Pulse Signal Analysis Research Articles

Identification of motion outliers in wrist pulse signal

Wrist pulse signal (WPS) analysis is a popular method to investigate the health state of the human being. However, presence of outliers is one of the most common problems that persist even after clean-up of the wrist signals which disturb analysis and classification rate. This paper presents a new shape based technique i.e. Canberra-Derivative Dynamic Time Warping (C-DDTW) for detecting the outliers in WPS with the advancement in existing Euclidean Dynamic Time Warping (E-DTW) based algorithm. By employing different distance metrics like Euclidian, Manhattan and Canberra in DTW and DDTW, the problem of unavoidable motion artifacts in wrist pulse signal has been surmounted. Among all the algorithms, the C-DDTW showed best results for all the classification measures. The experimental outcomes demonstrated a noteworthy improvement in performance index for C-DDTW in comparison with existing E-DTW algorithm for outlier identification in WPS.

Micro-piezoelectric pulse diagnoser and frequency domain analysis of human pulse signals

BackgroundThe theory of pulse diagnosis is to assess the physiological condition of the human body using radial pulse. However, pulses can vary markedly from person to person. Further, pulse diagnosis is difficult to learn and requires one-on-one teaching. MethodsTo address this problem, we built a home-made pulse diagnoser and measured human pulses for studying the standardization of pulse diagnosis. Our pulse diagnoser was composed of a piezoelectric transducer, differential amplifier, data acquisition instrument, and a Matlab analysis program. The measured pulses were converted into electronic signals by a piezoelectric transducer and saved on a computer. The digitalized data were then refined and analyzed by fast Fourier transform for frequency analysis. Simulations were performed to assess the factors that affected the pulse, including phase shifts of reflected pulse waves (generate sub-peaks in pulses), inconsistent heart rates (deform pulse waves), the vessel stiffness (alter harmonic frequencies of the pulses), and the wave amplitudes (determined by the pulse strength). ResultsBy comparing a published report and our simulation findings, we characterized the pulse types and the effects of various factors, and then applied the findings to study actual pulses in patients. Three types of pulses were determined from the frequency spectrum—choppy pulse (Se mai) without apparent harmonic peaks, the harmonic frequencies of wiry pulse (Xian mai) that are non-integer multiples of the fundamental frequency, and surging pulse (Hong mai) that exhibit strong amplitudes in the spectrum of frequency. A normal pulse and a slippery pulse were differentiated by a phase shift, but not by assessing the frequency spectrum. ConclusionThese findings confirm that frequency domain analysis can avoid ambiguity arising in assessing the three types of pulses in the time domain. Further studies of other pulses in the frequency domain are required to develop a precise electronic pulse diagnoser.

Self-Powered Pulse Sensor for Antidiastole of Cardiovascular Disease.

Cardiovascular diseases are the leading cause of death globally; fortunately, 90% of cardiovascular diseases are preventable by long-term monitoring of physiological signals. Stable, ultralow power consumption, and high-sensitivity sensors are significant for miniaturized wearable physiological signal monitoring systems. Here, this study proposes a flexible self-powered ultrasensitive pulse sensor (SUPS) based on triboelectric active sensor with excellent output performance (1.52 V), high peak signal-noise ratio (45 dB), long-term performance (107 cycles), and low cost price. Attributed to the crucial features of acquiring easy-processed pulse waveform, which is consistent with second derivative of signal from conventional pulse sensor, SUPS can be integrated with a bluetooth chip to provide accurate, wireless, and real-time monitoring of pulse signals of cardiovascular system on a smart phone/PC. Antidiastole of coronary heart disease, atrial septal defect, and atrial fibrillation are made, and the arrhythmia (atrial fibrillation) is indicative diagnosed from health, by characteristic exponent analysis of pulse signals accessed from volunteer patients. This SUPS is expected to be applied in self-powered, wearable intelligent mobile diagnosis of cardiovascular disease in the future.

