Robotic Assessment of Lower Extremity Motor Learning
This trial is active, not recruiting.
|Sponsor||Spaulding Rehabilitation Hospital|
|Start date||February 2010|
|End date||September 2016|
|Trial size||40 participants|
|Trial identifier||NCT01361867, 2009-P-002030|
The investigators hypothesize that the motor learning processes observed in the lower extremity will be similar to those seen in upper arm experiments. Furthermore, the investigators hypothesize that lower extremity motor learning can be quantified with an adapted model of the force-field adaption paradigm (FFAP) introduced by Shadmehr et al. for studying motor learning in the upper extremities.
|Intervention model||single group assignment|
|Primary purpose||basic science|
The subject is put on the Lokomat and the program will vary between free walking and perturbed walking.
Rate of subject motor adaptation
time frame: 4 hours
Male or female participants from 18 years up to 55 years old.
- Males and females, healthy adults age 18-55 years, with normal gait.
- Lower extremity fractures
- Current or previous history of orthopedic injury that would prevent safe use of the Lokomat
- Body/femoral length size beyond the limits of Lokomat robotic arm (femur length between 350-470mm)
- Body weight > 135kg (~298 lbs) maximum limit of the body weight support system
- Skin lesions on the lower extremities
- Cardiovascular or pulmonary contraindications
- Motor system or proprioceptive impairments
- Severe cognitive impairments that would prevent the use of the Lokomat
|Official title||Robotic Assessment of Lower Extremity|
|Principal investigator||Paolo Bonato, PhD|
|Description||Current rehabilitation assessment techniques make it difficult to monitor the day to day changes in patient functional abilities. In an ideal setting, one would like to be able to observe how subtle changes in the way that therapy is delivered affects the manner and the time it takes patients to learn the adaptations necessary to recover lost function. To this end, the investigators seek to apply a paradigm that has been used to study motor learning in the upper extremity (the FFAP) to the Lokomat gait orthosis platform. Over the last decade the FFAP has been used to elucidate the mechanisms and processes that contribute to motor learning in the upper extremity. The broad acceptance of this paradigm within the motor control community sets a precedent for application to the lower extremity and its use in clinical environments. Implementation of the FFAP in the Lokomat system will allow motor learning to be assessed during lower extremity motor tasks. Such a tool could be used to systemically assess the effectiveness of different aspects of therapy, such as the effects of training session duration, number of exercise repetitions, inter-trial (inter-session) intervals, and magnitude of perturbation. In this initial pilot, the investigators seek to apply our Lokomat implementation of the FFAP to healthy adult subjects in order to understand the feasibility of this approach and form a database of healthy subject learning rates. This initial step will allow us to bridge the scientific gap between lower extremity and upper limb motor learning research, while yielding data that can serve as a basis of comparison for future studies with patients. Additionally, such a methodology would suggest new avenues of research for lower limb motor learning and create an increased understanding of the motor principles that govern the spectrum of human movements. Ultimately, by understanding the fundamental motor learning principles that drive neurorehabilitation the investigators can better understand what makes rehabilitation successful and attempt to better improve current rehabilitation protocols. Before the testing session begins, the subject will be placed within the Lokomat by securing subjects at the trunk, pelvis, and lower extremities using adjustable cuffs with Velcro straps, so that the hip and knee joints are aligned to those of the Lokomat. Each testing session will begin with walking for approximately 5 minutes in the standard clinical mode of operation. Optional use of body weight support and foot straps can be used to ensure subject is walking comfortably within the Lokomat. Clinical mode allows subject to be walked by the Lokomat along a predefined trajectory with the pace of the treadmill matched to the robotic legs. After subject has acclimated to Lokomat walking, the motor learning experiments will begin. The format of the motor learning experiments is as follows: - "Free-run mode"- Subject walks as normally as possible within the Lokomat, while the Lokomat compensates for its own weight, but does not restrict the subject's movements. Subject's walking pattern is recorded as the baseline movements of the experiment. - Force field mode- Subject experiences small force perturbations from the Lokomat. These forces are perpendicular to their path (moving the foot upward), velocity dependent, and occur primarily in swing phase (when velocity is greatest). These forces are able to slightly alter the subject's walking trajectory. This generates error which drives the motor learning system and causes adaptation, which takes the form of compensatory forces equal and opposite to the force field. It is important to note that any forces outside the standard Lokomat safety range will not be experienced by the subject since the standard safety limits for clinical use remain present in the device. - Error clamp mode- Similar to the clinical mode, where the subject is limited to walking along a predefined trajectory, during the error clamp mode, the subject is required to walk along their average baseline trajectory (recorded during the Free-run mode), but can do so at the speed of their choosing. Error clamp trials are interspersed between force field trials, and used to measure adaptive compensatory forces. Any forces not used to move the subject along the path are instead compensatory forces that reflect the subject's adaptation. These forces can be measured throughout the experiment and used to infer the subjects' rate of learning.|
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