Asana Research Articles

Effect of Specific Yogic Asana on Mental Toughness and Stress Level of College Cricketers

Today we see that yoga is being applied in not less than 20 fields quite successfully including other sports like Kabaddi then why not other sports. Remarkably it is also true that many top sports stars are already practicing yoga postures and taking the best advantage. Cricket is long duration playing game which needs mentally strong and tough players to win matches and championships. Due to paramount importance of mental toughness in sports and particular in cricket that present paper focused to compare. Yoga has both preventive and therapeutic benefits. It has been shown to offer both physical and mental benefits to the body and the mind. , the present study was based on a pre-test, post-test design, a total of 100 male subjects were randomly selected from various colleges of Agra university. The subjects were College level batsman, with minimum 5 years of playing experience. The age of the subjects ranged between 20 to 22 years, the mean age was found to be 20.8 years. A pre test was taken of all the selected sports persons on the selected variables of Attention level and stress level, thereafter a yogic Asana program was implemented for 8 weeks and a post test is taken. For the collection of the data mental toughness was checked by Dr. Alan Goldberg (2004) Mental Toughness Questionnaire and stress questionnaire developed by Dave Hompes (2001) were selected. . The collected data was analyzed by computing descriptive statistics followed paired sample t test. A significant difference has been found in the pre and post test values of mental toughness and stress level of the Cricket players due to the yogic practice.

Deep Learning-Based Yoga Posture Recognition Using the Y_PN-MSSD Model for Yoga Practitioners.

In today's digital world, and in light of the growing pandemic, many yoga instructors opt to teach online. However, even after learning or being trained by the best sources available, such as videos, blogs, journals, or essays, there is no live tracking available to the user to see if he or she is holding poses appropriately, which can lead to body posture issues and health issues later in life. Existing technology can assist in this regard; however, beginner-level yoga practitioners have no means of knowing whether their position is good or poor without the instructor's help. As a result, the automatic assessment of yoga postures is proposed for yoga posture recognition, which can alert practitioners by using the Y_PN-MSSD model, in which Pose-Net and Mobile-Net SSD (together named as TFlite Movenet) play a major role. The Pose-Net layer takes care of the feature point detection, while the mobile-net SSD layer performs human detection in each frame. The model is categorized into three stages. Initially, there is the data collection/preparation stage, where the yoga postures are captured from four users as well as an open-source dataset with seven yoga poses. Then, by using these collected data, the model undergoes training where the feature extraction takes place by connecting key points of the human body. Finally, the yoga posture is recognized and the model assists the user through yoga poses by live-tracking them, as well as correcting them on the fly with 99.88% accuracy. Comparatively, this model outperforms the performance of the Pose-Net CNN model. As a result, the model can be used as a starting point for creating a system that will help humans practice yoga with the help of a clever, inexpensive, and impressive virtual yoga trainer.

Kinematics, dynamics, and muscle-synergy analysis of single-leg Yoga postures

Kinematics, dynamics, and muscle-synergy analysis of single-leg Yoga postures

The relationship between physical activity and diabetes in middle-aged and elderly people.

To investigate the association between diabetes symptoms and physical activity (PA) levels among middle-aged and older Chinese adults. Data for this study were obtained from 2018 Charles data. Z test, logistic regression analysis, and linear hierarchical regression analysis were performed in 5352 individuals aged ≥50 years with complete information. In terms of diabetes, 6.8% of the middle-aged and elderly people with diabetes were detected, and 93.2% of the middle-aged and elderly people without diabetes symptoms. The proportion of middle-aged and elderly people with high PA levels was 50.5%, and the proportion of middle-aged and elderly people with low PA was 49.5%. There was a significant positive correlation between low PA and diabetes (P < .05). After adjusting demographic characteristics (gender, registered permanent residence type, education level, age, widowhood) and health status characteristics (poor mood, asthma, hyperlipidemia, disability, memory disease, self-assessment of health status, hypertension, smoking, stroke, depression), there was still a statistical significance between PA level and diabetes (P < .05). The risk of diabetes of middle-aged and elderly people in China increases with age, while the risk of diabetes of middle-aged and elderly people with low level of PA is higher. The risk of diabetes is high among middle-aged and elderly people who are old, have poor self-evaluation health, suffer from hyperlipidemia, memory disease, and asthma. The middle-aged and old people should increase their PA levels to prevent and improve diabetes.

