Unraveling Mechanisms Underlying the Effectiveness of Robot-Assisted Gait Training in Children with Cerebral Palsy
Abstract
The objective of this paper is to discuss potential mechanisms that affect the outcomes of robot-assisted gait training in children with cerebral palsy. Our group and others have shown that gait function can be significantly improved in children with cerebral palsy by relying upon robotic technology. However, it has been also emphasized that the magnitude of motor gains achieved in this patient population varies dramatically from subject to subject. This observation has motivated many to explore mechanisms potentially related to the differences in robot-assisted gait training outcomes observed across individuals. Factors that we explore and discuss in this paper include the baseline functional ability level of the individual receiving gait training, the specific type of gait deviations observed at baseline, the mechanical characteristics of the robot used for training, the level of engagement of the child during the therapeutic session, and finally the ability of individuals to generate motor adaptation strategies in response to the forces generated by the robot. We observe that the ability of individuals to generate motor adaptation strategies has been disregarded by previous research work and suggest that methodologies suitable to assess the ability of children with cerebral palsy to ”respond” to the forces generated by the robot should be developed and tested.
Keywords
Robot-assisted gait training cerebral palsy motor controlPreview
Unable to display preview. Download preview PDF.
References
- 1.Meyer-Heim, A., et al.: Feasibility of robotic-assisted locomotor training in children with central gait impairment. Dev. Med. Child. Neurol. 49, 900–906 (2007)CrossRefGoogle Scholar
- 2.Borggraefe, I., et al.: Improved gait parameters after robotic-assisted locomotor treadmill therapy in a 6-year-old child with cerebral palsy. Mov. Disord. 23, 280–283 (2008)CrossRefGoogle Scholar
- 3.Patritti, B.L., et al.: Robotic Gait Training in Children with Cerebral Palsy. In: XVII Congress of the International Society of Electrophysiology and Kinesiology, Niagara Falls, Canada (2008)Google Scholar
- 4.Patritti, B., et al.: Enhancement and Retention of Locomotor Function in Children with Cerebral Palsy after Lokomat Training. In: 18th Meeting of the European Society of Movement Analysis for Adults and Children, London, United Kingdom (2009)Google Scholar
- 5.Pietrusinski, M., et al.: Design of Human-Machine Interface and altering of pelvic obliquity with RGR Trainer. In: IEEE Int. Conf. Rehabil. Robot., vol. 2011, p. 5975496 (2011)Google Scholar
- 6.Koenig, A., et al.: Virtual gait training for children with cerebral palsy using the Lokomat gait orthosis. Stud. Health Technol. Inform. 132, 204–209 (2008)Google Scholar
- 7.Brutsch, K., et al.: Influence of virtual reality soccer game on walking performance in robotic assisted gait training for children. J. Neuroeng. Rehabil. 7, 15 (2010)CrossRefGoogle Scholar
- 8.Patritti, B., et al.: The Role of Augmented Feedback in Pediatric Robotic-Assisted Gait Training: A Case Series. Technology and Disability 22, 215–227 (2010)Google Scholar
- 9.Shadmehr, R., Mussa-Ivaldi, F.A.: Adaptive representation of dynamics during learning of a motor task. J. Neurosci. 14, 3208–3224 (1994)Google Scholar
- 10.Cajigas, I., et al.: Assessment of lower extremity motor adaptation via an extension of the force field adaptation paradigm. In: Conf. Proc. IEEE Eng. Med. Biol. Soc., vol. 2010, pp. 4522–4525 (2010)Google Scholar
- 11.Priplata, A.A., et al.: Noise-enhanced balance control in patients with diabetes and patients with stroke. Ann. Neurol. 59, 4–12 (2006)CrossRefGoogle Scholar
- 12.Cheung, V.C., et al.: Muscle synergy patterns as physiological markers of motor cortical damage. Proc. Natl. Acad. Sci. U S A 109, 14652–14656 (2012)CrossRefGoogle Scholar