Ching-Hsing Luo

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.

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

BACKGROUNDnA 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.nnnDESIGNnBy 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 physicians finger-reading skill.nnnRESULTSnIn 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.nnnCONCLUSIONSnIntegrating 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.

Exploring the conventional pulse conditions using bi-sensing pulse diagnosis instrument

Pulse diagnosis is one of the efficient techniques to detect the health status of a patient. However, pulse diagnosis suffers from a viewpoint of nonscientific and subjectivity. The goal of this report wants to propose an outline to integrate both the quantification of pulse diagnosis and application of clinic. Hence, the definitions of the quantifiable parameter are followed by clinical experiences. These core parameters are classified into four categories: position, rate and rhythm, shape, and trend. Using Bi-Sensing Pulse Diagnosis Instrument (BSPDI) to acquire wrist artery information for interpreting pulse conditions. The DS (Depth-Strength) curve can be classified the pulse condition whether it belongs to floating pulse or sunken pulse; and similarly, DR (Depth-Rate-Rhythm) curve to rapid pulse or slow pulse, DW (Depth-Width) curve to fine pulse or large pulse, DL (Depth-Length) curve to long pulse or short pulse. The pulse conditions will be understood based on these curves and pulse diagnosis is no more subjectivity and nonscientific.

Spatial feature extraction from wrist pulse signals

Pulse diagnosis is an important diagnostic method in traditional Chinese medicine. However, it lacks objectivity. To standardize pulse diagnosis, pulse-taking platforms are required. This study implements a complete processing method for wrist pulse signals obtained from a pulse diagnosis instrument with a two-dimensional pressure sensor array to extract the spatial features. First, a zero-phase filter is adopted for acquiring the appropriate frequency band for bio-signals and removing noise. The filter is better to extract the pulse trend due to no phase shift distortion. Next, irregular pulses are removed prior to signal analysis. Then, percussion peaks are identified and the interval between them is used to calculate the pulse rate. Finally, a polynomial surface fitting method is used to compute pulse features, such as the peak, length, width, and surface curvature, from a visualized pulse, which is helpful for the study of pulse classification or even pulse diagnosis.

A new pulse pillow of Traditional Chinese Medicine - The Wrist Fixer System

This research developed a new Wrist Fixer System and used it to fix the patients wrist as the Traditional Chinese Medicine (TCM) doctors did to make Pulse Diagnosis. The system contains a wrist fixer made by two step motors with a specific structure, a PC-Based controller, an USB input output interface card, and two Accelerometers. The four diagnostic methods in TCM are Inspection, Listening and Smelling Examination, Inquiry, and Palpation, and the Palpation is the most objective diagnostic method. When TCM doctors make the pulse diagnosis, they always use the pulse pillow to fix the patients wrist. Besides fixing the patients wrist, it can also make the radial artery of wrist horizontal. Bi-Sensing Pulse Diagnosis Instrument (BSPDI) is a tool used to take pulse from patients wrist automatically. This research was done to make a Wrist Fixer System and used it to fix the patients wrist when BSPDI took pulse. And using the ultrasonic to verify shapes of the patients wrist radial artery could be found that the wrist fixer reconstruct the angle and position of patients wrist. The angle of patients wrist which is fixed on the wrist fixer system is similar to that of being put on TCM Pulse Pillow. It enables the BSPDI to take pulse accurately.

New vision of the pulse conditions using Bi-Sensing Pulse Diagnosis Instrument

Clinical experiences of pulse diagnosis are possible to be quantified and get rid of the viewpoint of nonscientific and subjectivity. The aim of this report wants to propose a new vision of pulse conditions by version 2 of Bi-Sensing Pulse Diagnosis Instrument (BSPDI V2). BSPDI V2 can repeat the pulse taking depth of physicians by displacement detection system, and mimic the fingertip sensations by pulse detection system. The 3-Dimension Pulse Mapping (3DPM) of pulse conditions can be constructed by BSPDI V2. Hence, the new vision platform of pulse conditions is to be built through BSPDI V2. Therefore, pulse conditions can be stereoscopic observation based on spatial and temporal dimensions. The more information and clearer outline of pulse conditions are to be explored, and the quantification of pulse patterns will much closer to fingertip sensations of physicians.

