The aim of this study was to review the literature about the effects of Activity-based therapy (ABT) interventions on mobility, functional independence and quality of life for people with a spinal cord injury (SCI). A systematic review with meta-analysis of randomised and non-randomised trials was performed, including adults with a non-progressive SCI at any level. The intervention of interest was ABT defined as any intervention that sought to improve muscle activation or sensory function below the level of injury in the spinal cord and does not rely on compensatory mechanisms for improving function. The comparison was either no intervention or conventional physical interventions targeted to regions above the level of injury. The outcome measures were Quality of life questionnaires; mobility and functional independence scales. Nineteen trials were included in this systematic review. Three compared ABT to no intervention and 16 to conventional physical rehabilitation. The methodological quality of the trials was assessed using the PEDro scale as moderate. Six studies investigated the effects of ABT interventions for the upper limbs, 11 investigated gait-related interventions and two applied multimodal interventions. When compared to no intervention, the meta-analysis found that ABT was not more effective for improving independence or lower limb mobility, and a large positive effect on upper limb function. When compared to conventional physical interventions, there was no significant effect of ABT on lower limb mobility, independence or quality of life, however it had positive effects on upper limbs. In conclusion, there is evidence that ABT can improve independence and functional ability when applied to the upper limbs in people with SCI. However, they are not superior to conventional physical interventions when applied to the lower limbs.

The evoked electromyographic signal (eEMG) potential is the standard index used to monitor both electrical changes within the motor unit during muscular activity and the electrical patterns during evoked contraction. However, technical and physiological limitations often preclude the acquisition and analysis of the signal especially during functional electrical stimulation (FES)-evoked contractions. Hence, an accurate quantification of the relationship between the eEMG potential and FES-evoked muscle response remains elusive and continues to attract the attention of researchers due to its potential application in the fields of biomechanics, muscle physiology, and rehabilitation science. We conducted a systematic review to examine the effectiveness of eEMG potentials to assess muscle force and fatigue, particularly as a biofeedback descriptor of FES-evoked contractions in individuals with spinal cord injury. At the outset, 2867 citations were identified and, finally, fifty-nine trials met the inclusion criteria. Four hypotheses were proposed and evaluated to inform this review. The results showed that eEMG is effective at quantifying muscle force and fatigue during isometric contraction, but may not be effective during dynamic contractions including cycling and stepping. Positive correlation of up to r = 0.90 (p < 0.05) between the decline in the peak-to-peak amplitude of the eEMG and the decline in the force output during fatiguing isometric contractions has been reported. In the available prediction models, the performance index of the eEMG signal to estimate the generated muscle force ranged from 3.8% to 34% for 18 s to 70 s ahead of the actual muscle force generation. The strength and inherent limitations of the eEMG signal to assess muscle force and fatigue were evident from our findings with implications in clinical management of spinal cord injury (SCI) population.

The difficulty of real-time muscle force or joint torque estimation during neuromuscular electrical stimulation (NMES) in physical therapy and exercise science has motivated recent research interest in torque estimation from other muscle characteristics. This study investigated the accuracy of a computational intelligence technique for estimating NMES-evoked knee extension torque based on the Mechanomyographic signals (MMG) of contracting muscles that were recorded from eight healthy males. Simulation of the knee torque was modelled via Support Vector Regression (SVR) due to its good generalization ability in related fields. Inputs to the proposed model were MMG amplitude characteristics, the level of electrical stimulation or contraction intensity, and knee angle. Gaussian kernel function, as well as its optimal parameters were identified with the best performance measure and were applied as the SVR kernel function to build an effective knee torque estimation model. To train and test the model, the data were partitioned into training (70%) and testing (30%) subsets, respectively. The SVR estimation accuracy, based on the coefficient of determination (R²) between the actual and the estimated torque values was up to 94% and 89% during the training and testing cases, with root mean square errors (RMSE) of 9.48 and 12.95, respectively. The knee torque estimations obtained using SVR modelling agreed well with the experimental data from an isokinetic dynamometer. These findings support the realization of a closed-loop NMES system for functional tasks using MMG as the feedback signal source and an SVR algorithm for joint torque estimation.

Introduction: Activity-based therapy (ABT) aims to activate the neuromuscular system below the level of the spinal cord lesion and promote recovery of motor tasks through spinal reorganisation, motor learning and changes to muscles and sensory system. We investigated the effects of a multimodal ABT program on mobility, independence and sitting balance in individuals with spinal cord injury (SCI). Methods: Retrospective clinical data from 91 adults who independently enrolled in four community-based ABT centres in Australia were analysed. The multimodal ABT program was delivered for 3 to 12 months, one to four times per week. Assessments were undertaken every 3 months and included the Modified Rivermead Mobility Index (MRMI), Spinal Cord Independence Measure (SCIM) and seated reach distance (SRD). A linear mixed model analysis was used to determine time-based and other predictors of change. Results: There was a significant improvement after 12 months for all outcome measures, with a mean change score of 4 points in the SCIM (95% confidence interval [CI]: 2.7-5.3, d = 0.19), 2 points in the MRMI (95% CI: 1-2.3, d = 0.19) and 0.2 in the SRD (95% CI: 0.1-2.2, d = 0.52). Greater improvements occurred in the first 3 months of intervention. There were no interaction effects between time and the neurological level of injury, American Spinal Injury Association Impairment Scale classification, or duration post-injury for most outcomes. Conclusions: A community-based ABT exercise program for people with SCI can lead to small improvements in mobility, independence and balance in sitting, with greater improvements occurring early during intervention.

Rehabilitation after spinal cord injury (SCI) has traditionally involved teaching compensatory strategies for identified impairments and deficits in order to improve functional independence. There is some evidence that regular and intensive activity-based therapies, directed at activation of the paralyzed extremities, promotes neurological improvement. The aim of this study is to compare the effects of a 12-week intensive activity-based therapy program for the whole body with a program of upper body exercise.