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Remarkable compliance of human hands due to muscular biomechanics and neural reflexes, attributes lacking in conventional prosthetic hands. Our prior study replicated neuromuscular reflex in prosthetic control using neuromorphic modeling. Nonetheless, the specific impact of the spinal reflex feedback in biomimetic control on amputees' manipulation capabilities remains unclear. This study aims to investigate the plausible role of reflex regulation in biomimetic control for tendon-driven prosthetic hands. Eleven subjects with forearm amputations participated in force control tasks and functional tasks. The force control tasks were performed using either the prosthetic forefinger or the entire hand. The functional tasks of varying difficulties included the standard rigid object test (SROT), refined rigid object test (RROT), and fragile object test (FOT). Additionally, the stiffness properties of biomimetic control were tested prior to the human-in-loop evaluations. Closed-loop control (CLC) with integrated proprioceptive feedback and open-loop control (OLC) were employed for assessments. Results showed that the reflex regulation contributed significantly to the increase by 20.4% in success rate, 17.9% in effective throughput, and 65.7% decrease in break rate during in the pressing force control task. CLC consistently outperformed OLC across all indices. Indeed, the gripping force control task revealed comparable trends as well. In functional tasks, the reflex regulation yielded 10.5%, 17.9%, and 146.4% improvements in performance for SROT, RROT and FOT, respectively. The findings highlight the essential role of reflex regulation in biomimetic prosthesis control, providing evidence for enhancing amputees' fine manipulation abilities by replicating the human sensorimotor functions. [ABSTRACT FROM AUTHOR]

Current control of prosthetic hands is ineffective when grasping deformable, irregular, or heavy objects. In humans, grasping is achieved under spinal reflexive control of the musculotendon skeletal structure, which produces a hand stiffness commensurate with the task. We hypothesize that mimicking reflex on a prosthetic hand may improve grasping performance and safety when interacting with human. Here, we present a design of compliant controller for prosthetic hand with a neuromorphic model of human reflex. The model includes 6 motoneuron pools containing 768 spiking neurons, 1 muscle spindle with 128 spiking afferents, and 1 modified Hill-type muscle. Models are implemented using neuromorphic hardware with 1 kHz real-time computing. Experimental tests showed that the prosthetic hand could sustain a 40 N load compared to 95 N for an adult. Stiffness range was adjustable from 60 to 640 N/m, about 46.6% of that of human hand. The grasping velocity could be ramped up to 14.4 cm/s, or 24% of the human peak velocity. The complaint control could switch between free movement and contact force when pressing a deformable beam. The amputee can achieve a 47% information throughput of healthy humans. Overall, the reflex-enabled prosthetic hand demonstrated the attributes of human compliant grasping with the neuromorphic model of spinal neuromuscular reflex. [ABSTRACT FROM AUTHOR]