IMU based activity detection for post mini-stroke healthcare

Based on an IMU motion sensitive device, an activity detection system has preliminarily developed for the use of post mini-stroke healthcare. The electronically assistive device seeks a solution to identify specifically different motions of the post stroke patients. The development causally regards to a machine learning skill. To manage the input compatibility to the learning machine, a preprocessor of discrete action pattern length equalizer has thus been requested. The study introduces two types of the length equalizer to embed with the post ANN classifier to carry out the machine learning for the activity detection. By a general comparative evaluation, the study evidentially analyzed and ensured an excellently combinational devise for the detector with an empirical cross-validation procedure.