Department of Electrical Engineering, Instrumentation Chip Group, National Cheng Kung University, Tainan, Taiwan.
J Altern Complement Med. 2012 Oct;18(10):924-31. doi: 10.1089/acm.2012.0047.
A stringlike pulse is highly related to hypertension, and many classification approaches have been proposed in which the differentiation pulse wave (dPW) can effectively classify the stringlike pulse indicating hypertension. Unfortunately, the dPW method cannot distinguish the spring stringlike pulse from the stringlike pulse so labeled by physicians in clinics.
By using a Bi-Sensing Pulse Diagnosis Instrument (BSPDI), this study proposed a novel Plain Pulse Wave (PPW) to classify a stringlike pulse based on an array of pulse signals, mimicking a Traditional Chinese Medicine physician's finger-reading skill.
In comparison to PPWs at different pulse taking positions, phase delay Δθand correlation coefficient r can be elucidated as the quantification parameters of stringlike pulse. As a result, the recognition rates of a hypertensive stringlike pulse, spring stringlike pulse, and non-stringlike pulse are 100%, 100%, 77% for PPW and 70%, 0%, 59% for dPW, respectively.
Integrating dPW and PPW can unify the classification of stringlike pulse including hypertensive stringlike pulse and spring stringlike pulse. Hence, the proposed novel method, PPW, enhances quantification of stringlike pulse.
弦脉与高血压高度相关，已有许多分类方法被提出，其中差分脉搏波（dPW）可有效区分指示高血压的弦脉。然而，dPW 方法无法区分春弦脉与临床上医生标记的弦脉。
本研究通过使用双传感脉象诊断仪（BSPDI），提出了一种新的平脉波（PPW），通过模拟中医切脉的手法，基于一系列脉象信号来对弦脉进行分类。
与不同取脉位置的 PPW 相比，相位延迟 Δθ和相关系数 r 可以作为弦脉的量化参数。因此，PPW 对高血压弦脉、春弦脉和非弦脉的识别率分别为 100%、100%和 77%，而 dPW 分别为 70%、0%和 59%。
整合 dPW 和 PPW 可以统一包括高血压弦脉和春弦脉在内的弦脉分类。因此，所提出的新方法 PPW 增强了弦脉的量化。
