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Stroke Survivors' Gait Adaptations to a Powered Ankle Foot Orthosis.

Authors:
Jeffrey Ward Thomas Sugar Alexander Boehler John Standeven Jack R Engsberg

Adv Robot 2011 Jan;25(15):1879-1901

Washington University; Saint Louis, Missouri 63130.

Background And Purpose: Stroke is the leading cause of long term disability in the United States, and for many it causes loss of gait function. The purpose of this research is to examine stroke survivors' gait adaptations to training on the Powered Ankle Foot Orthosis (PAFO). Of particular interest is the stroke survivors' ability to learn how to store and release energy properly while using the device. The PAFO utilizes robotic tendon technology and supports motion with a single degree of freedom, ankle rotation in the sagittal plane. This actuator comprises a motor and series spring. The user interacts with the output side of the spring while the robot controls the input side of the spring such that typical able body ankle moments would be generated, assuming able body ankle kinematics are seen at the output side of the spring.

Methods: Three individuals post-stroke participated in a three week training protocol. Outcome measures (temporal, kinematic, and kinetic) were derived from robot sensors and recorded for every step. These data are used to evaluate each stroke survivor's adaptations to robotic gait assistance. The robot was worn only on the paretic ankle. For validation of the kinematic results, motion capture data were collected on the third subject.

Results: All subjects showed increased cadence, ankle range of motion, and power generation capabilities. Additionally, all subjects were able to achieve a larger power output than power input from the robot. Motion capture data collected from subject three validated the robot sensor kinematic data on the affected side, but also demonstrated an unexpected gait adaptation on the unaffected ankle.

Conclusions: Sensors on the gait assisting robot provide large volumes of valuable information on how gait parameters change over time. We have developed key gait evaluation metrics based on the available robot sensor information that may be useful to future researchers. All subjects adapted their gait to the robotic assistance, and many of their key metrics moved closer to typical able body values. This suggests that each subject learned to utilize the assistive moments generated by the robot, despite having no predefined ankle trajectory input from the robot. The security of being harnessed on the treadmill led to more dramatic and favorable results.

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http://dx.doi.org/10.1163/016918611X588907DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4203663PMC
January 2011

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