Investigation of Embodiment for Upper Limb Amputees

Description

Leveraging advancements in neural interfaces, biomechatronic devices, and myoelectric control algorithms, my research mission is to enable the embodiment of artificial devices by providing physiologically appropriate somatosensory feedback.

Specific Aim 1: How does the amount of embodiment vary among conventional prosthetic hands?.

Data from Specific Aim 1 will be used to test the following hypotheses: H1a. The body-powered prosthetic devices are embodied more than passive and myoelectric prosthetic devices. H1b. Passive cosmetic devices are embodied less than actuated cosmetic devices (agency). H1c. Body-powered terminal devices are embodied less than myoelectric terminal devices (agency).

Specific Aim 2: Design of Multi-Modal Sensors for Full Hand Sensation (No human subject experiments.) Specific Aim 3: What somatosensory percepts from the hand are most critical for embodiment? Data from Specific Aim 3 will be used to test the following hypotheses: H3a. The maximum number of channels elicits more embodiment than the minimum number. H3b. The sensory feedback from passive spatial locations of the hand increases the embodiment compared to sensory feedback just from the grasping spatial locations.