This instrumentation grant project is to develop an integrated gait training and evaluation system, which will be one-of-a-kind facility for gait rehabilitation of stroke and other motor impaired subjects. Some features of this system are: (i) interface to novel lower extremity robotic exoskeletons being developed at the University of Delaware under Bioengineering Partnership R01 grant HD 38582, worn during training of the stroke survivors. These exoskeletons provide natural motion to the trunk and can apply actuator inputs at the hip and knee joints to retrain human gait. (ii) interface to innovative functional electric stimulation algorithms that assist in ankle dorsiflexion during swing and generation of anterior posterior ground reaction forces (push-off force) during late stance, currently under development under grant number 1R01NR010786-01. (iii) interface to force plate data from a dual belt instrumented treadmill - this data, in conjunction with force sensors on the robotic exoskeletons, will allow to perform real-time computation of joint kinetics and to optimize the effects of stimulation to the ankle muscles. (iv) interface to high speed motion capture data from a camera system, which will be calibrated to the joint motion data coming from the sensors on the robotic exoskeletons. This calibration will help provide more accurate and reliable data to the exoskeleton control and muscle stimulation algorithms. (v) The gait evaluation before and after the training will have synchronized motion data, force plate data, EMG data for both walking on treadmill and overground, as proposed in BRP grant HD 38582, 1R01NR010786-01, R01 grant NS50880, and for a variety of other studies including upper and lower extremity during walking and reaching tasks with stroke subjects. In this proposal, Vicon will serve as the provider for this integrated training and evaluation system that will consist of a high speed motion capture system (8 MX-T40 cameras with software), an instrumented dual belt treadmill with force plates and hand rail force sensors (Bertec), 16 channel EMG system (ZeroWire telemetered System), real-time data acquisition and control system (dSpace 1103 boards), and functional electrical stimulation hardware (National Instruments CompactRIO system and Grass stimulators). The justifications for this instrumentation grant are as follows: (i) Currently, the instrument is only available in components, e.g., high speed motion capture system, instrumented treadmill, EMG system, dSpace data acquisition and control system, in different laboratories on campus. As a result, data from these components can not be collected in one place in the same session with the patient, (ii) The research funding in the area of """"""""functional training and rehabilitation"""""""" has nearly doubled in the last 5 years at the University of Delaware. As a result, the existing facilities such as motion capture system, instrumented treadmill, EMG systems, data acquisition systems are used to their full capacity and there is little or no chance to integrate these into a single system in a single laboratory which can then be used for research and training of human subjects.

Agency
National Institute of Health (NIH)
Institute
National Center for Research Resources (NCRR)
Type
Biomedical Research Support Shared Instrumentation Grants (S10)
Project #
1S10RR028114-01A1
Application #
8052167
Study Section
Special Emphasis Panel (ZRG1-MOSS-G (30))
Program Officer
Levy, Abraham
Project Start
2011-07-01
Project End
2013-06-30
Budget Start
2011-07-01
Budget End
2013-06-30
Support Year
1
Fiscal Year
2011
Total Cost
$404,065
Indirect Cost
Name
University of Delaware
Department
Engineering (All Types)
Type
Schools of Engineering
DUNS #
059007500
City
Newark
State
DE
Country
United States
Zip Code
19716
Charalambous, Charalambos C; Alcantara, Carolina C; French, Margaret A et al. (2018) A single exercise bout and locomotor learning after stroke: physiological, behavioural, and computational outcomes. J Physiol 596:1999-2016
Alcântara, Carolina C; Charalambous, Charalambos C; Morton, Susanne M et al. (2018) Different Error Size During Locomotor Adaptation Affects Transfer to Overground Walking Poststroke. Neurorehabil Neural Repair 32:1020-1030
Charalambous, Charalambos C; Helm, Erin E; Lau, Kristin A et al. (2018) The feasibility of an acute high-intensity exercise bout to promote locomotor learning after stroke. Top Stroke Rehabil 25:83-89
Helm, Erin E; Matt, Kathleen S; Kirschner, Kenneth F et al. (2017) The influence of high intensity exercise and the Val66Met polymorphism on circulating BDNF and locomotor learning. Neurobiol Learn Mem 144:77-85
Kim, Seok Hun; Banala, Sai K; Brackbill, Elizabeth A et al. (2010) Robot-assisted modifications of gait in healthy individuals. Exp Brain Res 202:809-24