Using an array sensor to determine differences in pulse diagnosis—Three positions and nine indicators

Artificial Intelligence-Enabled Novel Atrial Fibrillation Diagnosis System Using 3D Pulse Perception Flexible Pressure Sensor Array

Atrial fibrillation (AF) as one of the most common cardiovascular diseases has attracted great attention due to its high disability and mortality rate. Thus, a timely and effective recognition method for AF is of great importance for diagnosing and preventing it. Herein, we proposed a novel intelligent sensing and recognition system for AF which combined Traditional Chinese Medicine (TCM), flexible wearable electronic devices, and artificial intelligence. Experiment and simulation synergistically verified that the flexible pressure sensor arrays designed according to the TCM theory could synchronously obtain the 3D pulses at Cun, Guan, and Chi. Combined with a homemade signal acquisition system and the pulse signals labeled by doctors of cardiovascular diseases, the differences in the 3D pulse signals between ones with AF and without can be picked up clearly. Enabled the convolutional neural network (CNN) and the pulse database, the recognition model was formed with a recognition rate of up to 90%. As a proof of concept, the artificial intelligence-enabled novel atrial fibrillation diagnosis system has been used to detect patients with AF in hospitals, showing 80% recognition rate. This work provides a new strategy to precisely diagnose and remotely treat AF, as well as to accelerate the development of Modern Chinese Medicine treatment.

A comprehensive review on technological advancements for sensor-based Nadi Pariksha: An ancient Indian science for human health diagnosis

Nadi Pariksha is a significant, rather symbolic term for Ayurveda. Ancient Ayurvedic literature has prominently stated its importance in the judgment of Tridoshas (Vata, Pitta, and Kapha) which are the base of ailment diagnosis and prediction. The knowledge about Nadi Pariksha is uncovered in various ancient Ayurvedic literature like Ravansamhita, Bhavprakash, Nadivigyan by Kanad, Sharangdhar, and Yogratnakar. The various Nadi parameters are indicative of the diagnosis of diseases. These techniques were used as popular diagnostic tools in Indian culture from ancient days. Still, nowadays, these are not being used explicitly due to the lack of expertise, so it is necessary to establish their results once gained so that they can be used along with technical aspects in today's era. Ayurveda believes that all the elements of the Universe are present in any human body in minute, proportionate quantity, and the Nadi represents these elements, that is, Vata, Pitta, and Kapha (VPK). To facilitate the Nadi Pariksha using appropriate sensors may help the Ayurveda practitioners diagnose Prakriti and predict some diseases, making the Nadi Pariksha more reliable and faster. This review paper lists, 2 books and 67 research papers, mostly from countries like India, China, Japan, Korea, etc., from various reputed databases. The review primarily concentrates on six research themes: sensors and devices used for Nadi signal acquisition, signal pre-processing methods, feature extraction methods, feature selection approaches, classification practices, diseases diagnosed, and results attained. The paper also reviews the challenges in implementing the automated Nadi Pariksha with technological aid, which is a necessity of this period and is a very vibrant research arena. Yet significant work remains to be done, like bridging the gaps between technical and commercial development, and the procedure standardization is also required.

Intelligent Wearable Wrist Pulse Detection System Based on Piezoelectric Sensor Array

The human radial artery pulse carries a rich array of biomedical information. Accurate detection of pulse signal waveform and the identification of the corresponding pulse condition are helpful in understanding the health status of the human body. In the process of pulse detection, there are some problems, such as inaccurate location of radial artery key points, poor signal noise reduction effect and low accuracy of pulse recognition. In this system, the pulse signal waveform is collected by the main control circuit and the new piezoelectric sensor array combined with the wearable wristband, creating the hardware circuit. The key points of radial artery are located by an adaptive pulse finding algorithm. The pulse signal is denoised by wavelet transform, iterative sliding window and prediction reconstruction algorithm. The slippery pulse and the normal pulse are recognized by feature extraction and classification algorithm, so as to analyze the health status of the human body. The system has accurate pulse positioning, good noise reduction effect, and the accuracy of intelligent analysis is up to 98.4%, which can meet the needs of family health care.

