; even so, most tactile sensors used in PDIs have only a single sensing element. Pulse-taking with a single sensing element cannot directly map pulse conditions and ignores the advantage of the three positions and nine indicators (TPNI) in TCM. This has severely hindered PD modernization.
The basic concept of PD is TPNI. There are three sections on the wrist, namely Cun, Guan, and Chi. Each section has three levels of depth, namely Fu, Zhong, and Chen. The Guan position, at the prominent bone near the wrist, is widely investigated by modern scholars. However, Fu, Zhong, and Chen are seldom discussed. So far, there is thus no standard scientific protocol for pulse-taking depth. One of the aims of this paper is to define the pulse-taking depths in terms of the width of the artery (WA). It is a reasonable quantitative method for determining Fu, Zhong, and Chen based on the anatomy and physiology. It allows the pulse conditions from various subjects to be fairly compared using one identical parameter. Most tactile sensors in PDIs are pressure sensors that cannot directly measure the WA. Therefore, two models are presented for WA estimation, namely the sensor displacement (SD) model and the artificial neural network (ANN) model with contact pressure (CP) and SD as the inputs. Through a PDI and an ultrasound apparatus experiments, the deviations of estimated WA of these two models are obtained.
With the pulse-taking protocol, feature extraction of pulses is required for pulse condition recognition. A PDI equipped with a single sensing point cannot be used to illustrate the shape of the pulse condition. In contrast, a two-dimensional array tactile sensor can visualize the pulse wave as a three-dimensional pulse map (3DPM), allowing the PDI to obtain pulse information that meets the requirements of TCM physicians. Based on a morphological approach and the descriptions of pulse condition in ancient TCM texts, this study proposes a spatial feature extraction method for parameter analysis of 3DPMs. The ultimate goal is to create a reference for TCM clinical diagnosis.
The results show that the accuracy and precision of the ANN model are 1.19% and 4.67%, respectively, with Fu, Zhong, and Chen defined as 15%, 45%, and 75% of the full WA. Compared with the SD model, the improvements are 71.62% in accuracy and 29.78% in precision. Therefore, pulse signals can be obtained in a certain WA by using the PDI with the ANN model assistance.
Pulse signals can be represented as a 3DPM via a two-dimensional array sensor. To obtain the characteristic parameters of pulses, a 3DPM was acquired from a healthy subject. Then, suitable signal processing and curve fitting were applied to obtain the polynomial of the 3DPM. After analysis of the polynomial, the following features of pulses can be quantified: PEAK, WIDTH, LENGTH, and CUREVATURE. This method was applied in a simulation of pulse recognition between a normal pulse and a stirred pulse (a pulse is like a bouncing pea). The results show that the recognition rate is 92.75% for 400 sets of test samples by using the Gaussian curvature values at the peak location of 3DPMs.
Although PD studies have made great progress, most of them are still tough to be accepted by practitioners of TCM and Western medicine. This paper proposes a quantitative method for determining the pulse-taking depth and an analytic method for spatial feature extraction for 3DPMs. It allows the pulse-taking method using a PDI to follow a standard protocol and provides a reliable foundation for further PD study. That has a significant contribution to the TCM PD scientization.

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