» Articles » PMID: 23080038

Robotic-assisted Gait Training and Restoration

Overview
Date 2012 Oct 20
PMID 23080038
Citations 17
Authors
Affiliations
Soon will be listed here.
Abstract

The past two decades have seen the introduction of and a strong growth in the availability of rehabilitation interventions that are based on the use of robotics. A major driving factor has been the advancement of technology, with faster, more powerful computers, new computational approaches, as well as increased sophistication of motors and other electro mechanical components. These advancements in technology have not been the only factor propelling these new rehabilitation interventions. During the same period, a strong growth in the understanding of neuroplasticity and motor learning has also been witnessed. Although there is still much to learn, comprehension of how new skills are acquired, or old ones are relearned, is evolving at a fast pace. Much of this improved understanding can be linked to the advancement of central nervous system imaging as well as techniques for studying changes at the cellular or molecular level. In this review, the authors present the notion that an ever-advancing understanding of neuroplasticity and motor learning can provide a theoretical basis for the clinical use of rehabilitation robotics as applied to enhancing mobility. Specifically focusing on locomotor training after injury to the central nervous system, these principles can provide guidance to clinicians on how to structure their interventions to potentially promote or accelerate functional recovery in their patients. Several types of existing robotic devices to assist walking that are currently available for use in the clinic, as well as their advantages and limitations, will be discussed.

Citing Articles

Efficacy of robot-assisted gait training on lower extremity function in subacute stroke patients: a systematic review and meta-analysis.

Hu M, Wang S, Wu C, Li K, Geng Z, Xu G J Neuroeng Rehabil. 2024; 21(1):165.

PMID: 39300491 PMC: 11411785. DOI: 10.1186/s12984-024-01463-1.


Modeling Neuromotor Adaptation to Pulsed Torque Assistance During Walking.

Kim G, Sergi F bioRxiv. 2024; .

PMID: 38979158 PMC: 11230210. DOI: 10.1101/2024.02.19.580556.


Effect of Robotic-Assisted Gait at Different Levels of Guidance and Body Weight Support on Lower Limb Joint Kinematics and Coordination.

Cherni Y, Blache Y, Begon M, Ballaz L, Dal Maso F Sensors (Basel). 2023; 23(21).

PMID: 37960500 PMC: 10650199. DOI: 10.3390/s23218800.


Effect of exoskeleton robot-assisted training on gait function in chronic stroke survivors: a systematic review of randomised controlled trials.

Yang J, Gong Y, Yu L, Peng L, Cui Y, Huang H BMJ Open. 2023; 13(9):e074481.

PMID: 37709309 PMC: 10503387. DOI: 10.1136/bmjopen-2023-074481.


Gait Training with Robotic Exoskeleton Assisted Rehabilitation System in Patients with Incomplete Traumatic and Non-Traumatic Spinal Cord Injury: A Pilot Study and Review of Literature.

Gupta A, Prakash N, Honavar P Ann Indian Acad Neurol. 2023; 26(Suppl 1):S26-S31.

PMID: 37092019 PMC: 10114533. DOI: 10.4103/aian.aian_1075_21.