Entropy Information of Pulse Dynamics in Three Stages of Pregnancy

The aim of the present study is to use entropy to explore the change of pulse generated by normal pregnant women with gestational. Firstly, the subjects were divided into early (E), middle (M), and late (L) three stages according to gestational age. Then, pulse signals of the Chi position of 90 pregnant women at different gestational ages were collected. Secondly, the four entropies, namely fuzzy entropy (FuEn), approximate entropy (ApEn), sample entropy (SamEn), and permutation entropy (PerEn), were applied to the analysis of the long-term pulse changes of the pregnancy. Finally, the related information about pulse in different stages of pregnancy is given by the analysis of four kinds of entropy. Furthermore, the statistical tests are conducted for further comparison, and the descriptive statistics and the results are presented. In addition, boxplots are employed to show the distribution of four entropies of pregnancy. This work has studied the changes in pulse during pregnancy from quantitative and qualitative aspects. Our results show that entropy improves the diagnostic value of pulse analysis during pregnancy and could be applied to facilitate noninvasive diagnosis of pregnant women's physiological signals in the future.

Pulse taking by a piezoelectric film sensor via mode energy ratio analysis helps identify pregnancy status

In order to solve the problem of non-invasive diagnosis and monitoring of women during pregnancy, a piezoelectric film pulse sensing system combined with the mode energy ratio (MER) analysis is utilized to detect human pulses to reveal pregnant conditions. Inspired by traditional Chinese medicine (TCM), pulse diagnosis has a history of more than 2,500 years. The life energy of the human body helps the diagnosis of the disease through the circulation of blood vessels connected to the organs. A PVDF piezoelectric film sensor is used to emulate the pulse taking process in TCM to record the pulse signals. And the algorithm of MER is proposed based on empirical mode decomposition (EMD). Through the MER analysis of 83 female volunteers with different pregnancy statuses, the identification and warning of pregnancy status and physical health indicators are realized.

Inter-Patient Classification With Encoded Peripheral Pulse Series and Multi-Task Fusion CNN: Application in Type 2 Diabetes

Diabetes mellitus, a chronic disease associated with elevated accumulation of glucose in the blood, is generally diagnosed through an invasive blood test such as oral glucose tolerance test (OGTT). An effective method is proposed to test type 2 diabetes using peripheral pulse waves, which can be measured fast, simply and inexpensively by a force sensor on the wrist over the radial artery. A self-designed pulse waves collection platform includes a wristband, force sensor, cuff, air tubes, and processing module. A dataset was acquired clinically for more than one year by practitioners. A group of 127 healthy candidates and 85 patients with type 2 diabetes, all between the ages of 45 and 70, underwent assessments in both OGTT and pulse data collection at wrist arteries. After preprocessing, pulse series were encoded as images using the Gramian angular field (GAF), Markov transition field (MTF), and recurrence plots (RPs). A four-layer multi-task fusion convolutional neural network (CNN) was developed for feature recognition, the network was well-trained within 30 minutes based on our server. Compared to single-task CNN, multi-task fusion CNN was proved better in classification accuracy for nine of twelve settings with empirically selected parameters. The results show that the best accuracy reached 90.6% using an RP with threshold ϵ of 6000, which is competitive to that using state-of-the-art algorithms in diabetes classification.

