Understanding how demographic characteristics impact the level of physical activity children with neuromotor impairments experience while using a robot-assisted walker
Youngblood, J. L.; Zaplachinski, M.; Shen, H.; Condliffe, E. G.
Show abstract
Importance: There are very few interventions designed for individuals with the most severe mobility impairments. Robotic walking may be an effective way to facilitate exercise in this population. Objective: To examine how robot-assisted walkers physical parameters and user characteristics moderate the exercise intensity achieved by individuals with neuromotor disorders causing mobility impairments. Design: A prospective study. Intervention: A single-session intervention involving an overground robot-assisted walker that can be used in an endurance mode requiring no voluntary movement or a strength mode during which voluntary movement could impact the gait pattern. Participants: Individuals with pediatric-onset mobility impairments Main Outcome Measures: Participants were characterized based on their age, sex, diagnosis, and Gilette Functional Assessment Questionnaire (FAQ) levels. Heart rate during the final minute of four 5-minute walking conditions: strength mode at fast speed, strength mode at slow speed, endurance mode at fast speed and endurance mode at slow speed was expressed as a percentage of each participant heart rate reserve (%HRR). Linear mixed-effects models were used to evaluate the impact of speed, device mode and user characteristics on the level of exercise achieved. Results: 29 individuals (aged 2-26 years) with mobility impairments (FAQ levels 1-6) completed this study. Fast speeds were associated with a higher %HRR (beta= 2.11, SE = 1.03, p = 0.044). Participants in FAQ class 1 exhibited significantly higher %HRR compared with those in FAQ classes 2 and 3 (beta=18.6, SE=7.31, p=0.017; beta= 16.9, SE = 8.13, p = 0.047, respectively). No other device or participant characteristics were associated with exercise intensity. Conclusions: To facilitate higher exercise levels, users of robot-assisted walkers can increase their speed. Individuals who cannot take steps due to their neuromotor impairments experience the highest levels of exercise. Relevance: The findings in this study highlight the promise of robot-assisted walkers to improve health, particularly in those who often face the greatest barriers to exercise.
Matching journals
The top 3 journals account for 50% of the predicted probability mass.
Similar papers in this journal
Similar papers in this journal
- Randomized, Crossover Clinical Trial on the Safety, Feasibility, and Usability of the ABLE Exoskeleton: A Comparative Study with Knee-Ankle-Foot Orthoses 95%
- An inertial sensor-based comprehensive analysis of manual wheelchair user mobility during daily life in people with SCI 95%
- Biomechanical effects of adding an articulating toe joint to a passive foot prosthesis for incline and decline walking 95%
Similar papers in this journal
- Does increased gait variability improve stability when faced with an expected balance perturbation during treadmill walking? 95%
- The relationship between gait asymmetry and stability in people with sub-acute stroke 94%
- Slow walking synergies reveal a functional role for arm swing asymmetry in healthy adults: a principal component analysis with relation to mechanical work. 94%
Similar papers in this journal
- Does the margin of stability measure predict stability of gait with a constrained base of support? 96%
- Effects of interval treadmill training on spatiotemporal parameters in children with cerebral palsy: a machine learning approach 95%
- Repeatability of gait of children with spastic cerebral palsy in different walking conditions 95%
Similar papers in this journal
- Gait adaptation to asymmetric hip stiffness applied by a robotic exoskeleton 96%
- Application of a novel force-field to manipulate the relationship between pelvis motion and step width in human walking 94%
- Effects of targeted assistance and perturbations on the relationship between pelvis motion and step width in people with chronic stroke 94%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.