Traditional Chinese Medicine Pulse Diagnosis on a Smartphone Using Skin Impedance at Acupoints: A Feasibility Study

AI: Bridging Ancient Wisdom and Modern Innovation in Traditional Chinese Medicine

The pursuit of groundbreaking health care innovations has led to the convergence of artificial intelligence (AI) and traditional Chinese medicine (TCM), thus marking a new frontier that demonstrates the promise of combining the advantages of ancient healing practices with cutting-edge advancements in modern technology. TCM, which is a holistic medical system with >2000 years of empirical support, uses unique diagnostic methods such as inspection, auscultation and olfaction, inquiry, and palpation. AI is the simulation of human intelligence processes by machines, especially via computer systems. TCM is experience oriented, holistic, and subjective, and its combination with AI has beneficial effects, which presumably arises from the perspectives of diagnostic accuracy, treatment efficacy, and prognostic veracity. The role of AI in TCM is highlighted by its use in diagnostics, with machine learning enhancing the precision of treatment through complex pattern recognition. This is exemplified by the greater accuracy of TCM syndrome differentiation via tongue images that are analyzed by AI. However, integrating AI into TCM also presents multifaceted challenges, such as data quality and ethical issues; thus, a unified strategy, such as the use of standardized data sets, is required to improve AI understanding and application of TCM principles. The evolution of TCM through the integration of AI is a key factor for elucidating new horizons in health care. As research continues to evolve, it is imperative that technologists and TCM practitioners collaborate to drive innovative solutions that push the boundaries of medical science and honor the profound legacy of TCM. We can chart a future course wherein AI-augmented TCM practices contribute to more systematic, effective, and accessible health care systems for all individuals.

Treatment of Hypothyroidism and Stress Using Neuro-Emotional Technique (NET): A Case Study

Hypothyroidism is generally considered an autoimmune condition, and typical medical management involves taking levothyroxine (synthetic thyroid hormone) for life. This case report details the results of a mind-body intervention (MBI) called the Neuro-Emotional Technique (NET) used to treat a 28-year-old Caucasian female presenting with symptoms and bloodwork markers associated with two years of hypothyroidism and a long history of stress. The patient's medical doctor provided a diagnosis of hypothyroidism after blood tests showed that thyroid-stimulating hormone (TSH) levels were high at 6.87 mIU/L (where the acceptable range is 0.40-3.50 mIU/L) and free T4 (FT4) levels were low at 8.6 pmol/L (where the acceptable range is 9.0-19.0 pmol/L). Psychometric tests were completed at baseline and after 12 weeks of treatment to evaluate changes in mental health and emotional well-being. The Adverse Childhood Experiences Questionnaire (ACE-Q) revealed a high degree of childhood trauma that may have predisposed to the underlying autoimmune thyroid dysfunction. At the conclusion of the treatment period, serum thyroid-stimulating hormone (TSH) and free T4 were within normal ranges and psychometric indicators normalized. We hypothesize that these changes may be due to the stress-reducing mechanism of NET and outline possible mechanisms via the Psycho-Immune-Neuroendocrine (PINE) network. The PINE network model asserts that chronic stress acts as a potential driver of pathophysiology that can lead to one or more medical and mental health conditions. While further studies with larger sample sizes are required to establish whether these results could be extrapolated to a wider population, the results of this case suggest that it may be pertinent to consider co-management of subclinical hypothyroidism with a relatively quick and cost-effective MBI such as NET.

