Publication Cover
Assistive Technology
The Official Journal of RESNA
Volume 35, 2023 - Issue 6
386
Views
1
CrossRef citations to date
0
Altmetric
Research Article

Factors influencing neuromuscular responses to gait training with a robotic ankle exoskeleton in cerebral palsy

, PhDORCID Icon, , MScORCID Icon, , PhDORCID Icon & , PhDORCID Icon
Pages 463-470 | Accepted 29 Aug 2022, Published online: 04 Oct 2022

References

  • Apley, D. W. (2018). ALEPlot: Accumulated local effects (ALE) plots and partial dependence (PD) plots. R Package.
  • Apley, D. W., & Zhu, J. (2020). Visualizing the effects of predictor variables in black box supervised learning models. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 82(4), 1059–1086. https://doi.org/10.1111/rssb.12377
  • Beretta, E., Storm, F. A., Strazzer, S., Frascarelli, F., Petrarca, M., Colazza, A., Castelli, E., Cordone, G., Biffi, E., Morganti, R., Maghini, C., Piccinini, L, & Castelli, E. (2020). Effect of robot-assisted gait training in a large population of children with motor impairment due to cerebral palsy or acquired brain injury. Archives of Physical Medicine and Rehabilitation, 101(1), 106–112. https://doi.org/10.1016/j.apmr.2019.08.479
  • Breiman, L. (2001). Random forests. Machine Learning, 45(1), 5–32. https://doi.org/10.1023/A:1010933404324
  • Chipman, H. A., George, E. I., & McCulloch, R. E. (2010). BART: Bayesian additive regression trees. The Annals of Applied Statistics, 4(1), 266–298. https://doi.org/10.1214/09-AOAS285
  • Conner, B. C., Luque, J., & Lerner, Z. F. (2020). Adaptive ankle resistance from a wearable robotic device to improve muscle recruitment in cerebral palsy. Annals of Biomedical Engineering, 48(4), 1309–1321. https://doi.org/10.1007/s10439-020-02454-8
  • Conner, B. C., Remec, N. M., & Lerner, Z. F. (2022). Is robotic gait training effective for individuals with cerebral palsy? A systematic review and meta-analysis of randomized controlled trials. Clinical Rehabilitation, 2692155221087084. https://doi.org/10.1177/02692155221087084
  • Conner, B. C., Remec, N. M., Orum, E. K., Frank, E. M., & Lerner, Z. F. (2020). Wearable adaptive resistance training improves ankle strength, walking efficiency and mobility in cerebral palsy: A pilot clinical trial. IEEE Open Journal of Engineering in Medicine and Biology, 1, 282–289. https://doi.org/10.1109/OJEMB.2020.3035316
  • Conner, B. C., Schwartz, M. H., & Lerner, Z. F. (2021). Pilot evaluation of changes in motor control after wearable robotic resistance training in children with cerebral palsy. Journal of Biomechanics, 126, 110601. https://doi.org/10.1016/j.jbiomech.2021.110601
  • Dorie, V., Hill, J., Shalit, U., Scott, M., & Cervone, D. (2019). Automated versus do-it-yourself methods for causal inference: lessons learned from a data analysis Competition. Statistical Science, 34(1), 43–68. https://doi.org/10.1214/18-STS667
  • Drużbicki, M., Rusek, W., Snela, S., Dudek, J., Szczepanik, M., Zak, E., Durmala, J., Czernuszenko, A., Bonikowski, M., & Sobota, G. (2013). Functional effects of robotic-assisted locomotor treadmill thearapy in children with cerebral palsy. Journal of Rehabilitation Medicine, 45(4), 358–363. https://doi.org/10.2340/16501977-1114
  • Freund, Y., & Schapire, R. E. (1997). A decision-theoretic generalization of on-line learning and an application to boosting. Journal of Computer and System Sciences, 55(1), 119–139. https://doi.org/10.1006/jcss.1997.1504
  • Graham, H. K., Rosenbaum, P., Paneth, N., Dan, B., Lin, J. -P., Damiano, D. L., & Lieber, R. L. (2016). Cerebral palsy. Nature Reviews Disease Primers, 2(1), 15082. https://doi.org/10.1038/nrdp.2015.82
  • Halilaj, E., Rajagopal, A., Fiterau, M., Hicks, J. L., Hastie, T. J., & Delp, S. L. (2018). Machine learning in human movement biomechanics: Best practices, common pitfalls, and new opportunities. Journal of Biomechanics, 81, 1–11. https://doi.org/10.1016/j.jbiomech.2018.09.009
  • Hicks, J. L., Schwartz, M. H., Arnold, A. S., & Delp, S. L. (2008). Crouched postures reduce the capacity of muscles to extend the hip and knee during the single-limb stance phase of gait. Journal of Biomechanics, 41(5), 960–967. https://doi.org/10.1016/j.jbiomech.2008.01.002
  • Hof, A. L. (2018). Scaling and normalization. In S. I. Wolf & B. Muller (Eds.), Handbook of human motion (pp. 295–305). Springer.
