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.

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Restoring neuromuscular reflex properties in the control of a prosthetic hand may potentially approach humanlevel grasp functions in the prosthetic hand. Previous studies have confirmed the feasibility of real-time emulation of a monosynaptic spinal reflex loop for prosthetic control [1]. This study continues to explore how well the biomimetic controller could enable the amputee to perform force-control tasks that required both strength and error-tolerance. The biomimetic controller was programmed on a neuromorphic chip for real-time emulation of reflex. The model-calculated force of finger flexor was used to drive a torque motor, which pulled a tendon that flexed prosthetic fingers. Force control ability was evaluated in a "press-withoutbreak" task, which required participants to press a force transducer toward a target level, but never exceeding a breakage threshold. The same task was tested either with the index finger or the full hand; the performance of the biomimetic controller was compared to a proportional linear feedback (PLF) controller, and the contralateral normal hand. Data from finger pressing task in 5 amputees showed that the biomimetic controller and the PLF controller achieved 95.8% and 66.9% the performance of contralateral finger in success rate; 50.0% and 25.1% in stability of force control; 59.9% and 42.8% in information throughput; and 51.5% and 38.4% in completion time. The biomimetic controller outperformed the PLF controller in all performance indices. Similar trends were observed with full-hand grasp task. The biomimetic controller exhibited capacity and behavior closer to contralateral normal hand. Results suggest that incorporating neuromuscular reflex properties in the biomimetic controller may provide human-like capacity of force regulation, which may enhance motor performance of amputees operating a tendondriven prosthetic hand.

Convalescent plasma could be screened from healthy blood volunteers to establish blood banks and to prepare specific H-IVIG for treating severe ARIs caused by common respiratory viruses.

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