The Effect of Lifting-and-Thrusting Laser Acupuncture on Electrodermal Activity of Acupoints, Pulse Characteristics, and Brainwave

Acupuncture has been shown as an effective traditional Chinese medicine treatment method, especially for pain relief. Recently, laser acupuncture is becoming increasingly popular, thanks to its noninvasive and painless nature and effectiveness in treating diseases, proven by many studies (for example, some previous studies showed that low-power laser stimulation is able to increase the power of alpha rhythms and theta waves). In our prior work, we developed a novel laser acupuncture model that emulates lifting-and-thrusting operation commonly used in traditional needle acupuncture and showed its benefit in improving cardiac output and peripheral circulation. By extending our previous studies, in this work, we perform extensive experiments to understand the effect of such a system on electrodermal activity (EDA) of acupoints, pulse characteristics, and brainwave, to further verify its efficacy. In particular, we found that laser stimulation could cause significant changes in EDA of acupoints, pulse amplitude, pulse-rate-variability (PRV), and acupoint conductance, as a function of laser power and stimulation time. In addition, laser acupuncture with the lifting-and-thrusting operation has more significant effect on increasing the power of alpha and theta frequency bands as compared to laser acupuncture without the lifting-and-thrusting operation. Finally, given sufficient stimulation time (e.g., > 20 min), the performance of a low-powered laser acupuncture with the lifting-and-thrusting operation could be comparable to that of traditional needle acupuncture.

Reflex Auriculo-Cardiac (RAC) Induced by Auricular Laser and Needle Acupuncture: New Case Results Using a Smartphone

The reflex auriculo-cardiac (RAC), dynamic pulse reaction (Nogier reflex), or vascular autonomic signal was proposed by Nogier. It refers to the pulse changes that can occur in the radial artery immediately after auricular acupuncture is performed. RAC is helpful for the clinical practice of auricular acupuncture, but there is a lack of objective verification methods. Photoplethysmography (PPG) has been used to objectively calculate radial artery blood flow. This study used PPG via a smartphone to measure RAC induced by auricular acupuncture. Thirty subjects without major diseases were recruited to receive traditional needle and laser acupuncture. The Shen Men ear point and control points were stimulated for 20 s. PPG was continuously measured during the acupuncture. The PPG data were tested for differences with a paired t-test. The results showed that there were no statistical differences in the frequency and amplitude of PPG obtained before and after acupuncture, either with a traditional needle or laser acupuncture. However, interestingly, it was found that one patient with insomnia, one patient with viral respiratory symptoms, and two menstruating females exhibited changes in PPG within five seconds of needle placement. We hypothesized that RAC might be induced by auricular acupuncture and could be quantified by PPG, even among subjects suffering from mild diseases; however, auricular acupuncture might not induce a measurable RAC in totally healthy subjects.

Chinese Medicine Phenomics (Chinmedphenomics): Personalized, Precise and Promising

The systematicness of phenomics and Traditional Chinese Medicine (TCM) enable these two disciplines to interlink with each other. This article discussed the similarity in theory and application between TCM and phenomics and illustrates their respective advantages in diagnosis and treatment of diseases, forming a new discipline eventually. Chinese medicine phenomics (Chinmedphenomics) is built on classic TCM, combined with phenomics technology, and the development of which needs the mega cohort with TCM syndrome and the characteristics of precision medicine as well as multi-disciplinary cooperation, which is personalized, precise and promising, providing unique scientific insights into understanding human health.

An Initial Study on Automated Acupoint Positioning for Laser Acupuncture

Acupuncture plays an important role in traditional Chinese medicine (TCM) and is one kind of an inexpensive and effective treatment. However, some people might be reluctant to receive acupuncture treatment due to fear of pain. Laser acupuncture, thanks to its painless and infection-free advantages, has recently become an alternative choice to traditional acupuncture. The accuracy of acupuncture point positioning has a decisive influence on the quality of laser acupuncture. In this study, built on top of our prior work, we proposed a low-cost automated acupoint positioning system for laser acupuncture. By integrating several machine learning algorithms and computer vision techniques, we design and implement a robot-assisted laser acupuncture system on top of a smartphone. Our contributions include the following: (a) development of an effective acupoint estimation algorithm with a localization error less than 5 mm; (b) implementation of a smartphone-controlled automated laser acupuncture system with lift-thrust function, as a point-of-care device, that can be used by patients to relieve their symptoms at home.