  • Kang, J., Martelli, D., Vashista, V., Martinez-Hernandez, I., Kim, H., & Agrawal, S. K. (2017). Robot-driven downward pelvic pull to improve crouch gait in children with cerebral palsy. Science Robotics, 2(8), eaan2634. https://doi.org/10.1126/scirobotics.aan2634
  • Kapelner, A., & Bleich, J. (2015). Prediction with missing data via Bayesian additive regression trees. Canadian Journal of Statistics, 43(2), 224–239. https://doi.org/10.1002/cjs.11248
  • Kapelner, A., & Bleich, J. (2016). bartMachine: Machine learning with Bayesian additive regression trees. Journal of Statistical Software, 70(4). https://doi.org/10.18637/jss.v070.i04
  • Mehrholz, J., Thomas, S., Kugler, J., Pohl, M., & Elsner, B. (2020, October). Electromechanical-assisted training for walking after stroke. Cochrane Database of Systematic Reviews, 2020. https://doi.org/10.1002/14651858.CD006185.pub5.
  • Nam, K. Y., Kim, H. J., Kwon, B. S., Park, J. W., Lee, H. J., & Yoo, A. (2017). Robot-assisted gait training (Lokomat) improves walking function and activity in people with spinal cord injury: A systematic review. Journal of Neuroengineering and Rehabilitation, 14(1), 1–13. https://doi.org/10.1186/s12984-017-0232-3
  • Orekhov, G., Fang, Y., Cuddeback, C. F., & Lerner, Z. F. (2021). Usability and performance validation of an ultra-lightweight and versatile untethered robotic ankle exoskeleton. Journal of Neuroengineering and Rehabilitation, 18(1), 163. https://doi.org/10.1186/s12984-021-00954-9
  • Rajagopal, A., Kidziński, Ł., McGlaughlin, A. S., Hicks, J. L., Delp, S. L., & Schwartz, M. H. (2018). Estimating the effect size of surgery to improve walking in children with cerebral palsy from retrospective observational clinical data. Scientific Reports, 8(1), 16344. https://doi.org/10.1038/s41598-018-33962-2
  • Ries, A. J., Novacheck, T. F., & Schwartz, M. H. (2014). Predicting changes in gait associated with optimal ankle-foot orthosis selection in children with cerebral palsy. Gait & Posture, 39(Supplement 1), S78–S79. https://doi.org/10.1016/j.gaitpost.2014.04.108
  • Shuman, B. R., Goudriaan, M., Desloovere, K., Schwartz, M. H., & Steele, K. M. (2018). Associations between muscle synergies and treatment outcomes in cerebral palsy are robust across clinical centers. Archives of Physical Medicine and Rehabilitation, 99(11), 2175–2182. https://doi.org/10.1016/j.apmr.2018.03.006
  • Shuman, B. R., Schwartz, M. H., & Steele, K. M. (2017). Electromyography data processing impacts muscle synergies during gait for unimpaired children and children with cerebral palsy. Frontiers in Computational Neuroscience, 11, 50. https://doi.org/10.3389/fncom.2017.00050
  • Smania, N., Bonetti, P., Gandolfi, M., Cosentino, A., Waldner, A., Hesse, S., Munari, D., Werner, C., Bisoffi, G., Geroin C., & Munari, D. (2011). Improved gait after repetitive locomotor training in children with cerebral palsy. American Journal of Physical Medicine & Rehabilitation, 90(2), 137–149. https://doi.org/10.1097/PHM.0b013e318201741e
  • Steele, K. M., Rozumalski, A., & Schwartz, M. H. (2015). Muscle synergies and complexity of neuromuscular control during gait in cerebral palsy. Developmental Medicine and Child Neurology, 57(12), 1176–1182. https://doi.org/10.1111/dmcn.12826
  • Tukey, J. W. (1977). Exploratory data analysis. Addison-Wesley.
  • Wallard, L., Dietrich, G., Kerlirzin, Y., & Bredin, J. (2017). Robotic-assisted gait training improves walking abilities in diplegic children with cerebral palsy. European Journal of Paediatric Neurology, 21(3), 557–564. https://doi.org/10.1016/j.ejpn.2017.01.012
  • Winchester, P., McColl, R., Querry, R., Foreman, N., Mosby, J., Tansey, K., & Williamson, J. (2005). Changes in supraspinal activation patterns following robotic locomotor therapy in motor-incomplete spinal cord injury. Neurorehabilitation and Neural Repair, 19(4), 313–324. https://doi.org/10.1177/1545968305281515
  • Wu, M., Kim, J., Gaebler-Spira, D. J., Schmit, B. D., & Arora, P. (2017). Robotic resistance treadmill training improves locomotor function in children with cerebral palsy: A randomized controlled pilot study. Archives of Physical Medicine and Rehabilitation, 98(11), 2126–2133. https://doi.org/10.1016/j.apmr.2017.04.022

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.