Relaying the High Frequency Contents of Tactile Feedback to Robotic Prosthesis Users: Design, Filtering, Implementation and Validation

It is known that high frequency tactile information conveys useful cues to discriminate important contact properties for manipulation, such as first-contact and roughness. Despite this, no practical system, implementing a Modality Matching paradigm, has been developed so far to convey this information to users of upper-limb prostheses. The main obstacle to this implementation is the presence of unwanted vibrations generated by the artificial limb mechanics, which are not related to any haptic exploration task. In this work, we describe the design of a digital system which can record accelerations from the fingers of an artificial hand, and reproduce them on the user’s skin through voice-coil actuators. Particular attention has been devoted to the design of the filter, needed to cancel all those vibrations measured by the sensors that do not convey information on meaningful contact events. The performance of the newly designed filter is also compared with the state of the art. Exploratory experiments with prosthesis users have identified some applications where this kind of feedback could lead to sensory-motor performance enhancement. Results show that the proposed system improves the perception of object-salient features such as first-contact events, roughness and shape.