 muscle groups stimulated. The second is the parameters of the stimulating current, that is, amplitude, pulse width, and frequency. The third is the timing of the stimulating signal sent to the individual muscles.
FES cycling is usually applied on several lower limb muscles simultaneously [43]. The main muscle groups considered are the hamstrings and quadriceps and, in some cases, the gluteus maximus. The quadriceps are stimulated either as a whole, that is, using only one pair of electrodes, or more selectively, in which three muscles composing them-that is, the vastus medialis, vastus lateralis, and rectus femoris-are stimulated individually. This more selective stimulation has demonstrated, in a recent pilot study, to improve up to 27% the power output in one patient with spastic muscles [44]. In this case, while the total stimulation current (the sum of the amplitude of currents applied in all of the channels) was higher, lower stimulation current amplitudes per muscle groups were sufficient to generate the required movement. The average current amplitude applied in FES cycling in SCI individuals is around 50-70 mA per muscles and it varies in a wide range. In some protocols, the current amplitude is increased until 120-140 mA to achieve power output around 10 W [45] and in extreme cases 20 W [46]. Others stimulated muscles with a frequency of 30 Hz, current amplitude of 70-90 mA, and pulse width of 500 μs, reaching a power output around 30 W [47]. The timing of stimulation is usually set according to recorded and processed muscle activities of able-bodied persons and/or on physiological, biomechanical parameters of the muscles and limbs of the participants. Nevertheless, these approaches are either not adaptive to the patientspecific musculoskeletal conditions, or very difficult to calibrate. For instance, when applying selective stimulation of the three quadriceps muscles separately [44], we found that the participant, even reaching higher power output, preferred to cycle for a shorter time, possibly due to a nonphysiological stimulation strategy. In our opinion, more studies are needed to explore these control combinations, in particular considering the case of selective stimulation. This will likely lead to new more efficient, natural, and adaptable stimulation protocols.
Cadence is another important variable in FES-cycling rehabilitation. In the case of ergometer-based training, cadence is on average set to 45-50 rpm, in most of the stimulating conditions. To adapt the treatment to patient residual motor ability, cadence can be changed in combination with various crank resistances during the rehabilitation process. Tricycles have been proposed as an alternative to stationary cycle ergometers [48]. A recent study reported that the series of FES trainings on a tricycle resulted in increased speed of cycling of paraplegics with denervated muscles [49], which is normally not observed in similar ergometer-based protocols. FES-driven tricycling is gaining relevance, as testified by several competitions organized during the last couple of years [50][51][52][53]. However, these competitions are only targeting people with SCI. We expect that wider range of participants, for example, stroke, will also be addressed in the near future, as supported by recent promising research works in this direction [54,55].

Exoskeletons and hybrid exoskeletons
Repetitive and intensive task-specific training drives beneficial neuroplasticity, thus enhancing functional recovery [56]. Therefore, exoskeletons for motor rehabilitation purposes have emerged in the last decade as a convenient technology that allow multiple, intensive, and more effective sessions of gait training, allowing SCI patients to ameliorate their performance in daily life [56]. Moreover, a study reported that spasticity and pain intensity of SCI patients decreased after one single session of walking assisted by a powered robotic exoskeleton [56].
A paradigmatic development of a stationary rehabilitation robot for gait training is the Lokomat system, which combines body-weight supported treadmill-training (BWSTT) with the assistance of a robotic gait orthosis. These robotic systems are able to provide guidance forces to the lower limb segments to induce a consisting stepping pattern with adjustable guidance. It has been shown that although the mechanical coupling and added guidance may change the task constraints and in turn alter voluntary leg movements, the basic neuromuscular pattern is preserved when intact humans walk assisted by this robot [57]. Robot-assisted gait training with the Lokomat after SCI has been shown in some studies to improve outcomes related to mobility when compared to conventional overground training [58,59]. For example, it was shown improved gait distance, strength, and functional level of mobility and independence of acute SCI patients receiving robotic-assisted gait training than the group of patients receiving conventional overground training [60]. Also, it has been demonstrated that robot-assisted gait training combined with conventional physiotherapy could yield more improvement in ambulatory function of SCI patients than conventional therapy alone. However, the impact of such complementary tools to provide neuromuscular education is still not well established for a convincing penetration of these systems in the clinical rehabilitation environments. Some limitations of such stationary robotic tools are that robotic-assisted training can be limited in the range of gait speed at which the exoskeleton robot can provide a comfortable gait pattern. Also, the stationary machine imposes restrictions to the user movements to the sagittal plane, significantly preventing motion in the frontal and transversal plane that are required for overground walking.
