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Arm Sensor
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Base Station
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Inspiration
Improper form is one of the largest issues in sports and can cause numerous preventable injuries. Weightlifting carries a significant risk of injury with improper form especially for exercises like the bench press, deadlifts, and squats.
What it does
Our product takes accelerometer and camera data, feeds it to a ML model and analyzes your exercise habits, offering helpful insight and feedback to improve future workouts.
How we built it
The Wearable: We used an ESP32 (the brain) and an MPU6050 (the motion sensor). The Base Station: We used the Arduino Uno Q, which we ran like a mini-computer to receive and process the data. The Connection: We linked them together using an iPhone hotspot so the system can work anywhere, like on a football field or in a gym. The Code: We wrote everything in C
Challenges we ran into
The biggest headache was definitely the Wi-Fi and connectivity.
Accomplishments that we're proud of
Managing to fit such a complex circuit into a small form factor. Being able to connect the ESP32 to the unoQ
What we learned
We learned about smart ai integration with arduino boards.
What's next for PerForm
Integration more sports, smaller form factor.
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