Development of Image Based Model for Basic Standing Yoga Poses that Control Type-2 Diabetes

Main Article Content

T. P. Kausalya Nandan
D. Madhavi

Abstract

Yoga is one of the ancient practices originated in India that helps in balancing mind and body of human. For the past few decades it has got wide spread throughout the world. Many are practicing it in the presence of yoga tutor or following some online modes. But improper practice may cause major harm to muscles and ligaments of the human body. There are different asanas proposed in the Patanjali Yoga Sutra that can cure different diseases. This paper, proposes a mathematical model for a set of yoga asanas that can help cure Type -2 Diabetes. A noninvasive analysis has been implemented using Kinect Sensor and LabVIEW software to analyze the performance of the practitioner. The joints are subjected to the flexibility of the practitioner without any overstress.

Article Details

How to Cite
Nandan, T. P. K. ., & Madhavi, D. (2023). Development of Image Based Model for Basic Standing Yoga Poses that Control Type-2 Diabetes. International Journal on Recent and Innovation Trends in Computing and Communication, 11(10s), 104–110. https://doi.org/10.17762/ijritcc.v11i10s.7602
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References

Available from: World Health Organization News room, fact sheets. https://www.who.int/newsroom/factsheets/detail/diabetes#:~:text=The%20number%20of%20people%20with,than%20in%20high% 2Dincome%20countries.

Available from: International Diabetes Federation: Diabetes facts and figures: Diabetes Atlas Tenth Edition 2021. https://idf.org/aboutdiabetes/what-is-diabetes/facts-figures.html

Raveendran, A.V., Deshpandae, A. and Joshi, S.R., Therapeutic role of yoga in type 2 diabetes. Endocrinology and Metabolism, 33(3), pp.307-317 (2018).

Calcaterra, V., Iafusco, D., Pellino, V.C., Mameli, C., Tornese, G., Chianese, A., Cascella, C., Macedoni, M., Redaelli, F., Zuccotti, G. and Vandoni, M., “CoVidentary”: An online exercise training program to reduce sedentary behaviours in children with type 1 diabetes during the COVID-19 pandemic. Journal of Clinical & Translational Endocrinology, 25, p.100261 (2021).

Shiju, R., Thomas, D., Al Arouj, M., Sharma, P., Tuomilehto, J. and Bennakhi, A., Effect of Sudarshan Kriya Yoga on anxiety, depression, and quality of life in people with type 2 diabetes: A pilot study in Kuwait. Diabetes & Metabolic Syndrome: clinical research & reviews, 13(3), pp.1995-1999 (2019).

Patil, S.G., Aithala, M.R., Naregal, G.V., Shanmukhe, A.G. and Chopade, S.S., Effect of yoga on cardiac autonomic dysfunction and insulin resistance in non-diabetic offspring of type-2-diabetes parents: A randomized controlled study. Complementary therapies in clinical practice, 34, pp.288-293 (2019).

Shantakumari, N. and Sequeira, S., Effects of a yoga intervention on lipid profiles of diabetes patients with dyslipidemia. Indian heart journal, 65(2), pp.127-131 (2013).

Bock, B.C., Thind, H., Fava, J.L., Dunsiger, S., Guthrie, K.M., Stroud, L., Gopalakrishnan, G., Sillice, M. and Wu, W., Feasibility of yoga as a complementary therapy for patients with type 2 diabetes: The Healthy Active and in Control (HA1C) study. Complementary therapies in medicine, 42, pp.125-131 (2019).

Xiaohui, T., Xiaoyu, P., Liwen, L. and Qing, X., Automatic human body feature extraction and personal size measurement. Journal of Visual Languages & Computing, 47, pp.9-18 (2018).

Shimada, N., Kimura, K. and Shirai, Y., July. Real-time 3D hand posture estimation based on 2D appearance retrieval using monocular camera. In Proceedings IEEE ICCV Workshop on Recognition, Analysis, and Tracking of Faces and Gestures in Real-Time Systems (pp. 23-30). IEEE (2001).

Werghi, N., Xiao, Y. and Siebert, J.P., A functional-based segmentation of human body scans in arbitrary postures. IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 36(1), pp.153-165 (2006).

Rama Prabha Krishnamoorthy, Abdul Rahman bin Senathirajah, Robinson Savarimuthu, Abdul Rahim Sadiq Batcha. (2023). An Ultracompact All Optical Two-Dimensional Photonic Crystal Based and Gate. International Journal of Intelligent Systems and Applications in Engineering, 11(4s), 328–333. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/2672

Ouellet, S. and Michaud, F., Enhanced automated body feature extraction from a 2D image using anthropomorphic measures for silhouette analysis. Expert Systems with Applications, 91, pp.270-276 (2018).

