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Being a weightlifter for 20+ years now, I'm working on a barbell speed and path tracking sensor based on newer IMU hardware technologies, which makes it both more precise and cheaper than camera- or actuator-based systems. Ultimately it helps you lift and train safer and better.
It's an intersection of industrial design, hardware, firmware, and software (and some sport science, of course). This intersection is not yet dominated by LLMs so it's a breath of fresh air.
In an early prototype stage as in "strap a Raspberry Pi to a bar", but it looks promising and I'm happy to move forward, also using connections from my previous 12+ years in China.
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Wannabe powerlifter here of about 20 years as well. This sounds like an awesome project! Is bar-path the main metric for safety and "better" lifting? A project I had in mind, once upon a time, was an automatic "Form Check Friday" for myself using a Pi + Webcam.
i'm curious about how effective path tracking can be in comparison with computer vision based inverse kinematics of the body itself. do all forms of bad form have detectable imu signatures?
i wonder if it would make sense to consider it as a data problem, capture a bunch of high fidelity inverse kinematics data for various forms of bad form/dangerous lifting along with the imu data and then work from there. there could be some interesting and unexpected features that are easier to detect than straying from straight line paths with some tolerance.
Side note: My LG Watch Sport smartwatch was able to determine what weight training workout I was performing and somehow figured the weight with astonishing accuracy.