Human Pose Estimation in Fitness Applications

Some 10 years ago the notion of “digital fitness” seemed like something futuristic. Today we see the constant growth of the fitness industry enriched by artificial intelligence to make a totally brilliant product that we use on a daily basis and thank those smart heads who made sport more accessible and affordable. During pandemic times, when physical activity has been a savior and a major outlet for both body and mind, AI-powered fitness apps proved especially efficient. Thanks to that, now artificial intelligence is being effectively used in sports. So why not take a quick look into the essence of fitness-AI tandem. How Does the AI-Fitness Cohesion Work? As a result of the intersection between AI and fitness pose estimation was born. Initially, human pose estimation technology is based on human body parts detection and comparison of their movement trajectory or static pose that was given in the preset algorithms. The idea is fairly simple - to ensure accuracy and atraumatic technique performance. If you’re still unfamiliar with any of the fitness apps, the idea is the following: you place a smartphone camera in front of your place for exercising, and the app signals if you do them correctly or if your technique needs to be corrected. Types of Pose Estimation Models Human body detection is by no means an easy task. Artificial Intelligence should have enough examples to be able to “see” and recognize body parts in various environments. After identifying body parts AI builds one of three types of pose estimation models according to the difficulty and sophistication of the app. ❏ Skeleton Model looks like a simple set of lines and dots connected to make up a human body's simplest image. ❏ Contour Model, respectively, recreates a body contour to provide a more accurate image to ensure safe performing of physical exercises. ❏ 3D Model is the newest type of pose estimation model which analyses all 3 dimensions of the human body and creates the most comprehensive image. Today computer vision has been developed to the level that allows 99% of fitness apps to operate using 3D human pose estimation. Such an advanced approach elevates the accuracy of digital training making AI-powered fitness apps no worse than sessions conducted by professional couches offline. How Pose Estimation Meets Yoga and Pilates Challenge Yoga and pilates are the two types of activities where right angles and precise exercise performance mean more than a lot. The trend for mindfulness has brought yoga to the pedestal and human pose estimation technology had to face a new challenge. The diversity of asanas and the need to estimate the appropriate movement of joints and muscles makes yoga AI-powered apps use thousands of real-time body images to achieve ultimate accuracy. Pilates is another popular kind of training that has been fairly easy to do at home even during pre-pandemic times. But even with online pilates classes the risks to do more harm than good are not excluded. That’s why AI-driven pilates apps are indispensable for those who want to stay in shape being sure they’re under scrupulous smart control. See the Benefits Human pose estimation technology is not perfect. But the range of benefits is way more impressive than the chances of possible drawbacks. Injury-Free Exercises The first and foremost is that AI-powered apps like the ones InData Labs develops don’t let injuries happen. Going to the gym with or without a fitness coach doesn’t necessarily mean that you’re secured against sprains and traumas simply because coaches are not always as careful and knowledgeable as they’re supposed to be. Obviously, working out on our own increases injury chances as well. Personalized Workouts Another pro of smart fitness apps equipped with computer vision is that the workout routine is fully customizable. It means that an app will first ask you several questions to identify the set of exercises that will work best for your goal, taking into account your physical level and other specific features. AI-powered fitness apps are made to cater to any person making each workout session fun and safe. Physical Recovery Therapy Apart from the basic sport-and-fitness-targeted field, pose estimation also works for post-injury recovery. The recuperation period is crucial for ensuring a healthy and full-fledged post-trauma comeback. The pandemic has made it harder for people to visit hospitals and have their therapy sessions there. That’s why having an opportunity to save time and recover quicker is a real-life saver for those who are in need of a careful and supervised AI coach. The Final Thought Computer vision holds our future, trying to enhance every dimension of our lives. Human pose estimation technology has proved efficient and established itself as a vital part for anyone who has been caught in lockdown trying to stay fit and in the post-pandemicpost-pandemic era, as being able to work out at home, saving a considerable amount of time and money are both beneficial and addictive.