I agree and disagree. I would definitely start with a simpler algorithm like logistic regression or even trees and use temporal features like power at different frequencies by taking an FFT. I would even add time lagged features. After that I'd graduate to a single hidden layer MLP.

If I had tons of data (a lot of different people using it), I'd experiment with LSTM neural networks because I think the temporal information is crucial for determining a movement.

I think a killer app would be aimed at weight lifters. If you go to the gym, the serious weight lifters record their reps and weight for each exercise. The app would utilize the iWatch or some other wearable and detect the exercise and count the reps. Then it would prompt the user for how much weight they used.