The in-house Yoga pose dataset consists of 27 individuals, comprising nineteen females and eight males, performing each of the ten Yoga poses, namely Malasana, Ananda Balasana, Janu Sirsasana, Anjaneyasana, Tadasana, Kumbhakasana, Hasta Uttanasana, Paschimottanasana, Uttanasana, and Dandasana. The videos of the Yoga poses are collected in both 1080p and 4K resolution at a rate of 30 frames per second using MI Max and One Plus 5T mobile phones. We captured the videos at various locations like gardens, rooms, certified Yoga centers, and terraces to increase the generality of the dataset and make the dataset more realistic so that the model trained using the dataset would work in a complex real-world environment. It is worth mentioning that our in-house created dataset does not contain any video sample created in the controlled laboratory-like environment with proper illumination. We did this deliberately to enhance the generalization ability of the models trained on our dataset. The individuals have voluntarily participated in data collection and have performed the ten Yoga poses with possible variations.

Here are a few use cases for this project:

1. Ergonomics Evaluation: This model can be used by OSHA/Ergonomics companies or consultants for evaluating employees' postures, particularly those in sedentary roles, to recommend improvements and reduce the risk of musculoskeletal disorders.

2. Health & Wellness Applications: The model can be used in apps that promote good posture, which may help individuals combat issues like back pain. These apps can provide automatic feedback on user's posture in real-time.

3. Virtual Fitness Training: In the context of fitness or yoga classes, the model can evaluate whether the participants are performing the postures correctly or not.

4. Physical Therapy: Physical therapists can use this model to create and monitor rehabilitation programs. They can give patients personalized, remote feedback during their recovery.

5. Gaming Industry: For interactive video games, the model can be used to observe and interpret players' postures to control in-game characters, adding another level of challenge and immersion.

Survey of people with cancer to understand their experiences and preferences with yoga. Delphi study with yoga teacher for recommendations regarding practices to address depression and anxiety. 1 dataset for a survey of people with cancer re yoga experiences and preferences. 1 dataset with several rounds of delphi study of yoga teachers for practices and techniques for yoga for depression and anxiety in people with cancer. This dataset cannot be published openly due to ethics considerations. To discuss the research, please contact Maria Gonzalez on 13515140@student.westernsydney.edu.au ORCID 0000-0001-8798-7212.

The brain plays a crucial role in regulating metabolic disorders through its structural and functional integrity. It acts a core centre for the function of the body and mind. Any changes to this can cause serious damage and lead to conditions developing in later life. Within this digital era, the active promotion of digital based careers and opportunities to work from home have resulted in people living more sedentary lifestyles, this can have an adverse effect on the body and mind.

Abstract copyright UK Data Service and data collection copyright owner.

The Active People Survey commenced in October 2005 and was commissioned by Sports England. The primary objective of the survey was to measure levels of participation in sport and active recreation and its contribution to improving the health of the nation. Sport and active recreation included walking and cycling for recreation in addition to more traditional formal and informal spots. When measuring sports participation the survey not only recorded the type of activity but also the frequency, intensity and duration of the activity.

The Active People Survey was replaced by the Active Lives Survey in November 2015. Active Lives is a new survey with a different methodology and intended to measure different outcomes from those in the Active People Survey, however there are similarities as it was important that data could be reproduced on some of the key measures.

More general information can be found on the Sport England Active Lives Survey webpage and the Active Lives Online website, including reports and data tables.



Variables no longer available on the Active People Survey
A number of questions were dropped from the Active People Survey for the last six months of its lifespan, due to dual running with the new Active Lives Survey. So, there is no data available for them in the APS10 dataset. The questions dropped covered:

• Reasons for participation;
• Sport provision;
• Change in participation;
• Likelihood to do more sport;
• Gender identity;
• Sexual identity;
• Volunteering by individual sport.

Some other variables are also unavailable, for example D14B (How is your health in general?) and D14ar (Overall how satisfied is your life nowadays?), but may still be referenced in the documentation.


Main Topics:

Topics covered in the Active People Survey include:

• Sport and physical activity
• Health behaviour
• General health and wellbeing
• Sports volunteering
• Sport spectating
• Club membership

Background: Yoga is a mind-body practice that can elicit robust health and wellbeing effects for older adults. As a result, there is increased public and academic interest into the potential benefits of yoga for older people with mild cognitive impairment (MCI) and dementia. Methods: Literature searches in five databases (CENTRAL, PubMed and EBSCOHost indexing CINAHL Plus, PsycINFO, Psychology and Behavioural Sciences Collection) were conducted from the databases' date of inception through to 4 September 2020 to identify pre-post single and multigroup studies of yoga-based interventions involving people with MCI or dementia. Effects on cognitive, mental, and physical health were evaluated, as was safety and study quality. Results: Database searches identified 1431 articles. Of these, 10 unique studies met inclusion criteria (total 421 participants). Four studies each implemented Kundalini yoga and chair yoga, while two employed Hatha yoga. Most programs ran for 12 weeks (n = 5) and compared yoga to a control group (n = 5). Most studies reported improved cognition, mood, and balance. However, these effects were marred by the high risk of bias identified in all articles. Four studies assessed safety, with one instance of dizziness reported. Conclusions: In this emerging field, these studies show that yoga may be safe and beneficial for the wellbeing of people with MCI or dementia. More high quality randomised controlled trials are needed to improve the evidence-base and overcome the limitations of existing studies.

SAR Detection

## Overview

SAR Detection is a dataset for object detection tasks - it contains People annotations for 1,980 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

IntroductionThough several lines of evidence support the utility of yoga-based interventions in diabetes prevention, most of these studies have been limited by methodological issues, primarily sample size inadequacy. Hence, we tested the effectiveness of yoga-based lifestyle intervention against diabetes risk reduction in multicentre, large community settings of India, through a single-blind cluster-randomized controlled trial, Niyantrita Madhumeha Bharat Abhiyan (NMB). Research Design and MethodsNMB-trial is a multicentre cluster-randomized trial conducted in 80 clusters [composed of rural units (villages) and urban units (Census Enumeration Blocks)] randomly assigned in a 1:1 ratio to intervention and control groups. Participants were individuals (age, 20–70 years) with prediabetes (blood HbA1c values in the range of 5.7–6.4%) and IDRS ≥ 60. The intervention included the practice of yoga-based lifestyle modification protocol (YLP) for 9 consecutive days, followed by daily home and weekly supervised practices for 3 months. The control cluster received standard of care advice for diabetes prevention. Statistical analyses were performed on an intention-to-treat basis, using available and imputed datasets. The primary outcome was the conversion from prediabetes to diabetes after the YLP intervention of 3 months (diagnosed based upon HbA1c cutoff >6.5%). Secondary outcome included regression to normoglycemia with HbA1c

BackgroundThe young Indian population, which constitutes 65% of the country, is fast adapting to a new lifestyle, which was not known earlier. They are at a high risk of the increasing burden of diabetes and associated complications. The new evolving lifestyle is not only affecting people’s health but also mounting the monetary burden on a developing country such as India.AimWe aimed to collect information regarding the prevalence of risk of diabetes in young adults ( 60), moderate (IDRS score 30–50), and low (IDRS < 30) diabetes risk in young adults (