Full-field wrist pulse signal acquisition and analysis by 3D Digital Image Correlation

Pulse diagnosis is an essential part in four basic diagnostic methods (inspection, listening, inquiring and palpation) in traditional Chinese medicine, which depends on longtime training and rich experience, so computerized pulse acquisition has been proposed and studied to ensure the objectivity. To imitate the process that doctors using three fingertips with different pressures to feel fluctuations in certain areas containing three acupoints, we established a five dimensional pulse signal acquisition system adopting a non-contacting optical metrology method, 3D digital image correlation, to record the full-field displacements of skin fluctuations under different pressures. The system realizes real-time full-field vibration mode observation with 10FPS. The maximum sample frequency is 472Hz for detailed post-processing. After acquisition, the signals are analyzed according to the amplitude, pressure, and pulse wave velocity. The proposed system provides a novel optical approach for digitalizing pulse diagnosis and massive pulse signal data acquisition for various types of patients.

Heart rate measurement and electrical pulse signal analysis for subjects span of 20–80 years

The preliminary research constructs the heart beat or pulse measurement for medical science. The electrical pulse signal analysis that supports one significant clinical study. The research prototype focuses the pulse rate and analysis system which consist of hardware and software parts. The hardware uses the ATMEGA 2560 ADK R3 for processing the input optical sensors, output result to LCD, and record data into SD memory card. The software as embedded algorithm is designed for controlling the input/output parts. Research techniques are applied in term of analog to digital converter, I2C, and data grouping.The 40 subjects are informed consent and measured with ethical research. Experimental result explains the subject behaviors with maximum/minimum pulse values, patterns, and similarity three groups. The distinctive point of medical and health science prototype is accuracy, durability, low power consumption, and cheaper price.

Feature Extraction of Wrist Pulse Signals using Gabor Spectrogram

Background/Objectives: The practice of Ayurveda has been long followed in India which is based on the analysis of wrist pulse signal for diagnosing human health. The pulse signal is a non-stationary signal. A signal can be analyzed in either time domain, frequency domain or joint time-frequency domain. This paper highlights the need of joint time-frequency analysis for a non-stationary signal and provides an approach of analyzing wrist pulse signals in time-frequency domain using Gabor Spectrogram. Methods/Statistical Analysis: The work in this paper has been done using Virtual Instruments (VI’s) in ®LabVIEW. In this paper, band pass filter and wavelet de-noising technique has been used for pre-processing of raw pulse signals. Segmentation and Normalization has been performed on the noise free pulse signals. For representing the pulse signals in t-f space, Gabor Spectrogram has been used. The Gabor Spectrogram is a time-frequency distribution technique that offers good time-frequency resolution and negligible cross term interference. The performance has been analyzed using a parameter Mean Square Error (MSE). Findings: Various features: Mean Instantaneous Frequency (MIF), Mean Instantaneous Bandwidth (MIB), Frequency Marginal Integral (FMI), Time Marginal Integral (TMI) and Group Delay (GD) have been extracted in t-f domain for pulse signals from healthy subjects and correlation has been performed. The extracted features for different healthy subjects show similarity in variation pattern even though the actual signals differ in time domain, illustrated through correlation, which marks a successful attempt towards the significance of time-frequency distribution for pulse signals. Application/Improvement: These features can prove very significant in health diagnosis of human beings.

Devising an information system for the analysis of pulse signals

Розробка інформаційних технічних систем медичного призначення дає змогу інтенсифікувати процедуру діагностики, прогнозувати та аутентифікувати стан людини, створює можливість проведення комп’ютерних модельних та імітаційних експериментів. Розглянуто основні критерії класифікації пульсограм із встановленням причин їх обмеженої дієвості для аналізу тривалих часових послідовностей.

Pulse signal analysis of patients with coronary heart diseases using Hilbert-Huang transformation and time-domain method.

