Recognizing Sports Exercises Using a Time of Flight Sensor and NanoEdge AI Studio

This project aims to recognize various sports movements, including squats, shoulder lifts, and arm stretches. It enables the programming of a microcontroller to count each exercise repetition.
The setup is based on a ST VL53L5CX Time-of-Flight sensor (8x8 LiDAR sensor), operates on an Arduino UNO R4 and utilizes NanoEdge AI Studio, a user-friendly platform for AI on microcontrollers, to log data, train the model, and test it. Additionally, it is compatible with any microcontroller that has an Arm Cortex-M architecture.
To get started with NanoEdge AI Studio visit: stm32ai.st.com...
And explore the ST Edge AI suite, a comprehensive set of tools, real-world case studies and educational resources for integrating artificial intelligence features in embedded systems, including STM32 microcontrollers and microprocessors, Stellar automotive microcontrollers, and MEMS smart sensors: st.com/st-edge-...
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[@ayoublouhabi2208]

great video Adnane 👏

[@IbtihalBoudraa]

Nice video ! This can be so helpful for ppl who struggle to count reps and sets at the gym !

[@shanghaiyongmingelectroniccolt]

This is very helpful for sports

[@med7214]

Proud of you Adnane

[@veoazul]

great video, thank you ST

[@kvin]

Man i would love to experiment with these !