Reliability of Manual Pulse Diagnosis Methods in Traditional East Asian Medicine: A Systematic Narrative Literature Review

Wearable multichannel-active pressurized pulse sensing platform

With the modernization of traditional Chinese medicine (TCM), creating devices to digitalize aspects of pulse diagnosis has proved to be challenging. The currently available pulse detection devices usually rely on external pressure devices, which are either bulky or poorly integrated, hindering their practical application. In this work, we propose an innovative wearable active pressure three-channel pulse monitoring device based on TCM pulse diagnosis methods. It combines a flexible pressure sensor array, flexible airbag array, active pressure control unit, advanced machine learning approach, and a companion mobile application for human-computer interaction. Due to the high sensitivity (460.1 kPa-1), high linearity (R 2 > 0.999) and flexibility of the flexible pressure sensors, the device can accurately simulate finger pressure to collect pulse waves (Cun, Guan, and Chi) at different external pressures on the wrist. In addition, by measuring the change in pulse wave amplitude at different pressures, an individual's blood pressure status can be successfully predicted. This enables truly wearable, actively pressurized, continuous wireless dynamic monitoring of wrist pulse health. The innovative and integrated design of this pulse monitoring platform could provide a new paradigm for digitizing aspects of TCM and other smart healthcare systems.

Towards Generating Realistic Wrist Pulse Signals Using Enhanced One Dimensional Wasserstein GAN

For the past several years, there has been an increasing focus on deep learning methods applied into computational pulse diagnosis. However, one factor restraining its development lies in the small wrist pulse dataset, due to privacy risks or lengthy experiments cost. In this study, for the first time, we address the challenging by presenting a novel one-dimension generative adversarial networks (GAN) for generating wrist pulse signals, which manages to learn a mapping strategy from a random noise space to the original wrist pulse data distribution automatically. Concretely, Wasserstein GAN with gradient penalty (WGAN-GP) is employed to alleviate the mode collapse problem of vanilla GANs, which could be able to further enhance the performance of the generated pulse data. We compared our proposed model performance with several typical GAN models, including vanilla GAN, deep convolutional GAN (DCGAN) and Wasserstein GAN (WGAN). To verify the feasibility of the proposed algorithm, we trained our model with a dataset of real recorded wrist pulse signals. In conducted experiments, qualitative visual inspection and several quantitative metrics, such as maximum mean deviation (MMD), sliced Wasserstein distance (SWD) and percent root mean square difference (PRD), are examined to measure performance comprehensively. Overall, WGAN-GP achieves the best performance and quantitative results show that the above three metrics can be as low as 0.2325, 0.0112 and 5.8748, respectively. The positive results support that generating wrist pulse data from a small ground truth is possible. Consequently, our proposed WGAN-GP model offers a potential innovative solution to address data scarcity challenge for researchers working with computational pulse diagnosis, which are expected to improve the performance of pulse diagnosis algorithms in the future.

Wrist pulse signal acquisition and analysis for disease diagnosis: A review

Pulse diagnosis (PD) plays an indispensable role in healthcare in China, India, Korea, and other Orient countries. It requires considerable training and experience to master. The results of pulse diagnosis rely heavily on the practitioner's subjective analysis, which means that the results from different physicians may be inconsistent. To overcome these drawbacks, computational pulse diagnosis (CPD) is used with advanced sensing techniques and analytical methods. Focusing on the main processes of CPD, this paper provides a systematic review of the latest advances in pulse signal acquisition, signal preprocessing, feature extraction, and signal recognition. The most relevant principles and applications are presented along with current progress. Extensive comparisons and analyses are conducted to evaluate the merits of different methods employed in CPD. While much progress has been made, a lack of datasets and benchmarks has limited the development of CPD. To address this gap and facilitate further research, we present a benchmark to evaluate different methods. We conclude with observations of the status and prospects of CPD.

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.

