Search Results (19)

Background: Insomnia requires long-term self-management, prompting many patients to turn to Traditional Chinese Medicine-based lifestyle (TCM-L) practices for health preservation. However, a consensus-based TCM-L content framework is lacking. This study aims to develop a consensus-based TCM-L content framework using a modified Delphi method. Methods: A modified Delphi study was conducted in two phases. In phase 1, a preliminary content framework was developed based on a systematic review, TCM textbooks, and clinical guidelines, consisting of 10 initial domains and 82 subordinate items. In phase 2, 18 local Chinese medicine practitioners were purposively recruited to evaluate the framework over four iterative rounds. Items were rated on a 5-point Likert scale, with consensus defined as a mean ≥ 4.0, a coefficient of variation < 0.25, and a consensus level of agreement ≥ 80%. Iterative modifications, deletions, and additions were informed by both these numerical thresholds and qualitative expert feedback. Kendall’s W was calculated to assess the coordination of consensus. Results: All 18 experts completed four rounds (100% response rate) with high authority (Cr = 0.864–0.883). The initial 10 domains and 82 subordinate items were refined to six domains and 49 subordinate items. Expert consensus was statistically significant across rounds (p < 0.01), with Kendall’s W demonstrating a high concordance of 0.717 for domain importance in the final round. The prioritized sequence of the six domains in the final TCM-L framework was: (1) Domain 1: introduction to TCM-L, (2) Domain 4: sleep–wake routines, (3) Domain 3: dietary regulation, (4) Domain 2: emotional regulation, and tied at (5) Domain 5: mind–body exercise and Domain 6: acupoint massage. Conclusions: This study established a consensus-based TCM-L content framework for insomnia, providing a culturally relevant foundational structure for future lifestyle interventions, clinical education, and self-management support. Full article

Deep learning for sensor-based medical imaging provides a non-contact and data-driven route for anatomical surface analysis and personalized traditional Chinese medicine (TCM) applications. However, accurate hand-acupoint localization from camera-acquired hand images remains challenging because expert-annotated acupoint datasets are limited and inter-subject anatomical variations are significant. This paper proposes a marker-free hand-acupoint localization method based on deep feature correspondence learning and sparse image registration. The task is formulated as template-to-target correspondence estimation, in which expert-annotated acupoints in a TCM template image are used as query points and mapped to a target hand image acquired by an optical imaging sensor. A Transformer-based architecture is employed to correlate multi-scale image features, and an uncertainty-aware matching formulation is used to estimate both acupoint positions and unreliable matches. Unlike conventional keypoint detection networks, the proposed method exploits TCM template priors and reduces the dependence on dense target-image acupoint annotations. The constructed dataset contains 1400 images from 378 participants. Participant-level partitioning was performed before image-pair generation, yielding a held-out test set of 38 participants (140 images). Palm and dorsal-hand views were evaluated separately against keypoint-detection baselines and COTR. On this participant-independent internal test set, the proposed method achieved AAPE values of 18.42 pixels for palm images and 12.60 pixels for dorsal-hand images, while reducing inference time from 11,000 ms for COTR to 600 ms. These results indicate the feasibility of template-guided image-based hand-acupoint localization with reference to expert annotations. Full article

Chemotherapy-induced nausea and vomiting (CINV) remain difficult to control after discharge despite guideline-based antiemetics. This multicenter exploratory single-arm two-stage trial evaluated patient-controlled, real-time transcutaneous electrical acupoint stimulation (TEAS) at Neiguan (PC6) as an adjunct to standard antiemetic therapy in patients with breast cancer. Forty-eight patients who had experienced CINV and were scheduled at enrollment to receive the same chemotherapy and antiemetic regimens during two consecutive cycles were analyzed. Cycle 1 served as the observation period, and cycle 2 added on-demand wrist-worn TEAS initiated by patients at nausea or vomiting onset during 0–120 h after chemotherapy. Compared with the observation period, TEAS was associated with lower nausea frequency and visual analogue scale scores on days 1–5 and higher nausea response rates on days 1–4. Vomiting frequency and severity were lower on days 1–3, but between-period differences were not significant on days 4–5. SF-36 scores increased and SAS/SDS scores decreased on day 5. Two transient local numbness events occurred, with no serious TEAS-related adverse events. These findings suggest that patient-controlled TEAS is feasible and warrants confirmation in randomized sham-controlled trials. Full article

