Abstract
Acupressure is a noninvasive method in traditional Chinese medicine to increase blood circulation, relieve discomfort, promote health, and prevent disease. This paper presents a multifunctional acupoint application system that not only provides real-time visualization of acupoints on mobile devices for users’ self-acupressure but also provides health care, education, and entertainment through acupressure. The system allows users to obtain acupoint information to relieve specific discomfort or symptoms. It automatically marks the requested acupoints on a real-time camera stream to guide users to locate acupoints so that even users unfamiliar with acupoints can easily find acupoints for self-acupressure. Three core technologies are used: acupoint localization and knowledge, real-time image recognition, and augmented reality. This paper details the system design and implementation. This system uses Google’s machine learning kit for facial detection to extract the user’s facial features and contours in real time on a mobile device. These contour points are used as landmarks with specific displacements to locate acupoints. As there are many acupoints and various positioning methods, the acupoint location is traditionally described in words through specific feature points and corresponding displacements related to each person’s physiological characteristics. This work proposes a novel acupoint positioning and marking mechanism based on the standard acupoint localization, which formalizes various acupoint positioning methods so that positions can be processed and stored in an acupoint database established in this system. This positioning information allows the proposed mechanism to fulfill real-time visualization of acupoints in augmented reality on the camera stream. Experimental results show that the proposed system locates and marks acupoints with low latency and high accuracy. Moreover, the system also provides recommendations for further medical treatment and a mini-game that tests knowledge of acupoints, which enhances users’ experience of acupoint massage.
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The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.
References
Android Medical—Best medical apps for Android, Available from: https://www.androidmedical.com/apps-acupressure.
J. Petr: Android application for acupressure, master thesis, Department of Computer Science, Czech Technical University in Prague, April 2020
K. Štěpán: iOS application for acupressure, master thesis, Department of Computer Science, Czech Technical University in Prague, May 2020
H. Jiang, J. Starkman, C. H. Kuo, and M. C. Huang, Acu glass: quantifying acupuncture therapy using Google glass, Proceedings of the 10th EAI International Conference on Body Area Networks, 2015, 7–10, https://doi.org/10.4108/eai.28-9-2015.2261520.
M. Chang and Q. Zhu, Automatic location of facial acupuncture-point based on facial feature points positioning, Proceedings of the 2017 5th International Conference on Frontiers of Manufacturing Science and Measuring Technology (FMSMT 2017), 2017, 545–549, https://doi.org/10.2991/fmsmt-17.2017.111.
Lan, K.C., Hu, M.C., Chen, Y.Z., Zhang, J.X.: The application of 3D morphable model (3DMM) for real-time visualization of acupoints on a smartphone. IEEE Sens. J. 21, 3289–3300 (2021). https://doi.org/10.1109/JSEN.2020.3022958
M. Zhang, J. P. Schulze, and D. Zhang, FaceAtlasAR: Atlas of Facial Acupuncture Points in Augmented Reality, 11th International Conference on Computer Science and Information Technology, Vancouver, Canada, May 29–30, 2021, https://doi.org/10.48550/arXiv.2111.14755.
Zhang, M., Schulze, J.P., Zhang, D.: E-faceatlasAR: extend atlas of facial acupuncture points with auricular maps in augmented reality for self-acupressure. Virtual Real. (2022). https://doi.org/10.1007/s10055-022-00663-1
J. X. Zhang: Localization of foot acupoints on a smartphone using augmented reality, M.S. Thesis, Institute of Medical Informatics, National Cheng Kung University, Tainan, Taiwan, R.O.C., 2021
G. R. Huag: On the development of an augmented reality system for palm acupoint, M.S. Thesis, Department of Multimedia Design, National Taichung University of Science and Technology, Taichung, Taiwan, R.O.C., 2016
Gach, M.R.: Acupressure: how to cure common ailments the natural way. Piatkus Books, London, England (1993)
Focks, C.: Atlas of Acupuncture. Elsevier, The Netherlands (2008)
Bleecker, D.: Acupuncture points handbook: a patient’s guide to the locations and functions of over 400 acupuncture points. Draycott Publishing, LLC, Texas, USA (2017)
Tan, H., Tumilty, S., Chapple, C., Liu, L., McDonough, S., Yin, H., et al.: Understanding acupoint sensitization: a narrative review on phenomena, potential mechanism, and clinical application. Evid. Based Complement. Altern. Med. 2019, 9 (2019). https://doi.org/10.1155/2019/6064358. (Article ID 6064358)
