Effectiveness of different sensing modalities in predicting targets of reaching movements

Abstract

Abstract-Human motion recognition is essential for many biomedical applications, but few studies compare the abilities of multiple sensing modalities. This paper thus evaluates the effectiveness of different modalities when predicting targets of human reaching movements. Electroencephalography, electrooculography, camera-based eye tracking, electromyography, hand tracking and the user's preferences are used to make predictions at different points in time. Prediction accuracies are calculated based on data from 10 subjects in within-subject crossvalidation. Results show that electroencephalography can make predictions before limb motion onset, but its accuracy decreases as the number of potential targets increases. Electromyography and hand tracking give high accuracy, but only after motion onset. Eye tracking is robust and gives high accuracy at limb motion onset. Combining multiple modalities can increase accuracy, though not always. While many studies have evaluated individual sensing modalities, this study provides quantitative data on many modalities at different points of time in a single setting. The information could help biomedical engineers choose the most appropriate equipment for a particular application.

EMG-based decoding of grasp gestures in reaching-to-grasping motions

“…Additional works could be done to integrate to the robotic system tactile sensors for the attainment of a safe/stable grasp. Indeed, recent developments on the sensory field [38,39], showed that the design of compliant prosthesis should also include the sensory feedback to the user. This feedback could involve visual and tactile information in order to provide a compliant solution to the demands of the different conditions.…”