Background/Objectives: Modern acupuncture research commonly operationalizes acupoints as standardized sites for needling or electrical stimulation. Although this convention has improved reproducibility, it may obscure how classical acupoint and meridian systems have historically organized relationships among intervention sites, sensory phenomena, symptom patterns, and therapeutic responses. This article proposes an operational framework for examining selected acupoint regions as candidate neuromodulation interfaces. It reframes acupoint and meridian systems as relational body maps and operationalizes this perspective through a multidimensional stimulation–engagement–response model that distinguishes intervention features, target engagement, and downstream functional outcomes while accounting for individual context. Methods: The framework was developed to organize existing evidence, identify unresolved causal links, and generate prospective experimental tests, rather than to establish neural or physiological mechanisms that have already been demonstrated. The Baliao region, comprising bilateral BL31–BL34 over the posterior sacral foramina, was selected as the primary case because classical localization and pelvic symptom associations can be examined alongside sacral anatomy and neurophysiology within a single region. Relevant clinical and preclinical findings were evaluated in relation to potential neural targets, physiological engagement, functional outcomes, and alternative explanations. Results: Clinical and preclinical evidence suggests possible engagement of sacral afferent, spinal, autonomic, and pelvic-floor regulatory circuits. However, the evidence remains indirect, heterogeneous, and insufficient to establish equivalence with implantable sacral neuromodulation, a unique BL31–BL34 mechanism, or absolute point specificity. The framework clarifies what current evidence supports, identifies unresolved mechanistic links and alternative explanations, and proposes prospective strategies for testing target engagement and physiological relevance. Conclusions: This approach provides a staged research agenda for moving from descriptive associations toward prospective tests of parameter-dependent target engagement, physiological relevance, and, ultimately, biomarker-guided neuromodulation. Full article

Infrared thermal imaging offers objective physiological insights for Traditional Chinese Medicine (TCM), yet automated acupoint localization struggles with low texture and extreme pose variations. To address this, we constructed a multi-pose thermal facial dataset using digitized bone-proportional measurements and TCM anatomical rules. We propose T2FAL, a two-stage cascaded regression framework explicitly decoupling macroscopic face detection from fine-grained acupoint localization. Stage 1 utilizes an improved YOLOv12m-based Thermal-Aware Face Detector—integrating ICAN_C2f, MixNeck, and TAF-IoU—to mitigate domain shifts and thermal noise. Stage 2 deploys pose-specific regressors incorporating Gated Feature-Conditioned Cascade Refinement (FCCR) and a Selective GeoDeriv module, mathematically translating anatomical rules into geometric constraints. Under the stated experimental protocol, Stage 1 processed images at 87.3 frames per second on an NVIDIA RTX 4090. For Stage 2, the final frontal- and profile-view configurations achieved mAP@50–95 values of 73.19% and 86.92%, with mean pixel errors of 1.986 and 3.109 pixels, respectively. These results support the feasibility of automated reference-coordinate localization on the datasets used. However, given the partial reliance of the annotations on image registration and geometric rules, the use of the cross-domain set for model selection, and the lack of clinical or diagnostic evaluation, further validation using independently generated expert annotations, a strictly held-out external test set, and clinically labeled data is required before clinical or diagnostic use. Full article