Inter-Rater Agreement of Biofield Tuning: Testing a Novel Health Assessment Procedure

Objectives: Practitioners of Biofield Tuning assess health status of their clients by detecting off-the-body biofield perturbations using tuning fork (TF) vibrations. This study tested inter-rater agreement (IRA) on location of these perturbations. Design: Three Biofield Tuning practitioners, in randomized order, identified locations of the 4-5 "strongest" perturbations along each of 4 sites for the same series of 10 research subjects. Setting/Location: An Integrative Health and Medicine Center in La Jolla, CA. Subjects: Adult volunteers with no serious current illness and no prior experience of a Biofield Tuning session. Interventions: Practitioners used an activated 174 Hz unweighted TF to "comb" the same four sites per subject, located on the left and right sides of the base of the spine and the heart. Outcome Measures: Practitioners identified and vocalized the distance from the body of perturbations along each site. Distances were recorded by a research assistant in the clinic room. No health information related to perturbation sites was discussed with the subjects. Results: Practitioners reported 6.3 ± 0.6 (mean ± standard deviation) perturbations per combed site per subject, with no significant difference among the raters. The overall level of IRA was low based initially on a first-pass, nonstatistical, analysis of results, with "agreement" defined within a tolerance of ±2 inches. In this approach agreement was 33%. More rigorous statistical analysis, including a statistical test using a Monte Carlo approach, strongly supported the conclusion of poor IRA. Conclusions: IRA was low despite attempts to balance the real-world practice of Biofield Tuning with the constraints of research. For example, while IRA necessitates multiple assessments of the same subject, no information exists as to whether an initial assessment may affect subsequent assessments. Our study exemplifies the challenges faced when attempting to fit interventions with incompletely understood procedures and mechanisms into conventional research designs.

Experimental Studies of Inter-Rater Agreement in Traditional Chinese Medicine: A Systematic Review

Objectives: It has been recommended that clinical trials of Traditional Chinese Medicine (TCM) would be more ecologically valid if its characteristic mode of diagnostic reasoning were integrated into their design. In that context, however, it is also widely held that demonstrating a high level of agreement on initial TCM diagnoses is necessary for the replicability that the biomedical paradigm requires for the conclusions from such trials. Our aim was to review, summarize, and critique quantitative experimental studies of inter-rater agreement in TCM, and some of their underlying assumptions. Design: Systematic electronic searches were conducted for articles that reported a quantitative measure of inter-rater agreement across a number of rating choices based on examinations of human subjects in person by TCM practitioners, and published in English language peer-reviewed journals. Publications in languages other than English were not included, nor those appearing in other than peer-reviewed journals. Predefined categories of information were extracted from full texts by two investigators working independently. Each article was scored for methodological quality. Outcome measures: Design features across all studies and levels of inter-rater agreement across studies that reported the same type of outcome statistic were compared. Results: Twenty-one articles met inclusion criteria. Fourteen assessed inter-rater agreement on TCM diagnoses, two on diagnostic signs found upon traditional TCM examination, and five on novel rating schemes derived from TCM theory and practice. Raters were students of TCM colleges or graduates of TCM training programs with 3 or more years experience and licensure. Type of outcome statistic varied. Mean rates of pairwise agreement averaged 57% (median 65, range 19-96) across the 9 studies reporting them. Mean Cohen's kappa averaged 0.34 (median 0.34, range 0.07-0.59) across the seven studies reporting them. Meta-analysis was not possible due to variations in study design and outcome statistics. High risks of bias and confounding, and deficits in statistical reporting were common. Conclusions: With a few exceptions, the levels of agreement were low to moderate. Most studies had significant deficits of both methodology and reporting. Results overall suggest a few design features that might contribute to higher levels of agreement. These should be studied further with better experimental controls and more thorough reporting of outcomes. In addition, methods of complex systems analysis should be explored to more adequately model the relationship between clinical outcomes, and the series of diagnoses and treatments that are the norm in actual TCM practice.