Fourier Series Analysis for Novel Spatiotemporal Pulse Waves: Normal, Taut, and Slippery Pulse Images.

In this article, a three-dimensional pulse image (3DPI) instead of a one-dimensional temporal pulse wave is studied to elucidate its spatiotemporal characteristics. To check the spatial and temporal properties of 3DPI, adopted is Fourier series, in which a ratio (r) is defined as one amplitude divided by the sum of the first three amplitudes of harmonics. A ratio sequence is constituted from 70 to 90 ratios in a heartbeat with 70-90 3DPIs by sampling. Twenty-four subjects (14 males and 10 females with age of 22.2 ± 3.7 years, 20.4 ± 1.4 BMI, and 112.1 ± 4.7 mmHg systolic blood pressure) are involved in this research. There are significant statistical differences in the groups of the normal, taut, and slippery 3DPIs by the first harmonic ratio average ( r 1 ¯ ) and ratio difference (Δr 1) produced from the ratio sequence. The proposed method of this study gives us a novel viewpoint to clarify the spatiotemporal characteristics of pulse images, which can translate and quantize the pulse feeling in Chinese medicine texts.

Neural network study for standardizing pulse-taking depth by the width of artery.

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.

How to standardize the pulse-taking method of traditional Chinese medicine pulse diagnosis.

The aim of this report is to propose standard pulse taking procedure of Traditional Chinese Medicine Pulse Diagnosis. In order to acquire full information from taking a wrist pulse, this proposal adopts a tactile sensor with 12 sensing points at one sensing position, such as Cun, Guan, or Chi. Simultaneously Palpation (SP) and Pressing with One Finger (PWOF) are adopted to explore their differences of the detected pulse signals. According to vertical dynamic characteristics, the results of a Pearson product moment reveal that the correlation coefficients of PWOF and SP are highly correlated from Fu to Chen. In addition, according to unique characteristics of body state, the results of a paired samples t test reveal that the SP and PWOF are indifferent at a specific pulse taking depth. Hence, if using the pulse-taking instrument with tactile sensors, it is concluded that pulse signals taken by familiar SP and PWOF methods are shown in statistical indifferences among seven parameters (Vppmean,Vppmax, HR, LENGTH, WIDTH, AS, and DS).

Stringlike pulse quantification study by pulse wave in 3D pulse mapping.

BACKGROUND: 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. DESIGN: 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. RESULTS: 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. CONCLUSIONS: 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.

Temporal and spatial properties of arterial pulsation measurement using pressure sensor array.

Conventionally, a pulse taking platform is based on a single sensor, which initiates a feasible method of quantitative pulse diagnosis. The aim of this paper is to implement a pulse taking platform with a tactile array sensor. Three-dimensional wrist pulse signals are constructed, and the length, width, ascending slope, and descending slope are defined following the surface of the wrist pulse. And the pressure waveform of the wrist pulse obtained through proposed pulse-taking platform has the same performance as the single sensor. Finally, the results of a paired samples t-test reveal that the repeatability of the proposal platform is consistent with clinical experience. On the other hand, the results of ANOVA indicate that differences exist among different pulse taking depths, and this result is consistent with clinical experience in traditional Chinese medicine pulse diagnosis (TCMPD). Hence, the proposed pulse taking platform with an array sensor is feasible for quantification in TCMPD.