The wearable system based on the multi-sensor fusion for recognizing stroke patients' upper limb motion auto matically

To study a wearable system based on the multi-sensor fusion for recognizing stroke patients' upper limb motion automatically.Method: A wearable system was proposed based on multi-sensor fusion for recognizing stroke patients' upper limb limb motion automatically. The hardware of the system was made up of a master node and three salve nodes. The master node consists of a WIFI module and a microprocessor, and the slave node was made up with a highly sensitive three- axis accelerometer and a microprocessor. Accelerometer signals were collected by the slave node, then transmitted to the master node, after that, transmitted to the computer through the WIFI.This hardware system had characteristics of the low power consumption, miniaturization, expansibility and so on. The algorithm for motion classification based on Adaboost was realized in the software of this system,which would recognize three different motions automatically through analyzing the received acceleration signals of upper limb motion.Result: Three different motion of upper limb could be recognized automatically by the system, the accuracy of motion recognition was up to 97.99%.Conclusion: The wearable system has great value in rehabilitation assessment of upper limb motion for stroke patients.