Research Fellow & Group Leader
OSMR Career Development Fellow
Conjoint Lecturer, School of Medical Sciences, UNSW
+612 9399 1074
Penelope McNulty (PhD) graduated from UNSW in 2001. After working at the University of Rochester, NY, USA on a Schmitt Fellowship she moved to the Sydney University during the first years of a NHMRC post-doctoral fellowship, before returning to NeuRA in 2007.
She studies human neurophysiology of the sensory and motor systems in healthy subjects and those with stroke and spinal cord injury including recording from single sensory receptors and stimulating single motor units. Current studies include investigations of a novel rehabilitation tool after stroke using Wii therapy, and how this changes the way the brain controls force during voluntary movement after stroke and with healthy ageing.
Successful rehabilitation after stroke is limited by many factors including trained personnel, equipment, time and money.
Every year more than 60,000 Australians suffer a stroke and this number will only increase with the aging population the growing epidemics of obesity, physical inactivity and diabetes.
We know that the ability to detect contact with the skin changes with age. These changes might occur in the sensory receptors that lie in the skin, in the nerves that transmit sensory signals from the receptors to the brain, in the processing of sensory signals in the brain, or in the properties of the skin itself.
Measuring how well people can drive their muscle to produce maximum forces tells us a lot about the voluntary control of movement. We know that muscle strength decreases as people get older, particularly after the age of 70. Despite the loss of strength, the ability to drive muscles in maximum efforts does not deteriorate with age.
Very little is known about the way in which the body controls voluntary movement changes after stroke, or which neurophysiological structures cause such changes.
There are 350-400 new cases of spinal cord injury in Australia every year. These injuries cause sudden and devastating changes in patients’ ability to live independently. Surveys have shown that people living with a spinal cord injury list improved hand control second only to bladder and bowel control.
Skin sensation, or the ability to detect contact on the skin, declines with age. Manual dexterity and fine motor control of the hand also decline with age.
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.