Transcutaneous functional electrical stimulation (FES) is a method used for rehabilitation of patients having suffered a stroke or spinal cord injury. When applying FES a common problem is that stimulation electrodes have to be placed with great care in order to avoid activation of muscles close to the target muscles. A promising approach to circumvent this problem is to employ multipad FES, i.e. to employ electrode arrays containing many small electrodes allowing selective activation of muscles. In this work an algorithm is presented which automatically determines subsets of active electrodes and stimulation currents such that movements with user-specified amplitudes are induced. Using a recently developed portable multipad FES system and a virtual reality dataglove, the algorithm was tested with seven able-bodied subjects. Stimulation with parameters determined by the algorithm led to movements with a median deviation of between 0° and 5° from the specified wrist angle and between 0% and 12% from the specified degree of finger flexion.
Abstract. Camera-based eye-and gaze tracking systems have a wide range of application areas including cognitive science, biometrics, usability studies and Assistive Technology. Although the accuracy of remote eye trackers improved considerably in recent years, it is still impractical to use eye tracking systems for cursor control because of jitter and inaccurate positioning. This work presents a novel approach for online offset correction of the estimated gaze point, so that state-of-the art, affordable remote eye tracking devices can be used for cursor control in desktop applications without special GUI adaption. For gaze point correction, additional sensor systems or input devices can be combined with the eye tracking device. In evaluations with test users it could be shown that the hit rate of small targets presented at random screen locations could be increased from 54% to 89% which significantly improved the usability of gaze tracking based mouse cursor control.
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