European Multicenter Study about Spinal Cord Injury (EM-SCI) Study GroupStudy design: Retrospective, longitudinal analysis of sensory, motor and functional outcomes from individuals with thoracic (T2-T12) sensorimotor complete spinal cord injury (SCI). Objectives: To characterize neurological changes over the first year after traumatic thoracic sensorimotor complete SCI. Methods: A dataset of 399 thoracic complete SCI subjects from the European Multi-center study about SCI (EMSCI) was examined for neurological level, sensory levels and sensory scores (pin-prick and light touch), lower extremity motor score (LEMS), ASIA Impairment Scale (AIS) grade, and Spinal Cord Independence Measure (SCIM) over the first year after SCI. Results: AIS grade conversions were limited. Sensory scores exhibited minimal mean change, but high variability in both rostral and caudal directions. Pin-prick and light touch sensory levels, as well as neurological level, exhibited minor changes (improvement or deterioration), but most subjects remained within one segment of their initial injury level after 1 year. Recovery of LEMS occurred predominantly in subjects with low thoracic SCI. The sensory zone of partial preservation (ZPP) had no prognostic value for subsequent recovery of sensory levels or LEMS. However, after mid or low thoracic SCI, X3 segments of sensory ZPP correlated with an increased likelihood for AIS grade conversion. Conclusion:The data suggest that a sustained deterioration of three or more thoracic sensory levels or loss of upper extremity motor function are rare events and may be useful for tracking the safety of a therapeutic intervention in early phase acute SCI clinical trials, if a significant proportion of study subjects exhibit such an ascent.

Study design: Multi-center pilot study. Objectives: To investigate the use of an upper limb robotic rehabilitation device (Armeo Spring, Hocoma AG, Switzerland) in a subacute cervical spinal cord injury (SCI) population. Setting: Two Canadian inpatient rehabilitation centers. Methods: Twelve subjects (motor level C4-C6, ASIA Impairment Scale A-D) completed the training, which consisted of 16.1 ± 4.6 sessions over 5.2±1.4 weeks. Two types of outcomes were recorded: (1) feasibility of incorporating the device into an inpatient rehabilitation program (compliance with training schedule, reduction in therapist time required and subject questionnaires) and (2) efficacy of the robotic rehabilitation for improving functional outcomes (Graded and Redefined Assessment of Strength, Sensibility and Prehension (GRASSP), action research arm test, grip dynamometry and range of motion). Results: By the end of the training period, the robot-assisted training was shown to require active therapist involvement for 25±11% (mean ± s.d.) of the total session time. In the group of all subjects and in a subgroup composed of motor-incomplete subjects, no statistically significant differences were found between intervention and control limbs for any of the outcome measures. In a subgroup of subjects with partial hand function at baseline, the GRASSP-Sensibility component showed a statistically significant increase (6.0 ± 1.6 (mean ± s.e.m.) point increase between baseline and discharge for the intervention limbs versus 1.9 ± 0.9 points for the control limbs). Conclusion:The pilot results suggest that individuals with some preserved hand function after SCI may be better candidates for rehabilitation training using the Armeo Spring device.

Upper limb robotic rehabilitation devices can collect quantitative data about the user's movements. Identifying relationships between robotic sensor data and manual clinical assessment scores would enable more precise tracking of the time course of recovery after injury and reduce the need for time-consuming manual assessments by skilled personnel. This study used measurements from robotic rehabilitation sessions to predict clinical scores in a traumatic cervical spinal cord injury (SCI) population. A retrospective analysis was conducted on data collected from subjects using the Armeo Spring (Hocoma, AG) in three rehabilitation centers. Fourteen predictive variables were explored, relating to range-of-motion, movement smoothness, and grip ability. Regression models using up to four predictors were developed to describe the following clinical scores: the GRASSP (consisting of four sub-scores), the ARAT, and the SCIM. The resulting adjusted R(2) value was highest for the GRASSP "Quantitative Prehension" component (0.78), and lowest for the GRASSP "Sensibility" component (0.54). In contrast to comparable studies in stroke survivors, movement smoothness was least beneficial for predicting clinical scores in SCI. Prediction of upper-limb clinical scores in SCI is feasible using measurements from a robotic rehabilitation device, without the need for dedicated assessment procedures.

A growing body of research suggests that non-invasive electrical brain stimulation can more effectively modulate neural activity when phase-locked to the underlying brain rhythms. Transcranial alternating current stimulation (tACS) can potentially stimulate the brain in-phase to its natural oscillations as recorded by electroencephalography (EEG), but matching these oscillations is a challenging problem due to the complex and time-varying nature of the EEG signals. Here we address this challenge by developing and testing a novel approach intended to deliver tACS phase-locked to the activity of the underlying brain region in real-time. This novel approach extracts phase and frequency from a segment of EEG, then forecasts the signal to control the stimulation. A careful tuning of the EEG segment length and prediction horizon is required and has been investigated here for different EEG frequency bands. The algorithm was tested on EEG data from 5 healthy volunteers. Algorithm performance was quantified in terms of phase-locking values across a variety of EEG frequency bands. Phase-locking performance was found to be consistent across individuals and recording locations. With current parameters, the algorithm performs best when tracking oscillations in the alpha band (8–13 Hz), with a phase-locking value of 0.77 ± 0.08. Performance was maximized when the frequency band of interest had a dominant frequency that was stable over time. The algorithm performs faster, and provides better phase-locked stimulation, compared to other recently published algorithms devised for this purpose. The algorithm is suitable for use in future studies of phase-locked tACS in preclinical and clinical applications.

