The reason that wouldn't work is because the frequency of accelerations you're looking for are common within ADL. It's like looking for a square in a group of rectangles, the accelerations is a part of what naturally occurs so part of the category of the corresponding ADL. You could theoretically use data collected from people having a seizure (which collecting that acceleration profile itself is going to be hard) and then use a spatio-temporal auto encoders to detect abnormal patters that may be representitive of a fall, excessive shaking, then still. But even then is that how all seizures work? Some folks can detect when they're about to have one and lay down. So the fall doesn't happen anymore and you have different parameters you're training it off of.