The intuitive control of upper
-
limb prostheses requires a man/machine interface that directly
exploits biological signals. Here, we define and experimentally test an offline man/machine interface
that takes advantage of the discharge timings of spinal moto
r neurons. The motor
-
neuron behaviour
is identified by deconvolution of the electrical activity of muscles reinnervated by nerves of a missing
limb in patients with amputation at the shoulder or humeral level. We mapped the series of motor
-
neuron discharge
s into control commands across multiple degrees of freedom via the offline
application of direct proportional control, pattern recognition and musculoskeletal modelling. A
series of experiments performed on six patients reveal that the man/machine interfac
e has superior
offline performance than conventional direct electromyographic control applied after targeted
muscle innervation. The combination of surgical procedures, decoding and mapping into effective
commands constitutes an interface with the output l
ayers of the spinal cord circuitry that allows for
the intuitive control of multiple degrees of freedom.