YoNet: A Neural Network for Yoga Pose Classification

Yoga has become an integral part of human life to maintain a healthy body and mind in recent times. With the growing, fast-paced life and work from home, it has become difficult for people to invest time in the gymnasium for exercises. Instead, they like to do assisted exercises at home where pose recognition techniques play the most vital role. Recognition of different poses is challenging due to proper dataset and classification architecture. In this work, we have proposed a deep learning-based model to identify five different yoga poses from comparatively fewer amounts of data. We have compared our model’s performance with some state-of-the-art image classification models-ResNet, InceptionNet, InceptionResNet, Xception and found our architecture superior. Our proposed architecture extracts spatial, and depth features from the image individually and considers them for further calculation in classification. The experimental results show that it achieved 94.91% accuracy with 95.61% precision.

A Deep Learning Framework for Classifying and Evaluating Yoga Exercises

Yoga is a type of physical activity that combines physical postures with breathing techniques. Cardiovascular disease is the leading cause of illness and mortality. Yoga's potential involvement in cardiac recovery can be incorporated into cardiovascular rehabilitation. Classifying and evaluating yoga exercises using a deep learning framework plays a significant role in postoperative recovery. Home based rehabilitation often suffers from a lack of patient adherence to prescribed exercise routines, resulting in longer treatment times and higher healthcare expenses. This study proposes a framework for classifying and evaluating the quality of yoga exercises. The ConvNet followed by the deep belief network model is used to create quality scores for input movements to evaluate the quality of yoga asanas. Additionally, various machine learning algorithms are deployed to identify the best performing algorithm. The proposed framework is tested using the COCO dataset and the publicly available dataset from KAGGLE. The model is implemented using a three stage pipeline. In the first stage, an estimator and detector model is used for feature extraction. In the second stage, restricted Boltzmann machines are used for dimensionality reduction in two steps: The forward pass and the backward pass. Finally, the ConvNet followed by the deep belief network is used to classify yoga postures. The quaternion data is treated as a multivariate Gaussian variable to create Markov random fields. To quantify yoga asanas, the Markov random fields network is triggered, and the resulting quaternion point is compared to standard pose data, increasing the likelihood that the yoga position is correct. The importance of our study is that it allows participants to watch their movement in real-time and to obtain a numerical estimate of the accuracy of their yoga stance. Using this method, we were able to achieve a precision of 99.99%, which was previously unattainable on this dataset. Our model is more robust than previous models in terms of performance.

Correlation of functional anatomy of hip musculature with yogic postures- Narrative review

The present study endeavours to explore the significant role pelvic stability contributes to maintaining the desired alignment in yoga asanas. The faulty postures due to sedentary lifestyles cause weakening of the muscles. This paper explains how Hip Musculature essentially The Gluteus Maximus and Gluteus Medius play an essential role in pelvic stability in many yoga asanas as well as a vital role in the health of our lumbar spine, sacrum, hip joints, and knees. Further, given the recent global interest in yoga asanas, it is critical to identify particular risk factors and injury processes to decrease the frequency with which these injuries occur. Also, this narrative review of the literature on hip musculature and its correlation with yoga asanas focuses on the factors leading to injuries, thereby helping to determine which asanas represent the greatest risk of injury and propose injury-prevention techniques.

Yogasanas in Spasmodic Dysmenorrhoea w.s.r to Udavartha Yonivyapath

Many women are familiar with the experience of spasmodic dysmenorrhoea, one of the commonest gynaecological conditions that affects the quality of life of many in their reproductive years. This condition manifested as painful menstruation, is the most frequently encountered gynaecological complaint and it can be included under Udavartha yonivyapat, caused by Apanavata vaigunya described in Ayurvedic classics. This situation not only has a significant effect on quality of life and personal health but also resulting in loss of work hours and depression. Scholastic backwardness and work absenteeism as a result of dysmenorrhoea is common nowadays. Most of the medical therapies for painful periods like analgesics, antispasmodics, NSAID, and anti-prostaglandins are having many side effects. Hormonal and surgical therapies are also not advisable to all type of patients, especially teenagers as it may harm their future reproductive capacity. Here comes the importance of Yoga, which provides good approach to treat primary dysmenorrhea. Yoga asanas helps in stretching muscles of pelvic cavity and increases the blood circulation to the pelvic organs and also helps to neutralize Apana vayu, which help in normal menstrual flow. The practice of Asanas has a beneficial impact on the whole body systems and helps in relaxation of both body and mind. This study is undertaken to find out the Yogasanas having pain relieving capacity in spasmodic dysmenorrhoea as it doesn’t cause any side effects but improve the quality of life. A thorough literary survey was done in Yogic classics especially Asanas for women’s health, Asanas for reproductive health and tried to compile the Asanas together having the pain relieving capacity in primary dysmenorrhoea.

