Abstract
There has been an urgent need for a ubiquitous and quantitative upper limb rehabilitation method for post-stroke patients. This paper presents a real-time micro-sensor-based upper limb rehabilitation system for quantitatively evaluating the patient function status and the rehabilitation training progress. The rehabilitation system mainly consists of three subsystems: a sensor subsystem, a data fusion subsystem, and a rehabilitation training subsystem. The sensor subsystem collects upper limb motion signals and transfers them to the data fusion subsystem. The data fusion subsystem fuses motion signals to obtain motion parameters. The rehabilitation training subsystem visualizes the whole rehabilitation training process in 3D virtual space, visually guiding the patient in the training, highlighting the progress and existing issues. The system can provide rehabilitation ubiquitously, reduce the cost, and bring convenience to patients and families.