As a startup founder in the sports industry, you may have heard about the potential of AI in fitness software over the past decade. However, incorporating AI into your fitness applications can still be confusing, especially if you haven’t worked with AI before. Today, we'd like to summarize what AI technology can offer to fitness applications and illustrate its use with some real-world examples.
Virtual Coaching Applications
AI coaching apps analyze exercise recordings in real-time, using computer vision and motion analysis. Users record their exercises with smartphones or wearables, capturing video or motion data. AI algorithms extract key points and track movements to assess form and biomechanics. By comparing to ideal standards, based on expert input or datasets, the app provides personalized, real-time feedback. This benefits users without access to in-person trainers, improving exercise technique and guidance.
\ BeONE Sports, a sports technology startup, is an example of an application that offers advanced specialized training for athletes. One of their innovative features is "comparative training," which allows athletes to compare their body mechanics and positioning with a proxy for perfect training. By using this app, athletes can learn and enhance their technique for better performance.
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Personalized Workout Recommendations
AI-powered personalized workout recommendation apps can generate customized workout plans. Users provide information about their fitness goals, exercise history, preferences, and limitations. This data forms a user profile that guides the AI algorithm. The algorithm then analyzes user data and identifies correlations between exercises, workout durations, intensity levels, and outcomes. This personalized approach increases user engagement, motivation, and the likelihood of achieving desired fitness outcomes.
\ You can find many examples of AI-based personal training apps on the market like Evolve AI, Fitbod, Freeletics, Zing Coach, and more.
Rehabilitation Solutions
AI can be utilized in the rehabilitation and recovery process for individuals with injuries, disabilities, or those undergoing medical treatments. These apps provide personalized guidance, monitoring, and support to help users enhance their physical function and regain mobility. They often incorporate wearable devices or sensors to track movements and relevant metrics during exercises. AI algorithms analyze the collected data to monitor progress and offer performance feedback in real-time.
\ It's still crucial to remember that these apps are intended to complement and enhance the rehabilitation process under the supervision of healthcare professionals rather than replacing professional medical advice and supervision.
\ Our team at MobiDev has been developing an application for the rehabilitation and remote care of the elderly. This app incorporates a human pose estimation model to detect and analyze pose movements. By comparing the user's exercise performance with a "virtual trainer," the app offers personalized recommendations on technique and injury prevention.
All-In-One Coaching Bots
Coaching bots are examples of solutions that integrate various AI technologies, including human pose estimation and conversational AI. They can assist athletes in refining their exercise technique, correcting posture, selecting appropriate exercises, offering diet recommendations, and more. These comprehensive coaching bots leverage AI to provide the latest advancements in fitness technology, delivering a convenient, all-in-one app experience.
Challenges and Future of Adopting AI in Fitness
Despite all the exciting things that AI can bring to building software products, the incorporation of this technology has certain challenges that you should be prepared for.
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- Technical Limitations: AI apps heavily rely on user-provided data, which can be challenging to input accurately. Motion analytics, for example, require users to follow strict filming rules to capture usable video. Poor lighting, inappropriate angles, and occlusive objects can result in frustrating retakes and inadequate input for the AI models.
- Data Accessibility: Fitness AI apps require a vast amount of data to recognize various body dimensions, sleeping patterns, and training capabilities. Collecting this data is an ongoing process, limiting the full potential of AI-enabled fitness apps until sufficient data is available.
- Trustworthiness of AI: The lack of transparency in AI decision-making raises concerns about trusting AI coaching recommendations. Users may question the ethics and reasoning behind AI's suggestions. Developers face the challenge of making applications more trustworthy by providing explanations behind AI decisions.
- Privacy and Regulations: AI-enabled fitness apps that collect and store information about diet programming or rehabilitation procedures must navigate healthcare regulations and privacy concerns. The broader the scope of the AI fitness project, the more privacy considerations it encompasses.
\ At the same time, the rapid advancement of artificial intelligence presents significant opportunities for founders of fitness and sports startups. To capitalize on this trend, it’s a good idea to begin integrating smart functionality into your offerings now. By doing so, you can establish a strong foundation for growth in this emerging and progressive market.
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