Traditional acupoint localization methods rely heavily on manual operation, resulting in high subjectivity and limited accuracy. To improve the precision and stability of acupoint detection, this study integrates machine vision technology with in situ projection to achieve automated recognition and real-time visualization of human acupoints. First, an automatic calibration method based on image processing is proposed for back acupoints. Spinal features are extracted from the blue channel, enhanced using adaptive histogram equalization, and processed through region of interest extraction, minimum-threshold binarization, and morphological operations. Key spinal curve points are then fitted using Bézier functions. Canny edge detection is used to extract the human silhouette, locate the acromion, and derive the pixel scale of the “cun” measurement, enabling coordinate computation for 141 back acupoints. In the deep learning component, an improved YOLOv8-Pose model is developed for acupoint localization. Unlike existing methods that use local attention or the original Object Keypoint Similarity (OKS) loss, we introduce two innovations: a non-local attention module for global dependency modeling, and a novel Efficient Object Keypoint Similarity (EOKS) loss function that incorporates geometric constraints—namely, width, height, and center distance—in addition to Euclidean distance. A non-local attention mechanism is incorporated into the backbone to enhance global feature extraction, and the EOKS loss function is designed to improve spatiogeometric regression accuracy. An inference mechanism is further introduced to derive the remaining acupoints from 49 detected keypoints; experiments demonstrate that the improved model achieves 95.0% detection accuracy, outperforming the baseline by 2.62%, with an inference time of 14.5 ms. Finally, an in situ projection platform is constructed, combining camera calibration, four-point proportional scaling, and an OpenCV 4.5.4-based interactive interface. The system supports real-time translation, rotation, and scaling, enabling accurate projection of detected acupoints onto the human body. Full article

We developed an AI-based system for facial acupoint recognition and healthcare support, integrating MediaPipe facial and hand tracking technologies to address the problems of inaccurate and non-standardized acupoint identification in traditional Chinese medicine (TCM). By leveraging facial landmark detection and fingertip tracking, the system enables accurate localization of facial acupoints to ensure precise stimulation. The system contributes to the standardization of acupoint recognition, intelligent health consultation, and the digital transformation of TCM practices. Further enhancements are necessary by expanding acupoint recognition to other body parts (e.g., ears, hands, feet, and back) and integrating with wearable devices to further promote personalized and precise TCM healthcare. Full article

Background: Precise localization of acupuncture points (acupoints) is crucial for the clinical success of Traditional Korean Medicine (TKM). Traditional methods that rely on visual inspection and palpation are subjective and prone to inter- and intra-observer differences, making standardization challenging. The progress of data-driven localization techniques is also limited by the scarcity of annotated datasets and inconsistent labeling quality. Objective: This study presents MetaAcuPoint, a synthetic dataset created to overcome these limitations by providing high-fidelity, anatomically consistent hand images for acupoint localization. Methods: MetaAcuPoint was generated using MetaHuman avatars within Unreal Engine, resulting in 900 RGB hand images. Anatomically aligned, bone-attached sockets were implemented for five diagnostically relevant hand acupoints, ensuring millimeter-level precision and spatial consistency across various hand poses. Dataset validity was assessed by training a high-resolution network (HRNet-W48) within the MMPose framework and testing its performance on real-world forearm images. Results: The synthetic-trained model achieved a mean distance error (MDE) of 5.67 ± 3.13 pixels, closely aligning with the real-data baseline at 4.81 ± 2.85 pixels. Adding synthetic samples to real data further enhanced performance (MDE: 4.95 pixels). In contrast, manually annotated synthetic images yielded poorer results (MDE: 12.76 pixels), emphasizing the advantages of automated anatomical annotation. Generalization tests across four external datasets confirmed that the synthetic data-trained model outperformed the real-data-trained model, maintaining higher accuracy (MDE: 5.84–6.45 mm vs. 10.63–15.80 mm). Conclusions: MetaAcuPoint demonstrates the first example of synthetic-to-real generalization for hand acupoint localization. By combining photorealistic rendering with anatomically grounded annotation, the dataset offers a reliable resource to promote standardized, data-driven approaches in acupuncture research and practice. Full article

