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Review of control strategies for robotic movement training after neurologic injury.

Marchal-Crespo L, Reinkensmeyer DJ - J Neuroeng Rehabil (2009)

Bottom Line: Several categories of strategies have been proposed, including, assistive, challenge-based, haptic simulation, and coaching.Clinical evidence regarding the relative effectiveness of different types of robotic therapy controllers is limited, but there is initial evidence that some control strategies are more effective than others.It is also now apparent there may be mechanisms by which some robotic control approaches might actually decrease the recovery possible with comparable, non-robotic forms of training.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Mechanical and Aerospace Engineering, University of California, Irvine, CA, USA. lmarchal@uci.edu

ABSTRACT
There is increasing interest in using robotic devices to assist in movement training following neurologic injuries such as stroke and spinal cord injury. This paper reviews control strategies for robotic therapy devices. Several categories of strategies have been proposed, including, assistive, challenge-based, haptic simulation, and coaching. The greatest amount of work has been done on developing assistive strategies, and thus the majority of this review summarizes techniques for implementing assistive strategies, including impedance-, counterbalance-, and EMG- based controllers, as well as adaptive controllers that modify control parameters based on ongoing participant performance. Clinical evidence regarding the relative effectiveness of different types of robotic therapy controllers is limited, but there is initial evidence that some control strategies are more effective than others. It is also now apparent there may be mechanisms by which some robotic control approaches might actually decrease the recovery possible with comparable, non-robotic forms of training. In future research, there is a need for head-to-head comparison of control algorithms in randomized, controlled clinical trials, and for improved models of human motor recovery to provide a more rational framework for designing robotic therapy control strategies.

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Number of articles cited in this review article published each year for the last 20 years. Number of articles cited in this review article published each year for the last 20 years. Note the exponential increase of publications in the last five years.
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Figure 2: Number of articles cited in this review article published each year for the last 20 years. Number of articles cited in this review article published each year for the last 20 years. Note the exponential increase of publications in the last five years.

Mentions: There is increasing interest in using robotic devices to help provide rehabilitation therapy following neurologic injuries such as stroke and spinal cord injury [1,2] (Figure 1). The general paradigm being explored [see Additional file 1] is to use a robotic device to physically interact with the participant's limbs during movement training, although there is also work that uses robots that do not physically contact the participant to "coach" the participant [3-5]. As can be seen in Figure 2, there was an exponential increase in papers in this field over the past ten years.


Review of control strategies for robotic movement training after neurologic injury.

Marchal-Crespo L, Reinkensmeyer DJ - J Neuroeng Rehabil (2009)

Number of articles cited in this review article published each year for the last 20 years. Number of articles cited in this review article published each year for the last 20 years. Note the exponential increase of publications in the last five years.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2710333&req=5

Figure 2: Number of articles cited in this review article published each year for the last 20 years. Number of articles cited in this review article published each year for the last 20 years. Note the exponential increase of publications in the last five years.
Mentions: There is increasing interest in using robotic devices to help provide rehabilitation therapy following neurologic injuries such as stroke and spinal cord injury [1,2] (Figure 1). The general paradigm being explored [see Additional file 1] is to use a robotic device to physically interact with the participant's limbs during movement training, although there is also work that uses robots that do not physically contact the participant to "coach" the participant [3-5]. As can be seen in Figure 2, there was an exponential increase in papers in this field over the past ten years.

Bottom Line: Several categories of strategies have been proposed, including, assistive, challenge-based, haptic simulation, and coaching.Clinical evidence regarding the relative effectiveness of different types of robotic therapy controllers is limited, but there is initial evidence that some control strategies are more effective than others.It is also now apparent there may be mechanisms by which some robotic control approaches might actually decrease the recovery possible with comparable, non-robotic forms of training.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Mechanical and Aerospace Engineering, University of California, Irvine, CA, USA. lmarchal@uci.edu

ABSTRACT
There is increasing interest in using robotic devices to assist in movement training following neurologic injuries such as stroke and spinal cord injury. This paper reviews control strategies for robotic therapy devices. Several categories of strategies have been proposed, including, assistive, challenge-based, haptic simulation, and coaching. The greatest amount of work has been done on developing assistive strategies, and thus the majority of this review summarizes techniques for implementing assistive strategies, including impedance-, counterbalance-, and EMG- based controllers, as well as adaptive controllers that modify control parameters based on ongoing participant performance. Clinical evidence regarding the relative effectiveness of different types of robotic therapy controllers is limited, but there is initial evidence that some control strategies are more effective than others. It is also now apparent there may be mechanisms by which some robotic control approaches might actually decrease the recovery possible with comparable, non-robotic forms of training. In future research, there is a need for head-to-head comparison of control algorithms in randomized, controlled clinical trials, and for improved models of human motor recovery to provide a more rational framework for designing robotic therapy control strategies.

Show MeSH
Related in: MedlinePlus