| Abstrakt: |
Yoga is a remarkable form of physical activity due to its most promising uses in personal health care. Several studies show that yoga can help with cancer, muscular, skeletal disorders, depression, parkinson's disease, and respiratory and cardiac illnesses. The entire body is the core focus for the practice of yoga. For ideal posture, the muscles, ligaments, and joints are to be aligned mechanically. Postural-based yoga improves flexibility, energy, and total brain activity while decreasing stress, blood pressure, and anxiety. Through the practice of body postural alignment techniques in yoga, key and common grievance such as back ache is critically addressed by practicing yogasanas regularly. Bending forward or backward is necessary in yogic asanas such as uttanasana, kurmasana, ustrasana, and dhanurasana. In addition, improper executed asanas can cause strain in the joints, ligaments, and backbone can create issues in human body joints. It is therefore important to monitor the correct yoga postures when performing the various asanas. The prediction of yoga postures and automatic movement analysis are now possible thanks to advances in computer vision algorithms and sensors. This research explores an in-depth analysis of improper yogasanas recognition and collectively summarizing the ensemble of yogic postures using computer vision, machine learning and deep learning techniques. (not doing the correction of postures in this research. [ABSTRACT FROM AUTHOR] |