Reliable acupoint localization is essential for developing artificial intelligence (AI) and extended reality (XR) tools in traditional Korean medicine; however, conventional annotation of 2D images often suffers from inter- and intra-annotator variability. This study presents a low-cost dual-camera imaging system that fuses infrared (IR) and RGB views on a Raspberry Pi 5 platform, incorporating an IR ink pen in conjunction with a 780 nm emitter array to standardize point visibility. Among the tested marking materials, the IR ink showed the highest contrast and visibility under IR illumination, making it the most suitable for acupoint detection. Five feature detectors (SIFT, ORB, KAZE, AKAZE, and BRISK) were evaluated with two matchers (FLANN and BF) to construct representative homography pipelines. Comparative evaluations across multiple camera-to-surface distances revealed that KAZE + FLANN achieved the lowest mean 2D error (1.17 ± 0.70 px) and the lowest mean aspect-aware error (0.08 ± 0.05%) while remaining computationally feasible on the Raspberry Pi 5. In hand-image experiments across multiple postures, the dual-camera registration maintained a mean 2D error below ~3 px and a mean aspect-aware error below ~0.25%, confirming stable and reproducible performance. The proposed framework provides a practical foundation for generating high-quality acupoint datasets, supporting future AI-based localization, XR integration, and automated acupuncture-education systems. Full article

Background and Objectives: Nausea and vomiting (NV) are common and distressing adverse effects among cancer patients undergoing treatment. Despite the widespread use of pharmacological antiemetics, these medications are often insufficient for controlling nausea and may cause medication interactions and side effects. Acupuncture has been proposed as a complementary therapy; however, the comprehensive analysis of its effects on NV across all emetogenic cancer treatments remains limited. This systematic review and meta-analysis aimed to evaluate the effectiveness and safety of acupuncture in managing NV in cancer patients undergoing chemotherapy, radiotherapy, or surgery. Materials and Methods: We conducted a comprehensive search across three electronic databases and two clinical registry platforms from inception to December 2024. Randomized controlled trials (RCTs) evaluating acupuncture for NV in cancer patients were included. Risk ratios (RRs) and 95% confidence intervals (CIs) were calculated using a random-effects model. Safety outcomes were assessed based on the Common Terminology Criteria for Adverse Events (CTCAE). Results: Seventeen RCTs met the inclusion criteria, with twelve studies included in the meta-analysis. Acupuncture did not demonstrate significant effects on acute nausea (RR: 0.98; 95% CI: 0.84–1.15; p = 0.80) or acute vomiting (RR: 0.93; 95% CI: 0.65–1.32; p = 0.67). However, it significantly reduced delayed vomiting (RR: 0.76; 95% CI: 0.61–0.95; p = 0.02). Subgroup analysis demonstrated significant effects when acupuncture was administered for at least five days (RR: 0.56; 95% CI: 0.39–0.81; p = 0.002). The most frequently used acupoints were PC6, ST36, CV12, LI4, LR3, and ST25. No serious adverse events related to acupuncture treatments were reported, with only minor AEs such as localized bleeding and mild bruising observed. Conclusions: Acupuncture represents a safe and effective complementary therapy for managing delayed vomiting in cancer patients receiving emetogenic treatments. Clinicians can anticipate optimal benefits from at least five days of treatment, particularly using acupoints PC6, ST36, CV12, LI4, LR3, and ST25. Further high-quality studies are needed to establish standardized treatment regimens and explore its comprehensive effects on NV. Full article