A novel approach for yoga pose estimation based on in-depth analysis of human body joint detection accuracy.

Virtual motion and pose from images and video can be estimated by detecting body joints and their interconnection. The human body has diverse and complicated poses in yoga, making its classification challenging. This study estimates yoga poses from the images using a neural network. Five different yoga poses, viz. downdog, tree, plank, warrior2, and goddess in the form of RGB images are used as the target inputs. The BlazePose model was used to localize the body joints of the yoga poses. It detected a maximum of 33 body joints, referred to as keypoints, covering almost all the body parts. Keypoints achieved from the model are considered as predicted joint locations. True keypoints, as the ground truth body joint for individual yoga poses, are identified manually using the open source image annotation tool named Makesense AI. A detailed analysis of the body joint detection accuracy is proposed in the form of percentage of corrected keypoints (PCK) and percentage of detected joints (PDJ) for individual body parts and individual body joints, respectively. An algorithm is designed to measure PCK and PDJ in which the distance between the predicted joint location and true joint location is calculated. The experiment evaluation suggests that the adopted model obtained 93.9% PCK for the goddess pose. The maximum PCK achieved for the goddess pose, i.e., 93.9%, PDJ evaluation was carried out in the staggering mode where maximum PDJ is obtained as 90% to 100% for almost all the body joints.

Effect of Selected Yogic Asanas On Flexibility Of College Women Students

Effect of Selected Yogic Asanas On Flexibility Of College Women Students

Aasna: Kinematic Yoga Posture Detection And Correction System Using CNN

Yoga is a very popular form of exercise that originated in India that has numerous benefits for the mind and body. According to recent statistics, there are over 300 million yoga practitioners worldwide, with the number of yoga instructors increasing annually. However, incorrect yoga postures can lead to injuries and health complications. This highlights the importance of correct yoga posture and the need for a system that can detect and correct improper poses. This abstract presents a yoga posture detection and correction system designed using OpenCV for computer vision, and kinematic representation of the human body considering 17 points mapped on the human body, utilizing the tf-pose estimation algorithm for precise pose estimation. The system also includes a convolutional neural network (CNN) model developed using the Keras API and trained on the TensorFlow platform's MoveNet architecture for handling training of the model. The MoveNet pose estimation module has been used to detect keypoints of the human body which achieved an accuracy of 99.88%. The system works by live capturing of the yoga practitioner using a camera, extracting the key features of the pose, and comparing them with a trained data model of known yoga poses. If the pose is incorrect, the system provides real-time feedback to correct the pose.

A Survey on Yogic Posture Recognition

Yoga has been a great form of physical activity and one of the promising applications in personal health care. Several studies prove that yoga is used as one of the physical treatments for cancer, musculoskeletal disorder, depression, Parkinson’s disease, and respiratory heart diseases. In yoga, the body should be mechanically aligned with some effort on the muscles, ligaments, and joints for optimal posture. Postural-based yoga increases flexibility, energy, overall brain activity and reduces stress, blood pressure, and back pain. Body Postural Alignment is a very important aspect while performing yogic asanas. Many yogic asanas including uttanasana, kurmasana, ustrasana, and dhanurasana, require bending forward or backward, and if the asanas are performed incorrectly, strain in the joints, ligaments, and backbone can result, which can cause problems with the hip joints. Hence it is vital to monitor the correct yoga poses while performing different asanas. Yoga posture prediction and automatic movement analysis are now possible because of advancements in computer vision algorithms and sensors. This research investigates a thorough analysis of yoga posture identification systems using computer vision, machine learning, and deep learning techniques.