To explore characteristic of pulse signal to distinguish patients with coronary heart diseases (CHD) from patients without CHD and healthy adults, and accordingly evaluate the potential role of pulse signal to diagnosis CHD. Totally 407 patients enrolled from 4 collaborating medical centers were assigned to a CHD group (205 patients) and a non-CHD group (202 patients). The healthy control group (62 adults) enrolled from Shanghai University of Traditional Chinese Medicine. Pulse signals were collected using the synchronous multiplex pulse signal acquisition system. The pulse signals were analyzed and extracted using Hilbert-Huang transformation (HHT) and time-domain, respectively. The time-domain parameters of pulse signal were processed by the analysis of variance (SNK test). Special patterns in the CHD group pulse signal were found in this study: (1) time-domain parameters of pulse signal, h1, h3, h4, h3/h1, ts, t4/t were increased and w was wider; (2) 44% of C2 waves in HHT were chaotic and disordered and 72% of C waves were exhibited irregularly with average amplitude over 10 g-forces, which were all significantly different from controls. Characteristic wave and time-domain parameters of pulse signal were extracted using HHT and time-domain which could be served as a non-invasive approach for assessing patients with CHD.

Traditional Indian Medicine (TIM) based Humor Identification A recurrence based Approach

Objective analysis and interpretation of radial pulse signal has been attempted. Capacitance variation based sensing and instrumentation mechanism has been developed for pulse sensing and logging. Traditional Indian Medicine (TIM) perspective for humor identification has been attempted. Pulse signal of healthy individual analysed in dominant humor interval, display prominent changes in recurrence quantification measures for pulse amplitude variations. These marker results are observed to correlate strongly with those obtained for a group of healthy individuals in a dominant humor interval period. Recurrence quantification analysis can possibly help in arriving at inferences apparent to sense perception for a TIM physician. General Terms Biomedical Signal Processing, Traditional Indian Medicine(TIM) – Ayurveda.

A Compound Pressure Signal Acquisition System for Multichannel Wrist Pulse Signal Analysis

In traditional Chinese pulse diagnosis (TCPD), to analyze the health condition of a patient, a practitioner should put three fingers on the wrist of the patient to adaptively feel the fluctuations in the radial pulse at the styloid processes. Thus, for comprehensive pulse signal acquisition, we should efficiently and accurately capture pulse signals at different positions and under different pressures. However, most conventional pulse signal acquisition devices can only capture signal at one position and under a fixed pressure, and thus only capture limited pulse diagnostic information. In this paper, we propose our novel solution to the problems of sensor positioning, sensor array design, pressure adjustment, and mechanical structure design, resulting in a compound system for multichannel pulse signal acquisition. Compared with the other systems, our system provides a systematic solution to sensor positioning, is effective in measuring the width of the pulse, and can capture multichannel pulse signals together with subsignals under different hold down pressures. Experimental results show that multichannel signals can achieve higher classification performance than single-channel signals.

Time and frequency domain analysis of wrist pulse signals for health diagnosis

Wrist pulse analysis is an approach of health diagnosis described in ancient Indian medicine. This approach is based on the analysis of three fingertip palpations observed over radial artery of both the hands. These three palpations identified as Vata, Pitta and Kapha in this approach are described by their unique characteristics. The characteristics of Vata and Pitta signals are explained by an irregularity present in the signal and the jumping or throbbing nature associated with the signal, respectively. In this paper, these wrist pulse signals are analysed in healthy and unhealthy subjects with the help of time and frequency domain signal processing techniques. Several pulse parameters are computed and their correlation is established with the corresponding pulse characteristics defined in ancient literature. These pulse parameters are also verified for their significant variations in healthy and unhealthy states of the subjects.