Photoacoustic imaging (PAI) has emerged as a transformative modality for bridging traditional Chinese medicine (TCM) theory and contemporary biomedical research in acupuncture mechanism studies. This review assesses PAI’s capacity to decode acupuncture-induced neuromodulatory and hemodynamic effects, with dual focus on the central nervous system (CNS) responses and acupoint-specific microcirculatory dynamics. Leveraging the photoacoustic effect coupled with ultrasonic detection, PAI enables non-invasive, high-resolution mapping of cerebral hemodynamic parameters, including blood flow, oxygen saturation and hemoglobin concentrations, in real time. Experimental evidence from murine models of cerebral hypoperfusion and ischemic stroke demonstrates acupoint-specific spatiotemporal activation patterns, particularly at Yongquan (KI1) and Yanglingquan (GB34), revealing cortical hemodynamic reorganization and angiogenesis. At the microcirculatory level, PAI identifies functional transitions from quiescent to activated vascular states during disease progression, characterized by altered perfusion dynamics and vascular permeability. While structural metrics (e.g., microvascular density and curvature) show no significant differences in knee osteoarthritis models, functional parameters such as hemoglobin flux and oxygen metabolism emerge as critical biomarkers of acupoint specificity. PAI further enhances treatment precision through standardized acupoint localization, as evidenced by electrostimulation studies at Hegu (LI4) and Zhongwan (CV12). This synthesis highlights PAI’s dual contributions: (1) validating CNS-mediated systemic regulation via acupoint-brain functional correlations, and (2) providing multimodal quantification of microcirculatory dynamics. Future directions emphasize integration of molecular probes for neuroendocrine pathway visualization and multimodal imaging to address unresolved thermal/optical interactions. By synergizing TCM principles with advanced biophotonics, PAI establishes a paradigm for mechanistic acupuncture research and clinical translation. Full article

Background/Objectives: Transcutaneous electrical acupoint stimulation (TEAS), also known as transcutaneous electroacupuncture stimulation, delivers electrical pulses to the skin over acupuncture points (“acupoints”) via surface electrodes. Electroencephalography (EEG) is an important tool for assessing the changes in the central nervous system (CNS) that may result from applying different TEAS frequencies peripherally—i.e., acting via the peripheral nervous system (PNS)—and determining how these influence cerebral activity and neural plasticity. Methods: A total of 48 healthy volunteers were allocated in a semi-randomized crossover study to receive four different TEAS frequencies: 2.5 pulses per second (pps); 10 pps; 80 pps; and sham (160 pps at a low, clinically ineffective amplitude). TEAS was applied for 20 min to each hand at the acupuncture point Hegu (LI4). The EEG was recorded during an initial 5 min baseline recording, then during TEAS application, and after stimulation for a further 15 min, separated into three periods of 5 min (initial, intermediate, and final) in order to assess post-stimulation changes. Source localization analysis was conducted for the traditional five EEG frequency bands: delta (0.1–3.9 Hz), theta (4–7.9 Hz), alpha (8–13 Hz), beta (14–30 Hz), and gamma (30.1–45 Hz). Results: Within-group source localization analyses of EEG data showed that during the initial 5 min post-stimulation, theta oscillations in the 2.5 pps TEAS group increased over the parahippocampal gyrus (t = 4.42, p < 0.01). The 10 pps TEAS group exhibited decreased alpha rhythms over the inferior parietal gyrus (t = −4.20, p < 0.05), whereas the sham (160 pps) TEAS group showed decreased delta rhythms over the postcentral gyrus (t = −3.97, p < 0.05). During the intermediate 5 min post-stimulation, the increased theta activity over the left parahippocampal gyrus (BA27) remained in the 2.5 pps TEAS group (t = 3.97, p < 0.05). However, diminished alpha rhythms were observed in the 10 pps TEAS group over the postcentral gyrus (t = −4.20, p < 0.01), as well as in the delta rhythms in the sham (160 pps) TEAS group in the same area (t = −4.35, p < 0.01). In the final 5 min post-stimulation, reduced alpha rhythms were exhibited over the insula in the 10 pps TEAS group (t = −4.07, p < 0.05). Interaction effects of condition by group demonstrate decreased alpha rhythms in the 10 pps TEAS group over the supramarginal gyrus during the initial 5 min post-stimulation (t = −4.31, p < 0.05), and decreased delta rhythms over the insula in the sham TEAS group during the final 5 min post-stimulation (t = −4.42, p < 0.01). Conclusions: This study revealed that low TEAS frequencies of 2.5 pps and 10 pps modulate theta and alpha oscillations over the brain areas related to emotional and attentional processes driven by external stimuli, as well as neural synchronization of delta rhythms in the sham group in brain areas related to stimulus expectation at baseline. It is hoped that these findings will stimulate further research in order to evaluate such TEAS modulation effects in clinical patients. Full article

