Fig. 2

Acquiring and encoding proprioceptive info for sensorimotor integration in prosthetics. 1. The actuator of the prosthesis operates the end effector based on the uptaken biologic signals of the user (e.g., EMG activity through surface electrode in case of myoelectric devices); 2. Sensors embedded in the prosthesis extract the configuration and power developed by the device (e.g., the joint angle is uptaken by the rotary encoders, pressure by superficial sensors and the force exerted is derived from the current adsorbed by the motors), also accordingly with the interaction with the environment (e.g., the cup grasped); 3. Data acquired from the sensors, which refer to proprioceptive-like parameters characterizing the state of the device are translated into feedback content to be delivered to the user; 4a. The feedback content is encoded back into input signals for the stimulators, on the basis of the amount of information to be transmitted, as well as the hardware’s capacities; 4b. The prosthesis, if implemented, can automatically modify (reflex-like behavior) the motor output based on the uptaken data; 5. The stimulators integrated into the device socket deliver the information to the sensory channels available in the stump or elsewhere (e.g., skin-stretch and electrotactile stimuli to skin mechanoceptors and nerve free endings respectively); 6. Once learnt how to interpret the flow of afferent information, the user is able to infer size, shape and stiffness of the object held by combining, for example, the information relative to prosthetic hand aperture and force developed; 7. Such information can be used consciously or unconsciously to correct the new motor command (e.g., increase muscle contraction) without constantly looking at the device, thus freeing attentional resources