  One of the most frequent and severe aftermaths of a stroke is the loss of
upper limb functionality. Therapy started in the sub-acute phase proved more
effective, mainly when the patient participates actively. Recently, a novel set
of rehabilitation and support robotic devices, known as supernumerary robotic
limbs, have been introduced. This work investigates how a surface
electromyography (sEMG) based control strategy would improve their usability in
rehabilitation, limited so far by input interfaces requiring to subjects some
level of residual mobility. After briefly introducing the phenomena hindering
post-stroke sEMG and its use to control robotic hands, we describe a framework
to acquire and interpret muscle signals of the forearm extensors. We applied it
to drive a supernumerary robotic limb, the SoftHand-X, to provide Task-Specific
Training (TST) in patients with sub-acute stroke. We propose and describe two
algorithms to control the opening and closing of the robotic hand, with
different levels of user agency and therapist control. We experimentally tested
the feasibility of the proposed approach on four patients, followed by a
therapist, to check their ability to operate the hand. The promising
preliminary results indicate sEMG-based control as a viable solution to extend
TST to sub-acute post-stroke patients.
