Recent studies suggest that the therapeutic effects of Functional Electrical Stimulation (FES) are maximized when the patterned electrical stimulation is delivered in close synchrony with the attempted voluntary movement. FES systems that modulate stimulation parameters based on the residual volitional muscle activity would assure this combination. However, the development of such a system might be not trivial, both from a hardware and a software point of view. This chapter provides an extensive overview of devices and filtering solutions proposed in the literature to estimate the residual volitional EMG signal in the presence of electrical stimulation. Different control strategies to modulate FES parameters as well as the results of the first studies involving neurological patients are also presented. This chapter provides some guidelines to help people who want to design innovative myocontrolled neuroprostheses and might favor the spread of these solutions in clinical environments.
TopIntroduction
Functional Electrical Stimulation (FES) consists of the electrical stimulation of an intact lower motor neuron to activate paralyzed or paretic muscles in a precise sequence so as to directly accomplish or support functional tasks (Meo & Post, 1962). Functional tasks may include standing, walking, or cycling, upper limb activities, such as grasping or reaching, and control of respiration and bladder function. With the term neuroprosthesis we refer to a system or a device that provides FES. FES systems have been covering a wide range of assistive and therapeutic applications in neuro-rehabilitation for the last forty years (Sheffler & Chae, 2007); they have been used to restore or replace impaired or lost motor functions in people affected by many neurological disorders, such as Spinal Cord Injury (SCI) (Gater, 2011), stroke (Ambrosini, 2012; Ambrosini, 2011a; Ferrante, 2008; Pomeroy, 2006; Popović, 2009), multiple sclerosis (Barrett, 2009), or cerebral palsy (Cauraugh, 2010; Trevisi, 2011).
When the muscles are not completely paralyzed it is possible to use the neural information extracted from the EMG signals of the paretic limb to control the timing and the intensity of the stimulation (Jiang, 2010). Such a control scheme seems to be a promising solution from a clinical prospective since it involves the physiological neural pathway in the recovery of the impaired motor functions. In support of this hypothesis, recent neurophysiological studies (Barsi, 2008; Iftime-Nielsen, 2012; Rushton, 2003; Gandolla, 2012) suggested that the use of electrical stimulation co-incidentally with the voluntary drive enhances the plasticity of the central nervous system (CNS), so as to improve motor relearning. First evidences about the efficacy of myocontrolled FES in improving upper limb motor performance have been shown in post-stroke patients (Fujiwara et al., 2009; Shindo et al., 2011). However, a full demonstration of the superiority of this approach compared to a more conventional use of FES is still missing, as well as a system ready to be transferred in clinical settings.