Portable Interactive Pulse Tactile Recorder and Player System

Pulse palpation is an effective method for diagnosing arterial diseases. However, most pulse measurement devices use preconfigured pressures to collect pulse signals, and most pulse tactile simulators can only display standard or predefined pulse waveforms. Here, a portable interactive human pulse measurement and reproduction system was developed that allows users to take arbitrary pulses and experience realistic simulated pulse tactile feedback in real time by using their natural pulse-taking behaviors. The system includes a pulse tactile recorder and a pulse tactile player. Pulse palpation forces and vibrations can be recorded and realistically replayed for later tactile exploration and examination. To retain subtle but vital pulse information, empirical mode decomposition was used to decompose pulse waveforms into several intrinsic mode functions. Artificial neural networks were then trained based on intrinsic mode functions to determine the relationship between the driving signals of the pulse tactile player and the resulting vibration waveforms. Experimental results indicate that the average normalized root mean square error and the average R-squared values between the reproduced and original pulses were 0.0654 and 0.958 respectively, which indicate that the system can reproduce high-fidelity pulse tactile vibrations.

Computational Traditional Chinese Medicine diagnosis: A literature survey

BACKGROUND AND OBJECTIVE

Traditional Chinese Medicine (TCM) diagnosis is based on the theoretical principles and knowledge, where it is steeped in thousands of years of history to diagnose various types of diseases and syndromes. It can be generally divided into four main diagnostic approaches: 1. Inspection, 2. Auscultation and olfaction, 3. Inquiry, and 4. Palpation, which are widely used in TCM hospitals in China and around the world. With the development of intelligent computing technology in recent years, computational TCM diagnosis has grown rapidly.

METHODS

In this paper, we aim to systematically summarize the development of computational TCM diagnosis based on four diagnostic approaches, mainly focusing on digital acquisition devices, collected datasets, and computational detection approaches (algorithms). Furthermore, all related works of this field are compared and explored in detail.

RESULTS

This survey provides the principles, applications, and current progress in computing for readers and researchers in terms of computational TCM diagnosis. Moreover, the future development direction, prospect, and technological trend of computational TCM diagnosis will also be discussed in this study.

CONCLUSIONS

Recent computational TCM diagnosis works are compared in detail to show the pros/cons, where we provide some meaningful suggestions and opinions on the future research approaches in this area. This work is useful for disease detection in computational TCM diagnosis as well as health management in the smart healthcare area.

INDEX TERMS

Computational diagnosis, Traditional Chinese Medicine, survey, smart healthcare.

Can Traditional Chinese Medicine Diagnosis Be Parameterized and Standardized? A Narrative Review

The integration of Traditional Chinese Medicine (TCM) in Western health systems and research requires a rational communicable theory, scientific proof of efficacy and safety, and quality control measures. The existence of clear definitions and the diagnosis standardization are critical factors to establish the patient's vegetative functional status accurately and, therefore, systematically apply TCM therapeutics such as the stimulation of reflex skin areas known as acupoints. This science-based conceptualization entails using validated methods, or even developing new systems able to parameterize the diagnosis and assess TCM related effects by objective measurements. Traditionally, tongue and pulse diagnosis and the functional evaluation of action points by pressure sensitivity and physical examination may be regarded as essential diagnostic tools. Parameterizing these techniques is a future key point in the objectification of TCM diagnosis, such as by electronic digital image analysis, mechanical pulse diagnostic systems, or the systematic evaluation of acupoints' electrophysiology. This review aims to demonstrate and critically analyze some achievements and limitations in the clinical application of device-assisted TCM diagnosis systems to evaluate functional physiological patterns. Despite some limitations, tongue, pulse, and electrophysiological diagnosis devices have been reported as a useful tool while establishing a person's functional status.

The novel three-dimensional pulse images analyzed by dynamic L-cube polynomial model

A dynamic L-cube polynomial is proposed to analyze dynamic three-dimensional pulse images (d3DPIs), as an extension of the previous static L-cube polynomial. In this paper, a weighted least squares (WLS) method is proposed to fit the amplitude C(t) of d3DPI at four physiological key points in addition to the best fit of L-cube polynomials to the measured normal and cold-pressor-test (CPT)-induced taut 3DPIs. Compared with other two fitting functions, C(t) of a dynamic L-cube polynomial can be well matched by the proposed WLS method with the least relative error at four physiological key points in one beat with statistical significance, in addition to the best fit of the measured 3DPIs. Therefore, a dynamic L-cube polynomial can reflect dynamic time characteristics of normal and CPT-induced hypertensive taut 3DPIs, which can be used as an evidence of hypertension diagnosis.

