ArticleJournal of neuroengineering and rehabilitation2020
Using force data to self-pace an instrumented treadmill and measure self-selected walking speed.
Article in Journal of neuroengineering and rehabilitation, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 28 citations in OpenAlex.
- Validation of Dynamic Bayesian Optimization for Human-in-the-Loop Optimization of Exoskeleton Control at User-Driven Walking Speed.bioRxiv : the preprint server for biology · 2026Article
- Dual-task gait assessment using n-back testing during self-paced treadmill walking in virtual reality: reliability and baseline characterisation for future clinical application.Frontiers in human neuroscience · 2026Article
- Effects of Belt Accelerations During Push-Off on Propulsion Mechanics in Individuals Post-Stroke.IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society · 2026Article
- Development of Control Algorithms for an Adaptive Running Platform for a Musculoskeletal Rehabilitation System.Sensors (Basel, Switzerland) · 2025Article
- Robotic Ankle Exoskeleton and Limb Angle Biofeedback for Assisting Stroke Gait: A Feasibility Study.IEEE robotics and automation letters · 2025Article
- Cross-step detection using center-of-pressure based algorithm for real-time applications.Journal of neuroengineering and rehabilitation · 2024Article
- Optimizing exoskeleton assistance to improve walking speed and energy economy for older adults.Journal of neuroengineering and rehabilitation · 2024Article
- Quantifying walking speeds in relation to ankle biomechanics on a real-time interactive gait platform: a musculoskeletal modeling approach in healthy adults.Frontiers in bioengineering and biotechnology · 2024Article
- Selected movement and force pattern differences in rail- and rung-climbing of fire apparatus aerial ladders at 52.5° slope.Applied ergonomics · 2022Article
- Optimized hip-knee-ankle exoskeleton assistance at a range of walking speeds.Journal of neuroengineering and rehabilitation · 2021Article
- Novel velocity estimation for symmetric and asymmetric self-paced treadmill training.Journal of neuroengineering and rehabilitation · 2021Article
- Optimizing Exoskeleton Assistance for Faster Self-Selected Walking.IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society · 2021Article
- Speed-related but not detrended gait variability increases with more sensitive self-paced treadmill controllers at multiple slopes.PloS one · 2021Article
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
backgroundSelf-selected speed is an important functional index of walking. A self-pacing controller that reliably matches walking speed without additional hardware can be useful for measuring self-selected speed in a treadmill-based laboratory.
methodsWe adapted a previously proposed self-pacing controller for force-instrumented treadmills and validated its use for measuring self-selected speeds. We first evaluated the controller's estimation of subject speed and position from the force-plates by comparing it to those from motion capture data. We then compared five tests of self-selected speed. Ten healthy adults completed a standard 10-meter walk test, a 150-meter walk test, a commonly used manual treadmill speed selection test, a two-minute self-paced treadmill test, and a 150-meter self-paced treadmill test. In each case, subjects were instructed to walk at or select their comfortable speed. We also assessed the time taken for a trial and a survey on comfort and ease of choosing a speed in all the tests.
resultsThe self-pacing algorithm estimated subject speed and position accurately, with root mean square differences compared to motion capture of 0.023 m s
conclusionsThe self-paced force-instrumented treadmill well adapts to subject walking speed and reliably measures self-selected walking speeds. We provide the self-pacing software to facilitate use by gait researchers and clinicians.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.