Laser Acupuncture and Dynamic Pulse Reaction Quantified by Smartphone:Two Experimental Examples

The dynamic pulse reaction (Nogier reflex), Reflex-Auriculo-Cardiac (RAC), or vascular autonomic signal is a physiologic phenomenon that is not fully accepted and widely understood in contemporary medical practice. In order to provide appropriate scientific evidence for better understanding, qualitative and-above all-quantitative research in this area is necessary. In this short report, 2 recordings of dynamic pulse reactions based on an analysis performed on a modified smartphone are demonstrated during laser acupuncture experiments using stimulation at ear acupuncture points.

Forschung im Bereich der Laserakupunktur und Lasermedizin

Dieses innovative Projekt im Rahmen einer erfolgreichen chinesisch-österreichischen Kooperation zur Hightech-Akupunktur zwischen der Pekinger Universität für Chinesische Medizin und der Medizinischen Universität Graz befasst sich mit der Förderung eines neuen Forschungsfeldes mit den Bezeichnungen Laserakupunktur und Lasermedizin. Laserakupunktur ist definiert als „Photonische Stimulation von Akupunkturpunkten und Bereichen, um therapeutische Wirkungen zu initiieren, die denen der Nadelakupunktur und verwandten Therapien ähnlich sind, zusammen mit den Vorteilen der PhotoBio-Modulation (PBM)“. Die Praxis der Laserakupunktur scheint in China noch in den Kinderschuhen zu stecken. Daher wird gemeinsam mit dem österreichischen Projektpartner in China, dem Dekan der Pekinger Universität für Chinesische Medizin, eine qualitativ hochwertige Einführung in die Thematik in Peking durchgeführt. Dazu ist bereits vor kurzem der erste lehrbuchspezifische Bericht über Laserakupunktur und innovative Lasermedizin in chinesischer Sprache erschienen. Im Rahmen von Meinungsführer- und Studentendiskussionen und Vorträgen soll das wichtige neue Forschungsfeld evidenzbasiert wissenschaftlich aufgrund der Pandemie „online“ beworben werden. Dies bietet die Chance, bestehende Kooperationen zu intensivieren und gegebenenfalls nach Zeiten der COVID-19-Pandemie neue gemeinsame Forschungsaktivitäten zu starten.

Artificial Intelligence Based Body Sensor Network Framework-Narrative Review: Proposing an End-to-End Framework using Wearable Sensors, Real-Time Location Systems and Artificial Intelligence/Machine Learning Algorithms for Data Collection, Data Mining and Knowledge Discovery in Sports and Healthcare

With the rising amount of data in the sports and health sectors, a plethora of applications using big data mining have become possible. Multiple frameworks have been proposed to mine, store, preprocess, and analyze physiological vitals data using artificial intelligence and machine learning algorithms. Comparatively, less research has been done to collect potentially high volume, high-quality 'big data' in an organized, time-synchronized, and holistic manner to solve similar problems in multiple fields. Although a large number of data collection devices exist in the form of sensors. They are either highly specialized, univariate and fragmented in nature or exist in a lab setting. The current study aims to propose artificial intelligence-based body sensor network framework (AIBSNF), a framework for strategic use of body sensor networks (BSN), which combines with real-time location system (RTLS) and wearable biosensors to collect multivariate, low noise, and high-fidelity data. This facilitates gathering of time-synchronized location and physiological vitals data, which allows artificial intelligence and machine learning (AI/ML)-based time series analysis. The study gives a brief overview of wearable sensor technology, RTLS, and provides use cases of AI/ML algorithms in the field of sensor fusion. The study also elaborates sample scenarios using a specific sensor network consisting of pressure sensors (insoles), accelerometers, gyroscopes, ECG, EMG, and RTLS position detectors for particular applications in the field of health care and sports. The AIBSNF may provide a solid blueprint for conducting research and development, forming a smooth end-to-end pipeline from data collection using BSN, RTLS and final stage analytics based on AI/ML algorithms.

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.