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Identifying Robotic Training Forces Which Lead To Optimal Recovery of Overground Locomotion

Award Number: R03HD107438
ORGANIZATION: NATIONAL INSTITUTE OF CHILD HEALTH AND HUMAN DEVELOPMENT
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)

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Conventional physical therapy following spinal cord injury (SCI) is an arduous task met with minimal returns and quickly plateauing recovery. Unconventional therapies, such as robotic assisted gait training (RAGT) have not produced the robust clinical gains that we all had hoped. Rodent RAGT is a nascent field, but it works on the same principles as the clinical counterpart. We have previously quantified the loss of function and spontaneous recovery of locomotion following SCI in rats. We have also investigated the ability of RAGT to enhance this recovery. After studying over 100 rats we have learned that training in a resistive field is detrimental, and training in a negative viscosity field is better than actively guiding the limbs through a healthy stepping pattern. Unfortunately, none of these treatments are particularly good at restoring locomotion. We believe that reanalysis of our existing data will uncover the optimal RAGT technique. Previously we grouped animals based on the RAGT treatment they received. Upon further reflection, these groups are not based on what the animals actually experienced, but how the robot was programmed. It may come to light that the actual forces applied during training, a force profile, is what leads to greater recovery. With this proposal we plan to uncover the optimal RAGT force profile by reanalyzing our existing data bi-directionally (does force profile predict recovery?, does recovery predict force profile?). This will provide new insights into the importance of the specific forces used in rehabilitation, and thus optimize RAGT. Aim 1 is to use cluster analysis to create new treatment groups based on similar force profiles during training, and see if there is a difference in the level of locomotor recovery. Aim 2 is to conduct outlier analysis to determine if rats that showed greater recovery of locomotion had similar force profiles during training. By using two separate techniques we hope to uncover a single (or very similar) force profile that optimizes RAGT. Training with such a force profile would represent a major shift in current RAGT techniques, and lead to improvements in patients’ lives.


Issue Date FY	Funding FY	Legal Entity Name	Legal Entity Address	Legal Entity City	Legal Entity State	Legal Entity Zip Code	Legal Entity COUNTY	Legal Entity COUNTRY	Assistance Listing	Award Code	Budget Year	Action Date	Action Type	Action Amount

Issue Date FY: 2024 ( Subtotal = -$1 )
2024	2023	GEORGETOWN UNIVERSITY	MAIN CAMPUS	WASHINGTON	DC	20057	DISTRICT OF COLUMBIA	USA	Child Health and Human Development Extramural Research	000	2	6/25/2024	NON-COMPETING CONTINUATION	-$1
														Subtotal = -$1

Issue Date FY: 2023 ( Subtotal = $78,000 )
2023	2023	GEORGETOWN UNIVERSITY	MAIN CAMPUS	WASHINGTON	DC	20057	DISTRICT OF COLUMBIA	USA	Child Health and Human Development Extramural Research	000	2	3/28/2023	NON-COMPETING CONTINUATION	$78,000
														Subtotal = $78,000

Issue Date FY: 2022 ( Subtotal = $78,000 )
2022	2022	GEORGETOWN UNIVERSITY (THE)	37TH AND O ST NW	WASHINGTON	DC	20057	DISTRICT OF COLUMBIA	USA	Child Health and Human Development Extramural Research	000	1	3/17/2022	NEW	$78,000
														Subtotal = $78,000

Grand Total All Awards = $155,999

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Identifying Robotic Training Forces Which Lead To Optimal Recovery of Overground Locomotion

Award Number: R03HD107438

ORGANIZATION: NATIONAL INSTITUTE OF CHILD HEALTH AND HUMAN DEVELOPMENT

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)

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