Radial Pulse Wave Signals Combined with Ba-PWV for the Risk Prediction of Hypertension and the Monitoring of Its Accompanying Metabolic Risk Factors

Our aim was to study whether radial pulse wave signals can improve the risk prediction of incident hypertension and are associated with its concomitant metabolic risk factors beyond the traditional cardiovascular risk factor Ba-PWV. By enrolling 523 Chinese subjects in this study, linear and stepwise regression analysis was performed to assess the association of radial artery pulse wave signals and Ba-PWV with blood pressure and its related metabolic risk factors such as fasting plasma glucose (FPG), total cholesterol (TC), triglyceride (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and uric acid (UA). The area under the receiver-operating characteristic curve (AUC), net reclassification improvement (NRI), and integrated discrimination improvement (IDI) were calculated by risk assessment plot to compare the discriminative ability among models with and without radial artery pulse wave signals. After adjusting related confounding factors, radial artery pulse wave variable h 3/h 1 was selected as the sensitive influential factor for blood pressure. Moreover, a new model with h 3/h 1 had a higher AUC than the reference model without it (0.86 vs 0.84; P=0.030). And the NRI and IDI for the new model was 50.0% (P=0.017) and 3.16% (P=0.044), respectively. In addition to Ba-PWV, we found that the decrease of t 4, t 5, and h 5 might be associated with higher FPG, TC, LDL-C, and UA and lower HDL-C. This research might provide a valuable additional tool for remote wearable monitoring of radial artery pulse wave signals in hypertension risk evaluation and management.

Quantitative Comparison of the Performance of Piezoresistive, Piezoelectric, Acceleration, and Optical Pulse Wave Sensors

The accurate measurement of the arterial pulse wave is beneficial to clinical health assessment and is important for the effective diagnosis of many types of cardiovascular disease. A variety of sensors have been developed for the non-invasive detection of these waves, but the type of sensor has an impact on the measurement results. Therefore, it is necessary to compare and analyze the signals obtained under a range of conditions using various pulse sensors to aid in making an informed choice of the appropriate type. From the available types we have selected four: a piezoresistive strain gauge sensor (PESG) and a piezoelectric Millar tonometer (the former with the ability to measure contact force), a circular film acceleration sensor, and an optical reflection sensor. Pulse wave signals were recorded from the left radial, carotid, femoral, and digital arteries of 60 subjects using these four sensors. Their performance was evaluated by analyzing their susceptibilities to external factors (contact force, measuring site, and ambient light intensity) and by comparing their stability and reproducibility. Under medium contact force, the peak-to-peak amplitude of the signals was higher than that at high and low force levels and the variability of signal waveform was small. The optical sensor was susceptible to ambient light. Analysis of the intra-class correlation coefficients (ICCs) of the pulse wave parameters showed that the tonometer and accelerometer had good stability (ICC > 0.80), and the PESG and optical sensor had moderate stability (0.46 < ICC < 0.86). Intra-observer analysis showed that the tonometer and accelerometer had good reproducibility (ICC > 0.75) and the PESG and optical sensor had moderate reproducibility (0.42 < ICC < 0.91). Inter-observer analysis demonstrated that the accelerometer had good reproducibility (ICC > 0.85) and the three other sensors had moderate reproducibility (0.52 < ICC < 0.96). We conclude that the type of sensor and measurement site affect pulse wave characteristics and the careful selection of appropriate sensor and measurement site are required according to the research and clinical need. Moreover, the influence of external factors such as contact pressure and ambient light should be fully taken into account.

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 (r1¯) and ratio difference (Δr₁) 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.