Impact of yoga asana on selected physiological variables

Now a days, our modern society realise about the significance of yoga in their daily life. That’s why the present investigation was taken as an initiative to find out the effect of yoga asana on selected physiological variables among high school boys. The study was conducted on 60 high school boys of Banipur Baniniketan high school, divided into two groups equally, namely control and experimental group. Their age ranged from 12 to 14 years. The experimental group treated by a six weeks training programme based on yoga asana whereas the control group did not undergo any type of training. Respiratory rate, heart rate, systolic blood pressure, diastolic blood pressure, and breathe hold time were selected as physiological variables and were measured using the standardized tests before and after given the treatment. Analysis of covariance (ANCOVA) was employed to analysis the data statistically. In results, significant effects were observed on respiratory rate, heart rate, systolic blood pressure and breathe hold time whereas in case of diastolic blood pressure, insignificant result was found.

Miniature Crane Prototype: A Novel Approach for Recognizing Yoga Postures to Treat Autistic Children

The paper presents a miniature crane prototype including a deep learning model especially designed for autistic children to assist them by teaching yoga. The objective of the paper is to propose a solution to help autistic kids overcome their difficulties faced in their local environment and adapt themselves to society for their well-being. Autistic kids find it hard to involve in social communications and feel insecure to talk with unknown people. Also, some of the kids have repetitive behaviors. To propose a solution, we introduce a miniature crane prototype to assist children in teaching yoga by which autistic kids can overcome their social difficulties. Play can create a positive impact on children during the learning phase and get rid of their difficulties. The play will take the input of the user and react accordingly. The miniature is mobile to get closer and playable with children by Responsive incorporation. The miniature can capture pictures depicting the behavior of the kid and respond to the kid through the LCD screen. The play enhances the activity of the kid and motivates them to learn yoga. The play is included with a yoga detection model which helps the play assist kids in learning yoga. The deep learning algorithm AlexNet is used which can detect and instruct while learning yoga. The model achieves higher accuracy of 98.61% which helps in assisting yoga postures the children with the proper instructions.

KILO - Fitness application with posture estimation

The lockdown measures taken by countries across the globe in light of the COVID-19 pandemic has made people realize the importance of a healthy lifestyle. As more people try to change their habits to adopt fitness routines, they tend to perform exercises without knowing which ones are for beginners and how long they should be working out for. In proposed work, we focus on implementing a fully functional workout app built using flutter, a cross-platform development framework to develop applications for iOS and android, supported by a backend service provided by firebase. This paper surveys different technologies used in pose estimation /classification as well as the different architectures used for the app development in Flutter. It also focuses on the importance of yoga and a technology aided approach for performing yoga poses. The grave nature of challenges faced while doing yoga such as performing it with incorrect form or postures as well as the cost of classes. With novel computer vision techniques, human pose estimation sees a great future. The work delves into the means of deploying yoga pose estimation on an android application, the modeling of the app and the working of each component.

Coherence and vitals of medicinal herbs, nutrients, and yoga in stress management and psychological stasis

Abstract When the time lows of the psychological body, about the human mind, there is a vital relationship between the psychological and somatic body leading to stress and mishaps. This could be a lack of coherence among significant components in the body, which are characterized by hormones such as cortisol and adrenaline that come into play. Cortisol and adrenaline are released when there is usually a response of fight or flight, where these hormones get ready to handle the body’s reaction, and when this happens properly, it yields stress. Stress occurs through all age groups across every ethnicity and population, as the functioning of the mind is very similar. Managing this emerging stress and anxiety condition could be done through the easy way of the modern system of medicine, allopathy. Alternatively, the traditional method comes in handy to maintain such a condition with hardly any long-term side effects. A few conventional techniques like the practice of yoga, support of the proper nutrients, and certain medicinal herbs are bent to see a change in the perspective of coping mechanisms that results in a stress-free environment within the human mind. Many patterns of practices are noticed that there are specific nutrients and supplements formulated with medicinal herbs with significant pharmacological properties and the ancient activity of yoga aid in stress management. Using and practicing regularly can help in an integrated caliber of living. This review article sheds information and collation on such significant medicinal herbs, nutrients, and renounced practices of yoga that play together in the balance of the human body to overcome the distress of the mind. Many studies have noticed that medicinal herbs, nutrients, and specific yogic asanas help handle stress and anxiety, giving a holistic living pattern.