In the past, neurorehabilitation for individuals with neurological damage, such as spinal cord injury (SCI), was focused on learning compensatory movements to regain function. Presently, the focus of neurorehabilitation has shifted to functional neurorecovery, or the restoration of function through repetitive movement training of the affected limbs. Technologies, such as robotic devices and electrical stimulation, are being developed to facilitate repetitive motor training; however, their implementation into mainstream clinical practice has not been realized. In this commentary, we examined how current SCI rehabilitation research aligns with the potential for clinical implementation. We completed an environmental scan of studies in progress that investigate a physical intervention promoting functional neurorecovery. We identified emerging interventions among the SCI population, and evaluated the strengths and gaps of the current direction of SCI rehabilitation research. Seventy-three study postings were retrieved through website and database searching. Study objectives, outcome measures, participant characteristics and the mode(s) of intervention being studied were extracted from the postings. The FAME (Feasibility, Appropriateness, Meaningfulness, Effectiveness, Economic Evidence) Framework was used to evaluate the strengths and gaps of the research with respect to likelihood of clinical implementation. Strengths included aspects of Feasibility, as the research was practical, aspects of Appropriateness as the research aligned with current scientific literature on motor learning, and Effectiveness, as all trials aimed to evaluate the effect of an intervention on a clinical outcome. Aspects of Feasibility were also identified as a gap; with two thirds of the studies examining emerging technologies, the likelihood of successful clinical implementation was questionable. As the interventions being studied may not align with the preferences of clinicians and priorities of patients, the Appropriateness of these interventions for the current health care environment was questioned. Meaningfulness and Economic Evidence were also identified as gaps since few studies included measures reflecting the perceptions of the participants or economic factors, respectively. The identified gaps will likely impede the clinical uptake of many of the interventions currently being studied. Future research may lessen these gaps through a staged approach to the consideration of the FAME elements as novel interventions and technologies are developed, evaluated and implemented.Electronic supplementary materialThe online version of this article (10.1186/s12984-018-0386-7) contains supplementary material, which is available to authorized users.

Background Current upper extremity outcome measures for persons with cervical spinal cord injury (cSCI) lack the ability to directly collect quantitative information in home and community environments. A wearable first-person (egocentric) camera system is presented that aims to monitor functional hand use outside of clinical settings. Methods The system is based on computer vision algorithms that detect the hand, segment the hand outline, distinguish the user’s left or right hand, and detect functional interactions of the hand with objects during activities of daily living. The algorithm was evaluated using egocentric video recordings from 9 participants with cSCI, obtained in a home simulation laboratory. The system produces a binary hand-object interaction decision for each video frame, based on features reflecting motion cues of the hand, hand shape and colour characteristics of the scene. Results The output from the algorithm was compared with a manual labelling of the video, yielding F1-scores of 0.74 ± 0.15 for the left hand and 0.73 ± 0.15 for the right hand. From the resulting frame-by-frame binary data, functional hand use measures were extracted: the amount of total interaction as a percentage of testing time, the average duration of interactions in seconds, and the number of interactions per hour. Moderate and significant correlations were found when comparing these output measures to the results of the manual labelling, with ρ = 0.40, 0.54 and 0.55 respectively. Conclusions These results demonstrate the potential of a wearable egocentric camera for capturing quantitative measures of hand use at home.

Egocentric vision (a.k.a. first-person vision -FPV) applications have thrived over the past few years, thanks to the availability of affordable wearable cameras and large annotated datasets. The position of the wearable camera (usually mounted on the head) allows recording exactly what the camera wearers have in front of them, in particular hands and manipulated objects. This intrinsic advantage enables the study of the hands from multiple perspectives: localizing hands and their parts within the images; understanding what actions and activities the hands are involved in; and developing human-computer interfaces that rely on hand gestures. In this survey, we review the literature that focuses on the hands using egocentric vision, categorizing the existing approaches into: localization (where are the hands or part of them?); interpretation (what are the hands doing?); and application (e.g., systems that used egocentric hand cues for solving a specific problem). Moreover, a list of the most prominent datasets with hand-based annotations is provided.

Background/objectives: In order to guide and improve rehabilitation interventions for grip function after spinal cord injury (SCI), it is important to have a detailed understanding of the motor control strategies that the central nervous system uses to control the hand. We examined whether changes in the motor control of the hand after SCI are manifested in the form of changes to muscle synergies. We further sought to determine a correlation between functional ability and the extent of muscle synergy disruption. Methods: Surface electromyographic (EMG) data were recorded from 8 hand muscles in 10 able-bodied subjects and 6 subjects with SCI as they performed various functional tasks using grip types relevant to activities of daily living. Muscle synergies were extracted using non-negative matrix factorization. Functional performance in each task was quantified using a 5-point clinical scale. Results: The synergies most commonly observed in able-bodied subjects were co-activation of extensor digitorum communis and extensor indicis proprius, as well as of flexor digitorum superficialis with flexor carpi ulnaris. The proportion of subjects in which particular synergies occurred was significantly different for subjects with SCI compared to able-bodied subjects (P < 0.001). Deviations from the average able-bodied synergies in subject with SCI were found to be poorly correlated (r = −0.04) with functional ability. Conclusions: Results suggest that the disruptions and re-organizations of neural circuitry after SCI are reflected by the extracted muscle synergies, but the question of how muscle synergies can guide rehabilitation interventions remains open.