Wearable robots (WR) for overground untethered assisted walking are emerging devices that have the potential to overcome some of the above-mentioned constraints and opening a range of clinical application scenarios. Through wearable mechanical actuation and sensing, WRs are proliferating for their use as assistive and rehabilitation technologies due to their ability to replicate the complex motions involved in human movement. As a result, the past few decades have seen an increasing amount of research focused on developing robotic systems intended to interact with the neurologically impaired human body. This interaction (of the human body) with WRs has been established in foundational literature [61] as dual, bidirectional physical (pHRi), and cognitive (cHRi) interactions. While these systems have been proven to be useful for specific applications, such as in-clinic rehabilitation, current research in the area of pHRi for WRs is focusing more on developing lightweight and flexible force interactions with hardware solutions that might be more suitable to a broader range of applications (by adding compliance to rigid exoskeletons [62,63] or developing "soft exosuits" [64]). However, these soft exoskeletons are in early stage and the majority of clinical evidence of their efficacy for treatment of SCI is in studies with motorized powered exoskeletons. A systematic review of the literature on powered WRs for overground gait rehabilitation pointed out that, although current technology is still under development, and hence its ultimate impact remains still unclear, a number of revised studies report positive changes in outcome variables and suggest that training time and improvements in gait speed using powered WRs are correlated in SCI population [65].
On the cHRi side, efforts are focused on developing means for interpretation of mechanical and neural signals to establish adequate control methods that integrate WRs as parts of human functioning. In this regard, a scheme for "symbiotic interaction" between humans and WRs has been recently developed in the FET Project BioMot (FP7-ICT-2013-10-611695), yielding new technologies to interface human neuromechanics with robot-control algorithms to guide assistance; the point of increasing their proficiency is to make them more capable of sophisticated interdependent joint activity with the human wearer. Under this approach, a tacit adaptability is provided to modulate the compliance in the robot torque controller, to automatically modulate in turn the difficulty of the task [66].
There is currently no agreement on the optimal robot-mediated treatment programs to induce plasticity and promote recovery of motor function following SCI, and the understanding of recovery mechanisms is still an open matter [67]. Whatever the robot hardware and patient's functional status, a WR-mediated neurorehabilitation model could pave the way for effective restoration of mobility after major neurological conditions. In the last few years, the development of computational neurorehabilitation models is becoming a relevant topic in the domain of neural repair, as these computational models can be expected to provide the basis for future clinical robot software that suggests timing, dosage, and content of therapy. For example, an analytical modeling approach has been applied to robot-mediated rehabilitation data of a group of SCI subjects, providing insights with regard to patient grouping and gait recovery prognosis and also providing predictive quantitative measures to consider before starting the treatment [68]. This, together with the fact that in the past years we are witnessing an unprecedented number of wearable interactive robotics products that will populate even more the clinic environments, a reasonable long-term vision is to gather multicenter clinical data to equip rehabilitation WRs with computational neurorehabilitation modeling tools that will in turn provide enriched data to establish scientific bases of exoskeleton-guided recovery.
On the other hand, the combination of FES with external orthotic devices that provide joint support and mechanical constraint to undesired movements was early proposed [69], but the challenges associated with the rapid onset of muscle fatigue and movement control still remained. In an attempt to further diminish the energy demand from the muscle while providing better joint control, FES systems were combined with lower limb exoskeletons, also called hybrid exoskeletons [70]. The combination of the lower limb robotic exoskeleton and the FES system can be shaped in different ways, depending on the configuration of the FES system and/or the exoskeleton. Regarding the former, the FES can be implanted [71] or superficial [72] and can be found either under open [71,73] or closed-loop [72,74] control of stimulation. With regards to the exoskeleton joints, it can provide means of