Mast cells are widely distributed in various parts of the human body and play a vital role in the progression of many diseases. Recently, the close relationship between mast cells and acupoints was elucidated, and the role of mast cells in acupuncture analgesia has attracted the attention of researchers worldwide. Using mast cells, acupuncture analgesia and acupoint as key words to search CNKI, PubMed, Web of Science and other databases, combining the representative articles in these databases with the published research papers of our group, we summarized: The enrichment of mast cells and the dense arrangement of collagen fibers, microvessels, and nerves form the basis for acupoints as the reaction sites of acupuncture; acupuncture can cause the deformation of collagen fibers and activate TRPV channels on mast cells membrane, so as to stimulate mast cells to release bioactive substances and activate nerve receptors to generate analgesic effect; system biology models are set up to explain the quantitative process of information initiation and transmission at acupuncture points, and indicate that the acupuncture effect depends on the local mast cells density. In a conclusion, this review will give a scientific explanation of acupuncture analgesia from the material basis of acupoints, the local initiation, and afferent biological mechanism. Full article

(1) Background: Acupuncture (AP) is a safe and effective analgesic therapy. Understanding how fine needles trigger biological signals can help us optimize needling manipulation to improve its efficiency. Adenosine accumulation in treated acupoints is a vital related event. Here, we hypothesized that extracellular ATP (eATP) mobilization preceded adenosine accumulation, which involved local activation of mechanosensitive channels, especially TRPV4 protein. (2) Methods: AP was applied at the injured-side Zusanli acupoint (ST36) of acute ankle arthritis rats. Pain thresholds were assessed in injured-side hindpaws. eATP in microdialysate from the acupoints was determined by luminescence assay. (3) Results: AP analgesic effect was significantly suppressed by pre-injection of GdCl₃ or ruthenium red in ST36, the wide-spectrum inhibitors of mechanosensitive channels, or by HC067047, a specific antagonist of TRPV4 channels. Microdialysate determination revealed a needling-induced transient eATP accumulation that was significantly decreased by pre-injection of HC067047. Additionally, preventing eATP hydrolysis by pre-injection of ARL67156, a non-specific inhibitor of ecto-ATPases, led to the increase in eATP levels and the abolishment of AP analgesic effect. (4) Conclusions: These observations indicate that needling-induced transient accumulation of eATP, due to the activation of mechanosensitive TRPV4 channels and the activities of ecto-ATPases, is involved in the trigger mechanism of AP analgesia. Full article

Acupuncture is clinically used to treat various diseases and exerts positive local and systemic effects in several nervous system diseases. Advanced molecular and clinical studies have continually attempted to decipher the mechanisms underlying these effects of acupuncture. While a growing understanding of the pathophysiology underlying several nervous system diseases shows it to be related to inflammation and impair cell regeneration after ischemic events, the relationship between the therapeutic mechanism of acupuncture and the p38 MAPK signal pathway has yet to be elucidated. This review discusses the latest advancements in the identification of the effect of acupuncture on the p38 signaling pathway in several nervous system diseases. We electronically searched databases including PubMed, Embase, and the Cochrane Library from their inception to April 2020, using the following keywords alone or in various combinations: “acupuncture”, “p38 MAPK pathway”, “signaling”, “stress response”, “inflammation”, “immune”, “pain”, “analgesic”, “cerebral ischemic injury”, “epilepsy”, “Alzheimer’s disease”, “Parkinson’s disease”, “dementia”, “degenerative”, and “homeostasis”. Manual acupuncture and electroacupuncture confer positive therapeutic effects by regulating proinflammatory cytokines, ion channels, scaffold proteins, and transcription factors including TRPV1/4, Na_v, BDNF, and NADMR1; consequently, p38 regulates various phenomena including cell communication, remodeling, regeneration, and gene expression. In this review article, we found the most common acupoints for the relief of nervous system disorders including GV20, GV14, ST36, ST37, and LI4. Acupuncture exhibits dual regulatory functions of activating or inhibiting different p38 MAPK pathways, contributing to an overall improvement of clinical symptoms and function in several nervous system diseases. Full article