Effect of a Nurse Led Multi-intervention Program on Quality of Life, Subjective Well-being and Level of Thyroid Hormones among Patients with Hypothyroidism- A Quasi-experimental Double arm Study

Introduction: Hypothyroidism is a leading public health concern, affecting one in ten Indians. Along with conventional treatment with supplemental Thyroid Hormones (TH), problems associated with hypothyroidism can be managed with complimentary nursing interventions. Aim: To assess the effect of a nurse-led multi-interventional program on Quality of Life (QoL), Subjective Well-Being (SWB), and level of TH among patients with hypothyroidism. Materials and Methods: A quasi-experimental double arm study was conducted from August 2021 to October 2021, at selected endocrinology clinics on patients with hypothyroidism were divided into interventional (n=39) and control group (n=38) non randomly. Information related to socio-demography, QoL, SWB, and TH levels were collected and followed by the implementation of a nurse-led multi-intervention program for the intervention group. The intervention was done individually, which consisted of a demonstration of yoga asana, yoga mudra, and neck exercises. Two-way repeated measures Analysis of Variance (ANOVA) was performed, to check if there is any significant difference in the average QoL/SWB/level of TH across different time points as well as between the experimental and control group. Results: A total of 77 participants 64 (83.1%) males and 13 (16.9%) females were included in the study with maximum participants belonged to the age group of 18-28 years. It was observed that after the implementation of multi-intervention program QoL was significantly improved among the experimental group (F=31.53, &lt;0.001), and SWB also significantly improved (F=36.615, &lt;0.001). Thyroid Stimulating Hormones (TSH) were significantly reduced among the experimental group (F=3.39, p=0.022) and Thyroxine (T4) levels were statistically significant among the experimental group (F=3.151, p=0.030). Conclusion: Patients with hypothyroidism require holistic care. Patients with hypothyroidism could be intervened with programs like yoga, neck exercise, pranayama, and yoga mudras.

Effect of yoga therapy on osteoarthritis of the knee

Background: Osteoarthritis (OA) is the most prevalent chronic disease and is a leading cause of pain and disability in most countries worldwide.Objective: To see the effect of the yoga program on patients with osteoarthritis of the knee.Design: single group longitudinal pre-post study.Setting: The study was conducted on thirty patients with KOA in residential health care Centre in Hissar, Haryana, India, between the periods of September to December 2022.Participants: 30 patients in which 28 women and 2 males with symptomatic knee osteoarthritis.Intervention: yoga practices intended to act physically, emotionally, Intellectually, and spiritually level and includes yoga postures, breathing exercises, internal cleansing techniques, meditation, pranayama, and relaxation techniques for one weak.Measurements: WOMAC.Results: While calculating the data with the help of SPSS 26 Version calculating significance value is 0.00 which is less than the level of significance.Conclusion: Results of this study showed a beneficial effect in reducing the cardinal symptoms of OAK. Therefore, yoga therapy can be used as an alternative and complementary therapy in OAK.

Cam Based Fine-Grained Spatial Feature Supervision for Hierarchical Yoga Pose Classification Using Multi-Stage Transfer Learning

Cam Based Fine-Grained Spatial Feature Supervision for Hierarchical Yoga Pose Classification Using Multi-Stage Transfer Learning

Effect of Yoga and Meditation on Different Health Parameters of the Yoga Practitioners

Yoga practitioners always look energetic, ever young and healthy compared to others because yoga postures (Asana) make the body flexible. Meditation (Dhyan) and breathing exercise (Pranayama) keep the physical, mental and spiritual wellbeing. The objective of this study is to identify the effect of Yoga and Meditation on different health parameters of the Yoga Practitioners. The method applied in this study was quantitative, descriptive based on the five points Likert Scales Ranking. The Wilcoxon Signed Rank test (2-tailed) revealed that a statistically positive significantly effect on health parameters after attended in yoga class, Z = -10.990, p&lt;0.01 (r=0.59)and meditation, Z= 10.544, p&lt;0.01 with large effect size (r=0.57). The Pearson correlation analysis result showed significant correlation between the impact of yoga and meditation on regular practitioners. The relative importance index (RII) analysis of respondent’s perceptions on each category, happiness had scored highest ranking. This study concluded that, yoga and meditation had prompt effect on the entire health of regular yoga and meditation practitioners to enhance complete wellbeing who practiced three to six months. Similarly, yoga and meditation indicated higher effect on the other domains of physical, mental and spiritual health parameters. While analysis the data, the female participants were found more benefited than that of male participants.