The ArmAssist is a simple low-cost robotic system for upper limb motor training that combines known benefits of repetitive task-oriented training, greater intensity of practice, and less dependence on therapist assistance. The aim of this preliminary study was to compare the efficacy of ArmAssist (AA) robotic training against matched conventional arm training in subacute stroke subjects with moderate-to-severe upper limb impairment. Twenty-six subjects were enrolled within 3 months of stroke and randomly assigned to the AA group or Control group (n = 13 each). Both groups were trained 5 days per week for 3 weeks. The primary outcome measure was Fugl-Meyer Assessment-Upper Extremity (FMA-UE) motor score, and the secondary outcomes were Wolf Motor Function Test-Functional Ability Scale (WMFT-FAS) and Barthel index (BI). The AA group, in comparison to the Control group, showed significantly greater increases in FMA-UE score (18.0 ± 9.4 versus 7.5 ± 5.5, p = 0.002) and WMFT-FAS score (14.1 ± 7.9 versus 6.7 ± 7.8, p = 0.025) after 3 weeks of treatment, whereas the increase in BI was not significant (21.2 ± 24.8 versus 13.1 ± 10.7, p = 0.292). There were no adverse events. We conclude that arm training using the AA robotic device is safe and able to reduce motor deficits more effectively than matched conventional arm training in subacute phase of stroke. The study has been registered at the ClinicalTrials.gov, ID: NCT02729649.

BackgroundFunctional electrical stimulation (FES) can be applied as an assistive and therapeutic aid in the rehabilitation of foot drop. Transcutaneous multi-pad electrodes can increase the selectivity of stimulation; however, shaping the stimulation electrode becomes increasingly complex with an increasing number of possible stimulation sites. We described and tested a novel decision support system (DSS) to facilitate the process of multi-pad stimulation electrode shaping. The DSS is part of a system for drop foot treatment that comprises a custom-designed multi-pad electrode, an electrical stimulator, and an inertial measurement unit.MethodsThe system was tested in ten stroke survivors (3–96 months post stroke) with foot drop over 20 daily sessions. The DSS output suggested stimulation pads and parameters based on muscle twitch responses to short stimulus trains. The DSS ranked combinations of pads and current amplitudes based on a novel measurement of the quality of the induced movement and classified them based on the movement direction (dorsiflexion, plantar flexion, eversion and inversion) of the paretic foot. The efficacy of the DSS in providing satisfactory pad-current amplitude choices for shaping the stimulation electrode was evaluated by trained clinicians. The range of paretic foot motion was used as a quality indicator for the chosen patterns.ResultsThe results suggest that the DSS output was highly effective in creating optimized FES patterns. The position and number of pads included showed pronounced inter-patient and inter-session variability; however, zones for inducing dorsiflexion and plantar flexion within the multi-pad electrode were clearly separated. The range of motion achieved with FES was significantly greater than the corresponding active range of motion (p < 0.05) during the first three weeks of therapy.ConclusionsThe proposed DSS in combination with a custom multi-pad electrode design covering the branches of peroneal and tibial nerves proved to be an effective tool for producing both the dorsiflexion and plantar flexion of a paretic foot. The results support the use of multi-pad electrode technology in combination with automatic electrode shaping algorithms for the rehabilitation of foot drop.Trial registrationThis study was registered at the Current Controlled Trials website with ClinicalTrials.gov ID NCT02729636 on March 29, 2016.

The goal of this study was to investigate surface motor activation zones and their temporal variability using an advanced multi-pad functional electrical stimulation system. With this system motor responses are elicited through concurrent activation of electrode matrix pads collectively termed "virtual electrodes" (VEs) with appropriate stimulation parameters. We observed VEs used to produce selective wrist, finger, and thumb extension movements in 20 therapy sessions of 12 hemiplegic stroke patients. The VEs which produce these three selective movements were created manually on the ergonomic multi-pad electrode by experienced clinicians based on visual inspection of the muscle responses. Individual results indicated that changes in VE configuration were required each session for all patients and that overlap in joint movements was evident between some VEs. However, by analyzing group data, we defined the probability distribution over the electrode surface for the three VEs of interest. Furthermore, through Bayesian logic we obtained preferred stimulation zones that are in accordance with our previously reported heuristically obtained results. We have also analyzed the number of active pads and stimulation amplitudes for these three VEs. Presented results provide a basis for an automated electrode calibration algorithm built on a priori knowledge or the starting point for manual selection of stimulation points.

The findings suggest that novel FES therapy combined with conventional rehabilitation is more effective on walking speed, mobility of the lower extremity, balance disability and activities of daily living compared to a conventional rehabilitation program only.

The purpose of this study was to examine surface motor activation zones for wrist, fingers and thumb extension movements and their temporal change during 20 therapy sessions using advanced multi-pad functional electrical stimulation system. Results from four hemiplegic patients indicate that certain zones have higher probability of eliciting each of the target movements. However, mutual overlap and variations of the zones are present not just between the subjects, but also on the intrasubject level, reflected through these session to session transformations of the selected virtual electrodes. The obtained results could be used as a priori knowledge for semi-automated optimization algorithm and could shorten the time required for calibration of the multi-pad electrode.

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