A case control study using radial artery pulse signals to evaluate the low pulsatility index in Koreans

Background: Noninvasive radial artery pulse signal analysis has been widely used to assess vascular diseases,but there is no evidence of a relationship between the radial artery pulse signal and pulsatility index. Objective: To determine whether radial artery pulse signal changes in patients with a low pulsatility index would provide diagnostic information for evaluating vascular disease. Methods: In this case control study, 36 Korean subjects were distributed into two groups, a normal pulsatility index group and a low pulsatility index group, based on their Doppler test results. Multivariate logistic regression analysis of these two groups was conducted to identify significant radial artery pulse signals for evaluating the low pulsatility index. A receiver operating characteristic (ROC) curve analysis was used to evaluate the logistic model. Results: The low pulsatility index group displayed significantly different radial artery pulse signals compared with the normal pulsatility index group (A1; primary amplitude of right Cun, ?1; shape of the primary wave of right Chi, ?2: secondary phase of left Cun, ?2/L: ratio of the shape of the secondary wave to the length of a single-period waveform). A predictive value for the low pulsatility index was obtained using binary logistic regression, which included A1, ?1, ?2 and ?2/L. A ROC curve analysis assessed the accuracy of the test for lowpulsatility index evaluation (AUC=0.931). Conclusion: A1 (primary amplitude), ?1 (shape of the primary wave), ?2 (secondary phase), and ?2/L (ratio ofthe shape of the secondary wave to the length of a single-period waveform) derived from radial artery pulsesignals may be used to assess a low pulsatility index in Koreans. Keywords: Aortic obstruction, pulsatility index, pulse signal, radial artery, vascular disease

Validation of Noninvasive MOEMS-Assisted Measurement System Based on CCD Sensor for Radial Pulse Analysis

Examination of wrist radial pulse is a noninvasive diagnostic method, which occupies a very important position in Traditional Chinese Medicine. It is based on manual palpation and therefore relies largely on the practitioner′s subjective technical skills and judgment. Consequently, it lacks reliability and consistency, which limits practical applications in clinical medicine. Thus, quantifiable characterization of the wrist pulse diagnosis method is a prerequisite for its further development and widespread use. This paper reports application of a noninvasive CCD sensor-based hybrid measurement system for radial pulse signal analysis. First, artery wall deformations caused by the blood flow are calibrated with a laser triangulation displacement sensor, following by the measurement of the deformations with projection moiré method. Different input pressures and fluids of various viscosities are used in the assembled artificial blood flow system in order to test the performance of laser triangulation technique with detection sensitivity enhancement through microfabricated retroreflective optical element placed on a synthetic vascular graft. Subsequently, the applicability of double-exposure whole-field projection moiré technique for registration of blood flow pulses is considered: a computational model and representative example are provided, followed by in vitro experiment performed on a vascular graft with artificial skin atop, which validates the suitability of the technique for characterization of skin surface deformations caused by the radial pulsation.

Procedure for Formation of Features of the Radial Artery Pulsation Signal

Existing methods for quantitative analysis of quasi-periodic signals are discussed. The technological and experimental basis of such methods is described. Automatic algorithms for periodic analysis of pulse signals are suggested. These methods are based on the use of real-time signals, as well as local waves within single periods. The results of comparative analysis of different pulsation signals of various spectral densities are described.

NON-INVASIE MICRO-OPTO-ELECTRO-MECHANICAL SYSTEM ADAPTATION TO RADIAL BLOOD FLOW PULSE AND VELOCITY ANALYSIS

Radial pulse examination is one of the most important diagnostic methods in traditional Chinese medicine. It has been used in establishing diseases and in guiding medicine selection for thousands of years. Blood flow fluctuation types present in radial artery contains rich and critical information which can reflect the state of various problems with health. Having precisely mastered the art of blood flow pulse practitioners can exactly determine what kind of health problems (i.e. problems with: gallbladder, kidneys, stomach, lungs, heart, high level of cholesterol and more) the patient has. Being non-invasive diagnostic technique this type of examination depends on the practitioner’s subjective analysis and may be unreliable and inconsistent. In this paper, we present novel computerized non-invasive micro-opto-electro-mechanical radial pulse signal analysis techniques strongly correlating with the valuable knowledge of traditional Chinese medicine. First, the fluctuations of blood flow are registered by laser triangulation displacement sensor. Then, using computer based techniques the signal is filtered from possible noise. Possible prototype model of final object is presented. Experiment results show that the proposed system works accurately and could be especially effective and helpful in ambulance medicine because of its portability and manufacturing price. DOI: http://dx.doi.org/10.5755/j01.mech.18.4.2343