Omkar, S.N., Mour, M. and Das D., A mathematical model of effects on specific joints during practice of the sun salutation–a sequence of yoga postures. Journal of Bodywork and Movement Therapies, 15(2), pp.201-208 (2011.).

Kumar, A., Kapse, R.C., Paul, N., Vanjare, A.M. and Omkar, S.N., Musculoskeletal modeling and analysis of trikonasana. International journal of yoga, 11(3), p.201 (2018).

Islam, M.T., Al-Absi, H.R., Ruagh, E.A. and Alam, T., DiaNet: A deep learning based architecture to diagnose diabetes using retinal images only. IEEE Access, 9, pp.15686-15695 (2021).

Dremin, V., Marcinkevics, Z., Zherebtsov, E., Popov, A., Grabovskis, A., Kronberga, H., Geldnere, K., Doronin, A., Meglinski, I. and Bykov, A., Skin complications of diabetes mellitus revealed by polarized hyperspectral imaging and machine learning. IEEE Transactions on Medical Imaging, 40(4), pp.1207-1216 (2021).

Liang, X., Alshemmary, E.N., Ma, M., Liao, S., Zhou, W. and Lu, Z., Automatic Diabetic Foot Prediction Through Fundus Images by Radiomics Features. IEEE Access, 9, pp.92776-92787 (2021).

Gudigar, A., Samanth, J., Raghavendra, U., Dharmik, C., Vasudeva, A., Padmakumar, R., Tan, R.S., Ciaccio, E.J., Molinari, F. and Acharya, U.R., Local preserving class separation framework to identify gestational diabetes mellitus mother using ultrasound fetal cardiac image. IEEE Access, 8, pp.229043-229051 (2020).

Paul Garcia, Ian Martin, Laura López, Sigurðsson Ólafur, Matti Virtanen. Enhancing Student Engagement through Machine Learning: A Review. Kuwait Journal of Machine Learning, 2(1). Retrieved from http://kuwaitjournals.com/index.php/kjml/article/view/163

Zarkogianni, K., Athanasiou, M., Thanopoulou, A.C. and Nikita, K.S., Comparison of machine learning approaches toward assessing the risk of developing cardiovascular disease as a long-term diabetes complication. IEEE journal of biomedical and health informatics, 22(5), pp.1637-1647 (2017).

Anaya-Isaza, A. and Zequera-Diaz, M., Detection of diabetes mellitus with deep learning and data augmentation techniques on foot thermography. IEEE Access (2022).

El-Sappagh, S., Alonso, J.M., Ali, F., Ali, A., Jang, J.H. and Kwak, K.S., An ontology-based interpretable fuzzy decision support system for diabetes diagnosis. IEEE Access, 6, pp.37371-37394 (2018).

Zhou, Y., Wang, B., Huang, L., Cui, S. and Shao, L., A benchmark for studying diabetic retinopathy: segmentation, grading, and transferability. IEEE Transactions on Medical Imaging, 40(3), pp.818-828 (2020).

Jia, L., Wang, Z., Lv, S. and Xu, Z., PE_DIM: An Efficient Probabilistic Ensemble Classification Algorithm for Diabetes Handling Class Imbalance Missing Values. IEEE Access (2022).

Wang, Q., Cao, W., Guo, J., Ren, J., Cheng, Y. and Davis, D.N., DMP_MI: an effective diabetes mellitus classification algorithm on imbalanced data with missing values. IEEE Access, 7, pp.102232-102238 (2019).

Wen, D., Li, P., Zhou, Y., Sun, Y., Xu, J., Liu, Y., Li, X., Li, J., Bian, Z. and Wang, L., Feature classification method of resting-state EEG signals from amnestic mild cognitive impairment with type 2 diabetes mellitus based on multi-view convolutional neural network. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 28(8), pp.1702-1709 (2020).

Wang, Y., Li, P.F., Tian, Y., Ren, J.J. and Li, J.S., A shared decision-making system for diabetes medication choice utilizing electronic health record data. IEEE journal of biomedical and health informatics, 21(5), pp.1280-1287 (2016).

Ghosal, S., Kumar, A., Udutalapally, V. and Das, D., glucam: Smartphone based blood glucose monitoring and diabetic sensing. IEEE Sensors Journal, 21(21), pp.24869-24878 (2021).

Winter, D.A., Biomechanics and motor control of human movement. John Wiley & Sons (2009).