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Award Abstract # 1208637
NRI-Small: Robotic Treadmill Therapy for Lower Spinal Cord Injuries

NSF Org: IIS
Division of Information & Intelligent Systems
Recipient: UNIVERSITY OF UTAH
Initial Amendment Date: August 15, 2012
Latest Amendment Date: April 17, 2015
Award Number: 1208637
Award Instrument: Standard Grant
Program Manager: Reid Simmons
IIS
 Division of Information & Intelligent Systems
CSE
 Directorate for Computer and Information Science and Engineering
Start Date: September 1, 2012
End Date: August 31, 2017 (Estimated)
Total Intended Award Amount: $908,999.00
Total Awarded Amount to Date: $916,999.00
Funds Obligated to Date: FY 2012 = $908,999.00
FY 2015 = $8,000.00
History of Investigator:
  • John Hollerbach (Principal Investigator)
    jmh@cs.utah.edu
  • Jake Abbott (Co-Principal Investigator)
Recipient Sponsored Research Office: University of Utah
201 PRESIDENTS CIR
SALT LAKE CITY
UT  US  84112-9049
(801)581-6903
Sponsor Congressional District: 01
Primary Place of Performance: University of Utah
UT  US  84112-8930
Primary Place of Performance
Congressional District:
01
Unique Entity Identifier (UEI): LL8GLEVH6MG3
Parent UEI:
NSF Program(s): NRI-National Robotics Initiati
Primary Program Source: 01001213DB NSF RESEARCH & RELATED ACTIVIT
01001516DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 7923, 8086, 9150, 9251
Program Element Code(s): 801300
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.070

ABSTRACT

New rehabilitation therapies for patients with incomplete lower spinal cord injuries (SCI) will be developed using the Treadport, a robotic treadmill that provides a realistic walking experience in a safe and flexible virtual environment. The Treadport overcomes limitations of current rehabilitation treadmills, which are too dissimilar from everyday walking and therefore limit a patient's recovery. We will seek to improve a patient's walking speed and effort, resistance to falling by strengthening and training a patient to unexpected perturbations, and arm swing coordination which is critical for normal walking. The intellectual merit is the body-weight assisted robotic treadmill training, and arm swing assistance using a light-weight exoskeleton. The robotic treadmill will provide monitored assistance and virtual reality training scenarios not currently possible.

The broader impact is the development of new technology and scientific understanding that will improve the lives of SCI patients so that they have the most mobility possible given their injuries. The proposed research combines the disciplines of robotics, biomechanics, and physical therapy, and requires interdisciplinary training. The socially positive nature of this project is expected to be especially attractive to underrepresented populations in engineering and computer science, particularly women and people with disabilities.

This proposal addresses the co-worker theme of the National Robotics Initiative, particularly rehabilitation, orthotics and prosthetics.

PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

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B. Hejrati, K.L. Crandall, J.M. Hollerbach, and J.J. Abbott "Kinesthetic Force Feedback and Belt Control for the Treadport Locomotion Interface" IEEE Transactions on Haptics , v.8 , 2015 , p.176
B. Hejrati, S. Cheesborough, B. Foreman, J.J. Abbott, and A.S. Merrywheather "Comprehensive Quantitative Investigation of Arm Swing during Walking at Various Speed and Surface Slope Conditions" Human Movement Science , v.14 , 2016
B. Hejrati, S. Chesebrough, K. B. Foreman, J. J. Abbott, and A. S. Merryweather "Comprehensive Quantitative Investigation of Arm Swing During Walking at Various Speed and Surface Slope Conditions" Human Movement Science , v.49 , 2016 , p.104
Hejrati, B., Crandall, K., Hollerbach, J.M., and Abbott, J.J. "`Kinesthetic Force Feedback and Belt Control for the Treadport Locomotion Interface" IEEE Trans. H aptics , v.8 , 2015 , p.176
Hejrati, B., Crandall, K.L., Hollerbach, J.M., and Abbott, J.J. "Kinesthetic force feedback and belt controller for the Treadport locomotion interface" IEEE Transactions on Haptics , v.9 , 2015 , p.176
O.R. Barnes, B. Hejrati, and J.J. Abbott "An Underactuated Wearable Arm-swing Rehabilitator for Gait Training" IEEE International Conference on Robotics and Automation , 2015
Sabetian, P., and Hollerbach, J.M. "`A 3 wire body weight support system for a large treadmill" IEEE Intl. Conf. Robotics and Automation , 2017 , p.498

PROJECT OUTCOMES REPORT

Disclaimer

This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.

The major outcome was to demonstrate that a robotic treadmill, theTreadport locomotion interface, significantly improves the gaits ofpatients with partial Spinal Cord Injuries (SCI) over standardtreadmill training in a clinic.  Patients walk more normally, fasterand longer, and more confidently.The features of the Treadport that differ from ordinary rehabilitationor exercise treadmills are (1) a large 6-by-10-foot belt, (2) anenveloping frontal visual display for projecting virtual realitysimulations of farms, cities, and even the Martian surface, and (3) amechanical tether that pushes and pulls on the user and that controlsmotion of the belt and motion of the use through a virtual world.Our first set of studies with 12 patients sought to understand whichfeatures of the Treadport were most responsible for the improvedresults.  Of the 3 features listed above, the key features wereself-selected speed by virtue of the operation of the mechanicaltether, and belt width.  The Treadport allows patients to set theirown speed of walking instantaneously, making it much more realisticthan clinical treadmills where speed is set by therapists.  The beltwidth allows patients to focus on walking through a virtualenvironment without worrying about stepping off the belt.  On a narrowbelt, patients kept their feet wider apart, apparently for stabilityreasons, but on the Treadport the patients kept a narrower distancesideways between feet, showing a greater sense of stability.Another set of studies with 12 patients looked at the longer-termeffect, where patients trained for 8 sessions over a 6-week period onthe Treadport and on the clinical treadmill each.  The results showedthat the rate of speed increase after 8 sessions was significantlygreater on the Treadport, meaning that the patients got better faster. The other major outcome was improvements to the hardware, control andsoftware to make the Treadport arguably the most realistic simulatorof real-world walking.  We highlight 3 such improvements.  (1)Previous research on ordinary treadmills indicated that stride lengthis shorter on treadmills than on the ground, but on the Treadport weshowed for the first time that walking on a treadmill can be the sameas on the ground.  The reason is that the mechanical tether pulls onthe user with prescribed forces to simulate missing inertial forces.The mechanical tether can also simulate slop walking without tiltingthe treadmill deck, which could lead to less expensive treadmills foreventual use in a clinic.(2) Another hardware addition was a 3-wire body weight support system,mounted in the ceiling.  The 3-wire system ensures that the supportforces are always vertical, which is important because of the large6-by-10 foot deck that allows the user to move around more than onordinary treadmills.  Body-weight support is required by somepatients.  It can help simulate reduced-gravity walking on Mars.  Itsuse was also shown to help simulate steep slope walking using themechanical tether force, since vertical forces are required to keepthe net forces on the body to equal the body weight.(3) An arm swing pacemaker was developed to assist SCI patients whoneed to relearn to swing their arms in rhythm with the step cycle.Arm swing is necessary to help stabilize the gait, and as aneurologically coupled motion to gait.  Although arm swing traininghas not yet been done on patients, studies were performed on healthysubjects to characterize what are normal arm-swing trajectories.  Totrigger the arm swing motions, a method was developed that convertsthigh-worn IMU signals into arm-swing trajectories.

 


Last Modified: 11/30/2017
Modified by: John M Hollerbach

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