Kim, C., Yoon, D., Lee, Y., Jung, W., Kim, J., Chae, Y.: Revealing associations between diagnosis patterns and acupoint prescriptions using medical data extracted from case reports. J. Clin. Med. 8, 10 (2019). https://doi.org/10.3390/jcm8101663. (Article 1663)
Robinson, N., Lorenc, A., Liao, X.: The evidence for Shiatsu: a systematic review of shiatsu and acupressure. BMC Complement. Altern. Med. 11, 15 (2011). https://doi.org/10.1186/1472-6882-11-88. (Article 88)
Napadow, V., Liu, J., Kaptchuk, T.J.: A systematic study of acupuncture practice: acupoint usage in an outpatient setting in Beijing, China. Complement. Ther. Med. 12, 209–216 (2004). https://doi.org/10.1016/j.ctim.2004.10.001
R. Hosseinabadi, K. Noroozi, Z. Poorismaili, M. Karimloo, and S. S. Maddah, Acupoint massage in improving sleep quality of older adults, J. Reha, 9(2008), 8–14, http://rehabilitationj.uswr.ac.ir/article-1-247-en.html
World Health Organization, Who Standard Acupuncture Point Locations in The Western Pacific Region, 2008
Dr. Chen, Hsin-Hao, Attending physician, Department of Family Medicine, Mackay Memorial Hospital, Hsinchu, Taiwan. Available from: https://www.hc.mmh.org.tw/doctor_view.php?depid=49&did=235
Core ML - Integrate machine learning models into your app., Apple Developer. Available from: https://developer.apple.com/documentation/coreml
Create ML - Create machine learning models for use in your app., Apple Developer. Available from: https://developer.apple.com/documentation/createml
Turi Create API Documentation. Available from: https://apple.github.io/turicreate/docs/api/
ML Kit, Google. Available from: https://developers.google.com/ml-kit/
TensorFlow Lite, Google. Available from: https://www.tensorflow.org/lite/
PyTorch Mobile. Available from: https://pytorch.org/mobile/home/
F. Zhang, V. Bazarevsky, A. Vakunov, A. Tkachenka, G. Sung, C. L. Chang, and M. Grundmann: Mediapipe: A framework for building perception pipelines. Available from: http://arxiv.org/abs/1906.08172 (2019)
ML Kit—Face Detection, Google. Available from: https://developers.google.com/ml-kit/vision/face-detection
Lan, K.C., Litscher, G.: Robot-controlled acupuncture—an innovative step towards modernization of the ancient traditional medical treatment method. Medicines (Basel) 6(3), 87 (2019). https://doi.org/10.3390/medicines6030087
Kamble, M.S., Londhe, V.: 3-D face image identification from video streaming using map reduce (hadoop). Int. Res. J. Eng. Technol. 5, 1613–1616 (2018)
Danish, M., Jiang, Q.: 3D Localization of hand acupoints using hand geometry and landmark points based on RGB-D CNN fusion. Ann. Biomed. Eng. (2022). https://doi.org/10.1007/s10439-022-02986-1
OpenCV. Available from: https://opencv.org/
Android Studio. Available from: https://developer.android.com/studio/intro
Android Developer Guides. Available from: https://developer.android.com/guide
Maria DB. Available from: https://mariadb.org/
SQLite. Available from: https://www.sqlite.org/index.html
Introducing JSON. Available from: https://www.json.org/json-en.html
Android Developer Guides. CameraX. Available from: https://developer.android.com/training/camerax
Beautiful Soup Documentation. Available from: https://www.crummy.com/software/BeautifulSoup/bs4/doc/
National health insurance administration ministry of health and welfare. Available from: https://www.nhi.gov.tw/English/
Canvas, Android Developers. Available from: https://developer.android.com/reference/android/graphics/Canvas
Acknowledgements
We would like to thank H. W. Lee and W. R. Yang for their assistance in the project development. We also thank H. L. Wu and C. F. Chung for participating in the experiments. Special thanks to the anonymous reviewers for their valuable comments in improving this research. This research was funded in part by the Ministry of Science and Technology, Taiwan, grant numbers 109-2813-C-260-017-H, 109-2221-E-260-011, 110-2221-E-260-001, and 111-2221-E-260-006.
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Mei-Ling Chiang performed the project management. Mei-Ting Su and Mei-Ling Chiang wrote the main manuscript text. Mei-Ting Su, Chia-Hsuan Tsai, Chi-Wei Lin, Rong-Xuan Liu, and Yong-Ting Juang cooperated to design and implement the proposed system. Mei-Ting Su performed experiments, and Hsin-Hao Chen verification experimental results. All authors reviewed the manuscript.
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Su, MT., Chiang, ML., Tsai, CH. et al. An acupoint health care system with real-time acupoint localization and visualization in augmented reality. Multimedia Systems 29, 2217–2238 (2023). https://doi.org/10.1007/s00530-023-01104-y
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DOI: https://doi.org/10.1007/s00530-023-01104-y