To Be Sensor Fusion or No To Be Sensor Fusion, and some ideas?

Hello Everyone, I'm currently using a single MetaMotionS on the wrist to track workout exercises i.e. squats. I'm still in the infant stages of understanding math and data. So I was looking for some inspiration or ideas that would perhaps help me. As of now, I simply collect Accelerometer data, use a low pass filter, and then interpret the data. My goal is to accurately calculate how many calories a person loses when doing a certain exercise and there's math behind that as well. But, in regards to the sensor, is it best that I use Sensor Fusion modes? If so which would you recommend? To note, the tutorials stated that the sensor fusion algorithms were designed for tracking human movement... I would love any other ideas or suggestions. Thank you so much!

Comments

  • For our MetaRom we use quaternions.

  • Okay bet Laura, haha! I'll have to do some more research and understand quaternions but thanks for your feedback and involvement in the community!

  • quaternions are the easiest to work with mathematically but they are not "human readable" so you always have to convert them to euler at the very end. You can do more research on this online as you mentioned.

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