News, articles, tips & tricks
How to Use LLMs and Pose Estimation to Create an AI Fitness Coach
The LLM analyses this data provided by QuickPose ML algorithms and provides motivational messages, celebrating achievements and encouraging continued effort.
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How Can AI Be Used in Fitness Apps?
24 ways that AI can be used to improve activation, conversion, and retention in Fitness Apps. Build an AI Fitness Assistant with QuickPose.
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Fitness App Trends
From wearables to hyper-personalisation there are key trends in fitness in 2023, with some key predictions for 2024.
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Best Fitness Apps using AI in 2023
In today’s tech-driven world, even your fitness journey can be personalised and optimised with the help of Artificial Intelligence (AI). AI fitness apps are revolutionising the way we exercise, offering tailored workouts, real-time feedback, and progress tracking to help you achieve your fitness goals more efficiently. Here’s a look at some of the top…
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5 Reasons Why Real-Time Feedback Enhances User Experiences
Trigger alerts and voice commands from body position info.
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Example Use Cases of Pose Estimation in Fitness Apps
The Fitness App industry is on the rise, with an estimated revenue $19.55 Billion in 2023, with an average user spend of US$25.78. With over 71,000 fitness apps uploaded to the relevant app stores in 2021, competition seems to be fierce, but Dr.Muscle says they’re all the same- “Most Workout apps are as useful as…
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How Pose Estimation Can Validate Move-to-Earn
What is Move-to-Earn? Move-to-earn is a concept where users are rewarded with cash or other incentives for completing physical activities, such as walking, running, or biking. These apps use location data and fitness metrics from their device and wearables. Stepn, Sweat Economy and Green Satoshi token are amongst the biggest tokens on the market…
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