The Wrist Fixer System of Three Position and Nine Indicators Pulse Diagnosis Instrument

The research is to develop a Wrist Fixer System which is used by Three Position and Nine Indicators Pulse Diagnosis Instrument (TPNI Pulse Diagnosis Instrument). The system contains a PC-Based Controller, a Wrist Fixer, an USB I/O card, and two Accelerometers. Chinese doctors practiced the methods for inspection. They practiced listening, smelling, inquiry, and palpation to make diagnoses in Traditional Chinese Medicine (TCM). Actually, Palpation is the best method to know the patients physiology. TPNI Pulse Diagnosis Instrument is a tool which is used to show and analyze the feeling of the doctors fingers. The signal is showed by 3D map. And it is helpful for the quantification of pulse diagnosis and its research afterward in TCM. The sampling procedure of TPNI Pulse Diagnosis Instrument is that the Chinese doctor set the location of Cun, Guan, Chi, Fu, Zhong, Chen and get the signal of pulse diagnosis by using the location data. In TCM, Chinese doctor used pulse pillow to fix the patients wrist. And this research is to design a Wrist Fixer System which can record the angle data of the patients wrist and reply it when the TPNI Pulse Diagnosis Instrument is sampling the signal. In addition, the correctness can be promoted. The system has been tested and it can record the angle data of the patients wrist and reply it at the time when TPNI Pulse Diagnosis Instrument gets the signal correctly.

Pulse differences and 3D pulse mapping in TPNI displacements

Pulse diagnosis is one of the most important examinations in Traditional Chinese Medicine (TCM). Regardless the fact of the subjectivity and fuzziness of pulse diagnosis in TCM, the displacement of Fu (superficial pressure), Zhong (medium pressure), Chen (deep pressure) at the location of Cun (upper), Guan (medium), Chi (lower) on the wrist during pulses diagnosis is still under discovering so far. In this paper, a novel Bi-Sensing Pulse Diagnosis Instrument (BSPDI) was provided quantifiable Traditional Chinese Medicine Pulse Diagnosis (TCMPD) research. Moreover, using signal processing algorithms, the core characteristics of three-dimension pulse mapping (3DPM) are identified, including strength, rate, length, width and trends. BSPDI can conduct the quantitative research of pulse diagnosis to discover the empirical finger-reading models published in the TCM books.

An ECG Acquisition System Prototype Design With Flexible PDMS Dry Electrodes and Variable Transform Length DCT-IV Based Compression Algorithm

In this paper, a system is designed using flexible poly-dimethylsiloxane (PDMS) dry electrodes instead of wet electrodes to acquire electrocardiogram (ECG) signals. This flexible PDMS dry electrode (FPDE) is revised from the hard commercial biopotential conductive snap to a flexible electrode using a replica method that provides a reliable attachment for the ECG measurement method. The measurement result shows the proposed FPDE, which has the ability to acquire ECG signals, is comparable with the traditional wet electrodes applied in medicine. In addition, an acquisition circuit design integrated with commercial ICs and an field-programmable gate array (FPGA) platform is built for the development of longterm ECG monitoring. A variable-transform-length DCT-IVbased ECG compression algorithm with a higher quality score (QS) and a better compressing ratio (CR) is further proposed to significantly reduce the large amount of recording data in both storage and transmission. The QS parameter, which denotes a ratio of a CR value to a percent rms difference (PRD) value, is another key index applied to fairly evaluate the performance of various compression algorithms. DCT-IV is used as a unified transform kernel for ECG signal encoding and decoding, because the forward DCT-IV formula is the same as its inverse. It can be easily converted into a compact hardware accelerator with fewer hardware resources. To fairly evaluate the proposed compression algorithm, ECG signals sourced from MIT-BIT arrhythmia database with a sampling rate of 360 Hz are employed as the test patterns. The simulation results show the averages of CR, PRD, and QS to be 6.86, 0.18, 2.60, 1.68, 32.19, and 39.86, respectively, for all 48 lead-II patterns of the MIT-BIH database. Compared with Lee et al.s DCT-II based algorithm, the QS value of the proposed method exhibits a 76% improvement. The experimental results clearly show that the proposed system would be a better choice for achieving ECG signal acquisition in the future.