Palpation Localization of Radial Artery Based on 3-Dimensional Convolutional Neural Networks

Palpation localization is essential for detecting physiological parameters of the radial artery for pulse diagnosis of Traditional Chinese Medicine (TCM). Detecting signal or applying pressure at the wrong location can seriously affect the measurement of pulse waves and result in misdiagnosis. In this paper, we propose an effective and high accuracy regression model using 3-dimensional convolution neural networks (CNN) processing near-infrared picture sequences to locate radial artery upon radius at the wrist. Comparing with early studies using 2-dimensional models, 3D CNN introduces temporal features with the third dimension to leverage pulsation rhythms. The model had achieved superior performance accuracy as 0.87 within 50 pixels at picture resolution of 2048*1088. Model visualization shows that the additional dimension of the temporal convolution highlights dynamic changes within image sequences. This study presents the great potential of our constructed model to be applied in real wrist palpation location scenarios to bring the key convenience for pulse diagnosis.

A Nature-inspired Hierarchical Branching Structure Pressure Sensor for Medical Wearables

Both ecosystems and biological systems in nature have evolved with unique hierarchical branching networks to maximize the efficiency and range of material transmission and adaptability to their external environment. Here we emulate this hierarchical branching (HB) network using a multilayer superposition approach and apply it in the design of flexible pressure sensors for medical wearables. Based on the HB structure, simulation results demonstrate that the deformation of microstructures is efficiently scheduled. Experiments show that the sensitivity of the HB sensor exhibits almost 34- and 55-fold improvements over the medium-pressure and high-pressure ranges, respectively, compared with that of a pressure sensor with a traditional monolayer structure. Successful monitoring of the diverse stimuli from humans demonstrates the considerable potential of the HB sensor in medical wearables. Additionally, the small and thin nature of the sensor enables it to quantify medical diagnostic processes, such as intelligent traditional Chinese medicine pulse diagnosis.

Integrated Study on Pulse Diagnosis of TCM and Cardiology by Analyzing the Distribution Characteristics of Atherosclerosis Parameters at Six Positions of Cunkou

The authors have requested that this preprint be withdrawn due to erroneous posting.

Study on the Syndrome Characteristics and Classification Model of Non- Small Cell Lung Cancer Based on Tongue and Pulse Data

Background: Lung cancer is a common malignant tumor that affects people's health seriously. Traditional Chinese medicine (TCM) is one of the effective methods for the treatment of advanced lung cancer, accurate TCM syndrome differentiation is essential to treatment. When the symptoms are not obvious, the traditional symptom-based syndrome differentiation cannot be carried out. There is a close relationship between syndrom and index of western medicine, the combination of micro index and macro symptom can assist syndrome differentiation effectively.Methods: Tongue and pulse data of non-small cell lung cancer (NSCLC) patients with Qi deficiency syndrome (n=163), patients with Yin deficiency syndrome (n=174) and healthy controls (n=185) were collected by using intelligent Tongue and Face Diagnosis Analysis-1 instrument and Pulse Diagnosis Analysis-1 instrument, respectively. The characteristics of tongue and pulse data were analyzed, the correlation analysis was also made on tongue and pulse data. And four machine learning methods, namely Random Forest, Logistic Regression, Support Vector Machine and Neural Network, were used to establish the classification models based on symptoms, tongue & pulse data, and symptoms & tongue & pulse data, respectively.Results: Significant difference indexes of tongue diagnosis between Qi deficiency syndrome and Yin deficiency syndrome were TB-a, TB-S, TB-Cr, TC-a, TC-S, TC-Cr, perAll and the tongue coating texture indexes including TC-Con, TC-ASM, TC-MEAN, and TC-ENT. Significant difference indexes of pulse diagnosis were t4 and t5. The classification performance of each model based on different data sets was as follows: model of tongue & pulse data <model of symptom < model of symptom & tongue & pulse data. The Neural Network model had a better classification performance for the symptom & tongue & pulse data, with an area under the ROC curve and accuracy rate were 0.9401 and 0.8806.Conclusions:This study explored the characteristics of tongue and pulse data of NSCLC with Qi deficiency syndrome and Yin deficiency syndrome, and established syndromes classification model. It was feasible to use tongue and pulse data as one of the objective diagnostic indexes in Qi deficiency syndrome and Yin deficiency syndrome of NSCLC.Name of the registry: Chinese Clinical Trial RegistryTrial registration number: ChiCTR1900026008; ChiCTR-IOR-15006502 Date of registration: Jun. 04th, 2015URL of trial registry record: http://www.chictr.org.cn/showprojen.aspx?proj=11119;http://www.chictr.org.cn/edit.aspx?pid=38828&htm=4 (This is a retrospective registration)

Integrated Study on Pulse Diagnosis of TCM and Cardiology by Analyzing the Distribution Characteristics of Atherosclerosis Parameters at Six Positions of Cunkou

The authors have requested that this preprint be removed from Research Square.

The Research of Three Regions Acquisition and Analysis System of Pulse Based on Flexible Sensor

The objectification of pulse diagnosis is very important to the development and inheritance of TCM, the first step is how to collect more abundant and comprehensive pulse information quickly, reduce the threshold of users for using pulse diagnosis equipment. The existing pulse diagnosis equipment has some limitations, such as single acquisition site, complex compression form and serious dependence on professionals for correcting-pulse position selection. Therefore, a three-pulse diagnosis system based on flexible sensor is designed, which uses a new type of flexible sensor as the data acquisition port, combined with upper computer software and lower computer software to achieve goals of intelligent decompression and data acquisition from Cun, Guan, Chi. The equipment not only greatly reduces the difficulty for users to find correct pulse position identification, but also collect non-destructive pulse information, which provides a new acquisition mode for the pulse diagnosis instrument.