A 3D Wrist Pulse Signal Acquisition System for Width Information of Pulse Wave

During pulse signal collection, width information of pulse waves is essential for the diagnosis of disease. However, currently used measuring instruments can only detect the amplitude while can't acquire the width information. This paper proposed a novel wrist pulse signal acquisition system, which could realize simultaneous measurements of the width and amplitude of dynamic pulse waves under different static forces. A tailor-packaged micro-electro-mechanical system (MEMS) sensor array was employed to collect pulse signals, a conditioning circuit was designed to process the signals, and a customized algorithm was developed to compute the width. Experiments were carried out to validate the accuracy of the sensor array and system effectiveness. The results showed the system could acquire not only the amplitude of pulse wave but also the width of it. The system provided more information about pulse waves, which could help doctors make the diagnosis.

A Wearable Combined Wrist Pulse Measurement System Using Airbags for Pressurization

The pulse measurement instrument is based on traditional Chinese medicine (TCM) and is used to collect the pulse of patients to assist in diagnosis and treatment. In the existing pulse measurement system, desktop devices have large volumes, complex pressure adjusting operations, and unstable pressurization. Wearable devices tend to have no pressurization function or the function to pressurize three channels separately, which are not consistent with the diagnostic method in TCM. This study constructs a wearable pulse measurement system using airbags for pressurization. This system uses guide plates, guide grooves, and positioning screws to adjust the relative position of the wristband and locate Cun, Guan and Chi regions. The pulse signal measured by the sensor is collected and sent to a computer by microcontroller unit. In experiments, this system successfully obtains the best pulse-taking pressure, its pulse waveform under continuous decompression, and the pulse waveform of three regions under light, medium, and heavy pressure. Compared with the existing technology, the system has the advantages of supporting single-region and three-region pulse acquisition, independent pressure adjustment, and position adjustment. It meets the needs of home, medical, and experimental research, and it is convenient and comfortable to wear and easy to carry.

The Association of Radial Artery Pulse Wave Variables with the Pulse Wave Velocity and Echocardiographic Parameters in Hypertension

This study aims at exploring the cardiovascular pathophysiological mechanism of TCM (traditional Chinese medicine) pulse by detecting the correlation between radial artery pulse wave variables and pulse wave velocity/echocardiographic parameters. Two hundred Chinese subjects were enrolled in this study, which were grouped into health control group, hypertension group, and hypertensive heart disease group. Physical data obtained in this study contained TCM pulse images at "Guan" position of the left hand, pulse wave velocity, and echocardiographic parameters. Linear and stepwise regression analysis was performed to assess the association of radial artery pulse wave variables with pulse wave velocity and echocardiographic parameters in the total population and in each different group. After adjusting for related confounding factors, decrease of t1, t5 and increase of h1, h3/h1 were statistically associated with arterial stiffness in the total population (P<0.05). Moreover, the correlation study in each group showed that the decrease of both t3 and h5 was also related to arterial stiffness (P<0.05). In terms of echocardiographic parameters, the height of dicrotic wave indicated by h5 was the most relevant pulse wave variable. For the health control, h5 was negatively associated with interventricular septal thickness (VST) and left ventricular posterior wall thickness (PWT) (P<0.05), while for the hypertension population and those with target-organ damage to heart, increase of h5 might be associated with decrease of ejection fraction (EF) and increase of all the remaining echocardiographic parameters especially for left ventricular end-systolic diameter (LVDs) and Left ventricular end-diastolic diameter (LVDd) (P<0.05). In conclusion, we found radial artery pulse wave variables were in association with the arterial stiffness and echocardiographic changes in hypertension, which would provide an experimental basis for cardiovascular pathophysiological mechanism of radial artery pulse wave variables.

Analysis of Pulse Signals Based on Array Pulse Volume

OBJECTIVE

To collect and analyze multi-dimensional pulse diagram features with the array sensor of a pressure profile system (PPS) and study the characteristic parameters of the new multi-dimensional pulse diagram by pulse diagram analysis technology.

