Withdrawal Reflexes in the Upper Limb Adapt to Arm Posture and Stimulus Location By.

Withdrawal reflexes in the upper limb adapt to arm posture and stimulus location by.

Muscle Nerve. 2013 Aug 8;
Peterson CL, Riley Z, Krepkovich ET, Murray WM, Perreault EJ

Withdrawal reflexes in the leg adapt in a context appropriate manner to remove the limb from noxious stimuli, but the extent to which withdrawal reflexes adapt in the arm remains unknown.We examined the adaptability of withdrawal reflexes in response to nociceptive stimuli applied in different arm postures and to different digits. Reflexes were elicited at rest, and kinetic and EMG responses were recorded under isometric conditions, thereby allowing motorneuron pool excitability to be controlled.Endpoint force changed from a posterior-lateral direction in a flexed posture to predominantly a posterior direction in a more extended posture (change in force angle = 35.6 ± 5.0 degrees; mean ± standard deviation), and the force direction changed similarly with digit I stimulation compared to digit V (change = 22.9 ± 2.9 degrees).The withdrawal reflex in the human upper limb adapts in a functionally relevant manner when elicited at rest. © 2013 Wiley Periodicals, Inc. HubMed – rehab

Error Augmentation Enhancing Arm Recovery in Individuals With Chronic Stroke: A Randomized Crossover Design.

Neurorehabil Neural Repair. 2013 Aug 8;
Abdollahi F, Case Lazarro ED, Listenberger M, Kenyon RV, Kovic M, Bogey RA, Hedeker D, Jovanovic BD, Patton JL

. Neurorehabilitation studies suggest that manipulation of error signals during practice can stimulate improvement in coordination after stroke.. To test visual display and robotic technology that delivers augmented error signals during training, in participants with stroke.. A total of 26 participants with chronic hemiparesis were trained with haptic (via robot-rendered forces) and graphic (via a virtual environment) distortions to amplify upper-extremity (UE) tracking error. In a randomized crossover design, the intervention was compared with an equivalent amount of practice without error augmentation (EA). Interventions involved three 45-minute sessions per week for 2 weeks, then 1 week of no treatment, and then 2 additional weeks of the alternate treatment. A therapist provided a visual cursor using a tracking device, and participants were instructed to match it with their hand. Haptic and visual EA was used with blinding of participant, therapist, technician-operator, and evaluator. Clinical measures of impairment were obtained at the beginning and end of each 2-week treatment phase as well as at 1 week and at 45 days after the last treatment.. Outcomes showed a small, but significant benefit to EA training over simple repetitive practice, with a mean 2-week improvement in Fugl-Meyer UE motor score of 2.08 and Wolf Motor Function Test of timed tasks of 1.48 s.. This interactive technology may improve UE motor recovery of stroke-related hemiparesis. HubMed – rehab

Prognostic Factors for Return to Work, Sickness Benefits, and Transitions Between These States: A 4-year Follow-up After Work-Related Rehabilitation.

J Occup Rehabil. 2013 Aug 9;
Oyeflaten I, Lie SA, Ihlebæk CM, Eriksen HR

Purpose The aim of this study was to examine if age, gender, medical diagnosis, occupation, and previous sick leave predicted different probabilities for being at work and for registered sickness benefits, and differences in the transitions between any of these states, for individuals that had participated in an interdisciplinary work-related rehabilitation program. Methods 584 individuals on long-term sickness benefits (mean 9.3 months, SD = 3.4) were followed with official register data over a 4-year period after a rehabilitation program. 66 % were female, and mean age was 44 years (SD = 9.3). The majority had a mental (47 %) or a musculoskeletal (46 %) diagnosis. 7 % had other diagnoses. Proportional hazards regression models were used to analyze prognostic factors for the probability of being on, and the intensity of transitions between, any of the following seven states during follow-up; working, partial sick leave, full sick leave, medical rehabilitation, vocational rehabilitation, partial disability pension (DP), and full DP. Results In a fully adjusted model; women, those with diagnoses other than mental and musculoskeletal, blue-collar workers, and those with previous long-term sick leave, had a lower probability for being at work and a higher probability for full DP during follow-up. DP was also associated with high age. Mental diagnoses gave higher probability for being on full sick leave, but not for transitions to full sick leave. Regression models based on transition intensities showed that risk factors for entering a given state (work or receiving sickness benefits) were slightly different from risk factors for leaving the same state. Conclusions The probabilities for working and for receiving sickness benefits and DP were dependent on gender, diagnoses, type of work and previous history of sick leave, as expected. The use of novel statistical methods to analyze factors predicting transition intensities have improved our understanding of how the processes to and from work, and to and from sickness benefits may differ between groups. Further research is required to understand more about differences in prognosis for return to work after intensive work-related rehabilitation efforts. HubMed – rehab