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Negin completed both a BSc and MSc in biomedical engineering at Amirkabir University of Technology (Tehran, Iran). During her BSc, she has modelled a MATLAB toolbox for simulating musculoskeletal systems. In her postgraduate research, she has designed electrical stimulation controllers to restore upper-limb motor function after spinal cord injury.
Negin completed her PhD at NeuRA in 2017, investigating the neurophysiological and kinematic changes underpinning the therapy-induced improvements of motor function in chronic stroke. She developed multiple quantitative approaches to analyse the complex and heterogeneous dataset of muscle activation and movement kinematics. In addition, she investigated the correlates and potential predictors of therapy-induced and longitudinal changes in chronic stroke in a multivariate model.
She has also been part of the UPWaRD project in 2018 at NeuRA, processing signals of brain activity to determine whether cortical reorganisation can predict low back pain outcome. Starting her new position as a postdoctoral researcher in 2019, she is now a part of the STOPain project. Her current work at NeuRA is focused on developing a Brain-Computer Interface for neuromodulation to reduce neuropathic pain in people with spinal cord injury. This approach is a novel intervention in which individuals will be trained to gain control over their brain activity using neurofeedback in a way that results in pain reduction.
NELL NORMAN-NOTT Honours Student Psychology
BROOKE NAYLOR Masters Student, Clinical Psychology
DANIEL HULTBERG Medical Student
ANTON PAULSON Medical Student
DAVID KANG Medical Student
Poststroke weakness on the more-affected side may arise from reduced corticospinal drive, disuse muscle atrophy, spasticity, and abnormal coordination. This study investigated changes in muscle activation patterns to understand therapy-induced improvements in motor-function in chronic stroke compared to clinical assessments and to identify the effect of motor-function level on muscle activation changes. Electromyography (EMG) was recorded from five upper limb muscles on the more-affected side of 24 patients during early and late therapy sessions of an intensive 14-day program of Wii-based Movement Therapy (WMT) and for a subset of 13 patients at 6-month follow-up. Patients were classified according to residual voluntary motor capacity with low, moderate, or high motor-function levels. The area under the curve was calculated from EMG amplitude and movement duration. Clinical assessments of upper limb motor-function pre- and post-therapy included the Wolf Motor Function Test, Fugl-Meyer Assessment and Motor Activity Log Quality of Movement scale. Clinical assessments improved over time (p < 0.01) with an effect of motor-function level (p < 0.001). The pattern of EMG change by late therapy was complex and variable, with differences between patients with low compared to moderate or high motor-function levels. The area under the curve (p = 0.028) and peak amplitude (p = 0.043) during Wii-tennis backhand increased for patients with low motor-function, whereas EMG decreased for patients with moderate and high motor-function levels. The reductions included movement duration during Wii-golf (p = 0.048, moderate; p = 0.026, high) and Wii-tennis backhand (p = 0.046, moderate; p = 0.023, high) and forehand (p = 0.009, high) and the area under the curve during Wii-golf (p = 0.018, moderate) and Wii-baseball (p = 0.036, moderate). For the pooled data over time, there was an effect of motor-function (p = 0.016) and an interaction between time and motor-function (p = 0.009) for Wii-golf movement duration. Wii-baseball movement duration decreased as a function of time (p = 0.022). There was an effect on Wii-tennis forehand duration for time (p = 0.002), an interaction of time and motor-function (p = 0.005) and an effect of motor-function level on the area under the curve (p = 0.034) for Wii-golf. This study demonstrated different patterns of EMG changes according to residual voluntary motor-function levels, despite heterogeneity within each level that was not evident following clinical assessments alone. Thus, rehabilitation efficacy might be underestimated by analyses of pooled data.
Fine motor control is achieved through the coordinated activation of groups of muscles, or "muscle synergies." Muscle synergies change after stroke as a consequence of the motor deficit. We investigated the pattern and longitudinal changes in upper limb muscle synergies during therapy in a largely unconstrained movement in patients with a broad spectrum of poststroke residual voluntary motor capacity. Electromyography (EMG) was recorded using wireless telemetry from 6 muscles acting on the more-affected upper body in 24 stroke patients at early and late therapy during formal Wii-based Movement Therapy (WMT) sessions, and in a subset of 13 patients at 6-month follow-up. Patients were classified with low, moderate, or high motor-function. The Wii-baseball swing was analyzed using a non-negative matrix factorization (NMF) algorithm to extract muscle synergies from EMG recordings based on the temporal activation of each synergy and the contribution of each muscle to a synergy. Motor-function was clinically assessed immediately pre- and post-therapy and at 6-month follow-up using the Wolf Motor Function Test, upper limb motor Fugl-Meyer Assessment, and Motor Activity Log Quality of Movement scale. Clinical assessments and game performance demonstrated improved motor-function for all patients at post-therapy (p < 0.01), and these improvements were sustained at 6-month follow-up (p > 0.05). NMF analysis revealed fewer muscle synergies (mean ± SE) for patients with low motor-function (3.38 ± 0.2) than those with high motor-function (4.00 ± 0.3) at early therapy (p = 0.036) with an association trend between the number of synergies and the level of motor-function. By late therapy, there was no significant change between groups, although there was a pattern of increase for those with low motor-function over time. The variability accounted for demonstrated differences with motor-function level (p < 0.05) but not time. Cluster analysis of the pooled synergies highlighted the therapy-induced change in muscle activation. Muscle synergies could be identified for all patients during therapy activities. These results show less complexity and more co-activation in the muscle activation for patients with low motor-function as a higher number of muscle synergies reflects greater movement complexity and task-related phasic muscle activation. The increased number of synergies and changes within synergies by late-therapy suggests improved motor control and movement quality with more distinct phases of movement.