METHODS

The pulse signals at the Guan position of left wrist were acquired from 105 volunteers at the Shanghai University of Traditional Chinese Medicine. We obtained the pulse data using an array sensor with 3×4 channels. Three dimensional pulse diagrams were constructed for the validated pulse data, and the array pulse volume (APV) parameter was computed by a linear interpolation algorithm. The APV differences among normal pulse (NP), wiry pulse (WP) and slippery pulse (SP) were analyzed using one-way analysis of variance. The coefficients of variation (CV) were calculated for WP, SP and NP.

RESULTS

The APV difference between WP and NP in the 105 volunteers was statistically significant (6.26±0.28 vs. 6.04±0.36, P=0.048), as well as the difference between WP and SP (6.26±0.28 vs. 6.07±0.46, P=0.049). However, no statistically significant difference was found between NP and SP (P=0.75). WP showed a similar CV (4.47%) to those of NP (5.96%) and SP (7.58%).

CONCLUSION

The new parameter APV could differentiate between NP or SP and WP. Accordingly, APV could be considered an useful parameter for the analysis of array pulse diagrams in Chinese medicine.

Detection of multipoint pulse waves and dynamic 3D pulse shape of the radial artery based on binocular vision theory

BACKGROUND AND OBJECTIVE

Pulse signals contain a wealth of human physiological and pathological information. How to get full pulse information is especially challenging, and most of the traditional pulse sensors can only get the pulse wave of a single point. This study is aimed at developing a binocular pulse detection system and method to obtain multipoint pulse waves and dynamic three-dimensional pulse shape of the radial artery.

METHODS

The proposed pulse detection approach is image-based and implemented by two steps. First, a new binocular pulse detection system is developed based on the principle of pulse feeling used in traditional Chinese medicine. Second, pulse detection is achieved based on theories and methods of binocular vision and digital image processing. In detail, the sequences of pulse images collected by the designed system as experimental data are sequentially processed by median filtering, block binarization and inversion, area filtering, centroids extraction of connected regions, to extract the pattern centroids as feature points. Then stereo matching is realized by a proposed algorithm based on Gong-shape scan detection. After multipoint spatial coordinate calculation, dynamic three-dimensional reconstruction of the thin film shape is completed by linear interpolation. And then the three-dimensional pulse shape is achieved by finding an appropriate reference time. Meanwhile, extraction of multipoint pulse waves of the radial artery is accomplished by using a suitable reference origin. The proposed method is analyzed from three aspects, which are pulse amplitude, pulse rate and pulse shape, and compared with other detection methods.

RESULTS

Analysis of the results shows that the values of pulse amplitude and pulse rate are consistent with the characteristics of pulse wave of the radial artery, and pulse shape can correctly present the shape of pulse in space and its change trend in time. The comparison results with the other two previously proposed methods further verify the correctness of the presented method.

CONCLUSIONS

The designed binocular pulse detection system and proposed algorithm can effectively detect pulse information. This tactile visualization-based pulse detection method has important scientific significance and broad application prospects and will promote further development of objective pulse diagnosis.

A non-contact pulse automatic positioning measurement system for traditional Chinese medicine

This study is to construct a non-contact pulse automatic positioning measurement system for Traditional Chinese Medicine (TCM) using optical triangulation measurements. The system consists of a linear laser, a CMOS image sensor and image analysis software. The linear laser is projected on the pulse beat location on the wrists; the CMOS image sensor records the process and the software analyzes the images. The program mainly uses the optical centroid and fast Fourier transform (FFT) principles to calculate centroid changes (pulse amplitude changes) from the images taken by the CMOS image sensor. It returns the positions of cun, guan and chi pulses automatically in terms of the amplitudes and the signals are then transformed from the time domain (time-amplitude) into the frequency domain (frequency-amplitude) via FFT to obtain the waveforms and frequencies of the cun, guan and chi pulses. It successfully extracts the data from the TCM pulse reading and can be a medical aid system for TCM. Combining the advantages of optical measurement and computer automation, this system provides a non-contact, easy to operate, fast in detection and low-cost equipment design.