Comparison of different fuzzy models to extract position information from muscle afferent activity
The aim of this study was to investigate different fuzzy models for joint position prediction using the ElectroNeuroGram (ENG) signals recorded from muscle afferents using cuff electrodes. The Dynamic Non-Singleton Fuzzy Logic System (DNSFLS) model performed best, The good performance of this fuzzy model suggests it might be possible to use activity from muscle afferents recorded with cuff electrodes for Functional Electrical Stimulation (FES) closed-loop control of joint position.
We propose a method for moving object detection under a moving camera by the rank minimization approach. Moving object detection under the moving camera system is a challenging problem. Recent approaches are based on complex cascade step approaches. By utilizing the rank minimization framework, alignment and moving object detection are performed simultaneously. We validate efficiency and robustness of the proposed method by showing qualitative evaluations.