Wrist blood flow signal-based computerized pulse diagnosis using spatial and spectrum features

Zhang, Dongyu; Zuo, Wangmeng; Zhang, David; Zhang, Hongzhi; Li, Nai-Min

doi:10.4236/jbise.2010.34050

Cited by 63 publications

(20 citation statements)

References 16 publications

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“…Ultrasonic duplex imaging provides arterial blood velocity changes during the cardiac cycle [20], while the arterial CSA can be achieved from sequences of B-mode ultrasonic images [21]. The uniqueness of the proposed method is to consider Eq (3) during cardiac cycles.…”

Section: Methodsmentioning

confidence: 99%

Assessing the blood pressure waveform of the carotid artery using an ultrasound image processing method

et al. 2017

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PurposeThe aim of this study was to introduce and implement a noninvasive method to derive the carotid artery pressure waveform directly by processing diagnostic sonograms of the carotid artery.MethodsUltrasound image sequences of 20 healthy male subjects (age, 36±9 years) were recorded during three cardiac cycles. The internal diameter and blood velocity waveforms were extracted from consecutive sonograms over the cardiac cycles by using custom analysis programs written in MATLAB. Finally, the application of a mathematical equation resulted in time changes of the arterial pressure. The resulting pressures were calibrated using the mean and the diastolic pressure of the radial artery.ResultsA good correlation was found between the mean carotid blood pressure obtained from the ultrasound image processing and the mean radial blood pressure obtained using a standard digital sphygmomanometer (R=0.91). The mean absolute difference between the carotid calibrated pulse pressures and those measured clinically was -1.333±6.548 mm Hg.ConclusionThe results of this study suggest that consecutive sonograms of the carotid artery can be used for estimating a blood pressure waveform. We believe that our results promote a noninvasive technique for clinical applications that overcomes the reproducibility problems of common carotid artery tonometry with technical and anatomical causes.

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Section: Methodsmentioning

confidence: 99%

Assessing the blood pressure waveform of the carotid artery using an ultrasound image processing method

et al. 2017

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“…They mentioned criteria for abnormality. The method proposed by Dong Yu Zhang et al [7] is effective and promising in distinguishing healthy people from patients with cholecystitis or nephritis. The blood flow velocity signal was collected using Doppler ultrasound device and preprocessed.…”

Section: Introductionmentioning

confidence: 99%

Diagnosis of Disease Using Wrist Pulse Signal for classification of pre-meal and post-meal samples

Khaire¹,

Joshi²

2015

2015 International Conference on Industrial Instrumentation and Control (ICIC)

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Diagnosis of disease is done by physical examination of patient by physician. For internal observation physician requires help of sonography, MRI, pathological tests reports etc. In Ayurveda Nadi-Pariksha (pulse examination) is used for making the diagnosis. It uses pulse signal sensed at radial artery on wrist below the thumb for diagnosis manually. The pulse signal contains very useful information related to human body. In some cases physician needs patient to tell symptoms of disease. For babies and animals it is not possible to tell the symptoms. To overcome the above mentioned problems a system for 'Diagnosis of Disease Using Wrist Pulse Signal' based on Nadi-Pariksha has been investigated. As an example pulse diagnosis has been investigated for detecting whether the person has taken meal or not. Hardware has been developed for recording pulse from wrist. It contains microphone as sensor, amplifier and low pass filter. In proposed method autocorrelation of signal is taken. Using Fast Fourier Transform spectral features are extracted. Support Vector Machine is used for classification of pulse samples. The experimental results show that pulse signal contains important information for detecting whether the person has taken meal or not. With proposed method accuracy of 88.8% for pre-meal signal and of 81.48% for post-meal signal is obtained.

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“…Using clinical studies and statistical methods, numerous classification models have been proposed to quantify principal pulse qualities (PQs), including the floating, sunken, deficient, excess, moderate, smooth, taut, hollow, and unsmooth PQs [1, 8–15]. Further progress has been made in pulse-signal processing and noise reduction [16–20]. In addition, studies verifying pulse characteristics of palpitation patients [21], dyspepsia and rhinitis patients [22], and cold/heat-stressed humans [23] and studies explicitly comparing pulse characteristics among the three pulse-diagnostic locations [24–26] were recently reported.…”

Section: Introductionmentioning

confidence: 99%

New Assessment Model of Pulse Depth Based on Sensor Displacement in Pulse Diagnostic Devices

Bae

Jeon

Kim

et al. 2013

Evidence-Based Complementary and Alternative Medicine

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An accurate assessment of the pulse depth in pulse diagnosis is vital to determine the floating and sunken pulse qualities (PQs), which are two of the four most basic PQs. In this work, we proposed a novel model of assessing the pulse depth based on sensor displacement (SD) normal to the skin surface and compared this model with two previous models which assessed the pulse depth using contact pressure (CP). In contrast to conventional stepwise CP variation tonometry, we applied a continuously evolving tonometric mechanism at a constant velocity and defined the pulse depth index as the optimal SD where the largest pulse amplitude was observed. By calculating the pulse depth index for 18 volunteers, we showed that the pulse was deepest at Cheok (significance level: P < 0.01), while no significant difference was found between Chon and Gwan. In contrast, the two CP-based models estimated that the pulse was shallowest at Gwan (P < 0.05). For the repeated measures, the new SD-based model showed a smaller coefficient of variation (CV ≈ 7.6%) than the two CP-based models (CV ≈ 13.5% and 12.3%, resp.). The SD-based pulse depth assessment is not sensitive to the complex geometry around the palpation locations and temperature variation of contact sensors, which allows cost-effective sensor technology.

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Wrist blood flow signal-based computerized pulse diagnosis using spatial and spectrum features

Cited by 63 publications

References 16 publications

Assessing the blood pressure waveform of the carotid artery using an ultrasound image processing method

Assessing the blood pressure waveform of the carotid artery using an ultrasound image processing method

Diagnosis of Disease Using Wrist Pulse Signal for classification of pre-meal and post-meal samples

New Assessment Model of Pulse Depth Based on Sensor Displacement in Pulse Diagnostic Devices

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