Machines Assisting Recovery From Stroke (MARS)
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|ClinicalTrials.gov Identifier: NCT02787694|
Recruitment Status : Recruiting
First Posted : June 1, 2016
Last Update Posted : November 9, 2017
|Condition or disease||Intervention/treatment||Phase|
|Cerebrovascular Disease; Sequelae||Other: Factor Targeted Walking Training Device: treadmill||Not Applicable|
Impairment in muscle strength is an important limiting factor in determining walking speed after stroke. There is a positive correlation between muscle strength and maximum gait speed (i.e. as muscles become stronger, maximum gait speed increases). Also, most stroke survivors walk at speeds that range from approximately 0.2 m/s to 0.8 m/s when asked to walk at a comfortable pace. These velocities are significantly lower than age-matched individuals (1.3 m/s to 1.4 m/s). Moreover, when stroke survivors were encouraged to walk at their self-selected maximum walking speed they achieved walking speeds from 0.3 m/s to 1.3 m/s, suggesting that stroke survivors have limited capability to adapt comfortable gait in order to increase walking speed to reach higher function.
Additionally, individuals with post-stroke hemiplegia are at high risk for falls due to poor balance and inability to tolerate environmental challenges. We have selected specific environmental hazards by turning to the current literature related to why people fall in the home or nonclinical environment. Research has identified specific risk factors for falls in people with stroke. Fallers have shown poorer balance, lower physical function measures than non-fallers, greater standing sway, impulsivity, and slowed response times, in addition to greater postural sway and reduced force generation when standing up and sitting down. Forster and Young found that fallers were more depressed and less socially active that non-fallers. They found that most falls occurred in patients' homes while walking or during transfers. Individuals reported loss of balance, getting their foot stuck, and difficulty performing transfers as reasons why they fell. Hyndman et. al, found that repeat fallers had significantly reduced arm function and activities of daily living (ADL) ability compared with those who did not fall.
A review concludes that the evidence supports a mix of approaches as a means for improving lower limb function during walking post-stroke. They concluded " . . . there is a need for high quality randomized trials and systematic reviews to determine the efficacy of clearly described individual techniques and task-specific requirements." However, Duncan and Dobkin argue that past mobility training approaches that focused on using either body-weight support treadmill training or robotic assistive training have failed to generate results that can justify their use for the mainstream stroke survivor . They cite two studies in particular, SCILT  and LEAPS , which produced conclusions that were not supportive of the extra effort and technology necessary to implement these protocols. One major suggestion from the authors was that a combinatorial approach should be implemented that incorporates strength training, aerobic training, and balance training. We agree with this suggestion and we propose to test this combinatorial approach in our study using a unique and innovative robotic system especially developed to combine exercises that target force, speed, balance, and locomotor challenge all within a single program.
As a result of previous funding, we have developed innovative protocols for assessing and treating mobility disability in chronic stroke survivors by using a unique robotic platform. The KineAssist- Mobility Activity Center (KA-MAC), developed by HDT Robotics (partners with this study), uses a patented force-sensing, pelvic support mechanism to sense the user's intended walking speed and direction to drive a moving surface, thus allowing a person to move at their own intended speed and pace. The device is sensitive enough to allow sudden starting and stopping movements, so that balance tasks and responses to sudden disturbances can be accommodated. This system is uniquely different compared to a treadmill, which only moves at a fixed speed and can only allow repetitive stepping protocols. In summary, we have developed a unique and innovative robotic system that can allow individuals to move at self-driven speeds against challenging conditions in order to implement a combinatorial approach to assessment and intervention.
|Study Type :||Interventional (Clinical Trial)|
|Estimated Enrollment :||30 participants|
|Intervention Model:||Single Group Assignment|
|Masking:||None (Open Label)|
|Official Title:||Machines Assisting Recovery From Stroke: Robotic Activity Mobility Center in a Fitness Center for People With Neurologic Disability|
|Study Start Date :||June 2013|
|Actual Primary Completion Date :||October 2017|
|Estimated Study Completion Date :||October 2018|
Experimental: Factor Targeted Walking Training
Individuals undergo 5x 2 week periods of targeted training based upon evaluation of walking factor results
Other: Factor Targeted Walking Training
Individuals walk on a treadmill for 30 minutes while exposed to either endurance, balance, challenge, strength, or speed focused approachesDevice: treadmill
- 10 m walk test [ Time Frame: 10 weeks ]
To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.
Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT02787694
|Contact: Program Coordinatorfirstname.lastname@example.org|
|United States, Alabama|
|Locomotor Control Lab||Recruiting|
|Birmingham, Alabama, United States, 35210|
|Contact: Program Coordinator 205-975-3592 email@example.com|