A fast digital timing and analysis system based on real-time dCFD technique for nuclear physics experiments

In this paper a fast digital real-time spectrometer was developed for timing and analysis of nuclear pulse signals. The hardware system design and algorithm implementation with field-programming gate array (FPGA) and digital signal processor (DSP) were introduced. The performance of the digital constant fraction discrimination (dCFD) platform was experimentally tested with Agilent 80 MHz function/arbitrary waveform generator and LaCl3:Ce3+ scintillator detector for 22Na positron annihilation gamma spectroscopy. The amplitude and time information of γ photon was online obtained. The energy resolution could be 5.525% and the timing resolution 293.75 ps, the system error estimation of dCFD approach was also studied. The results showed that this spectrometer achieved a timing resolution close to that of traditional CFD timing resolution with a more simplified system structure.

P02.76. Impedance plethysmographic (IPG) pulse signal analysis based personalized diagnostics & treatment simulating Ayurvedic pulse examination

P02.76. Impedance plethysmographic (IPG) pulse signal analysis based personalized diagnostics & treatment simulating Ayurvedic pulse examination

Complexity analysis of wrist pulse signals

Pulse pressure signals observed over radial artery have been utilised as bio-medical signals for health diagnosis as described by ancient Indian medicine where Vata, Pitta and Kapha are believed as three basic elements regulating the health conditions. Complexity analysis of all the six pulse signals has been carried out using Entropy for healthy and unhealthy subjects suffering from Gastrointestinal disorders. Complexity and its variability within pulse segments are found to be significantly higher in Vata pulse signal of both the hands. The findings are correlated with the principles described in Ayurveda for Vata element.

A New Two-Pulse Synthesis Model for Digital Volume Pulse Signal Analysis

Analysis of digital volume pulse (DVP) signal measured by photoplethysmograph (PPG) technique is a low cost non-invasive method of obtaining vital information related to arterial conditions. In this paper, we present a new two-pulse synthesis (TPS) model for deriving arterial parameters, useful for noninvasive assessment of human vascular health. The model is based on the use of Rayleigh function. Relevance of the proposed model is established by applying it on a sample set of 113 PPG signals, obtained form healthy and treated hypertensive subjects. The TPS model compares well with the conventional methods in determining parameters such as pulse transit time or foot-to-foot delay (D), reflection index (RI), stiffness index (SI) and pulse wave velocity (PWV). A new parameter, viz. differential pulse spread (DPS) has also been introduced for DVP signals using the model. The differential pulse spread provides a new dimension to estimate the process of arterial degeneration.

SignalCAD: A Digital Signal Processing Software for Forced and Ambient Vibration Testing of Engineering Structures

Abstract Commercial tools for measurement and analysis of vibration signals have traditionally been very expensive. In the last decade, however, multi-channel measurement systems have become relatively inexpensive. The analysis functionality in most inexpensive instruments is limited. Therefore, many companies are using alternatives for post processing of measurement results. MATLAB is a platform that is popular for this purpose and which offers many advantages over dedicated menu driven systems. The open functions in MATLAB assure flexibility and the possibility to modify functions for specific needs. In this paper, the presentation and numerical applications of an interactive and comparative digital signal processing software developed in MATLAB by writers is described. The software is named as SignalCAD. For developing SignalCAD, about 120 new functions have been created and are used with MATLAB Signal Processing Toolbox functions. The SignalCAD program is a powerful tool that deals with processing raw measured data obtained from forced and ambient vibration testing of engineering structures. SignalCAD offers extensive functionalities for the visualization and processing of the measurement data and the determination and visualization of the spectral analysis results. The program disposes of a graphical user interface, which what makes it very intuitive and easy to handle. The most common spectral analysis techniques have been used in SignalCAD. The possibilities of the program are demonstrated with a three dimensional steel frame model vibration test and some results are compared with commercial PULSE signal analysis software.