ArticleJournal of neuroengineering and rehabilitation2011
Controlling patient participation during robot-assisted gait training.
Article in Journal of neuroengineering and rehabilitation, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
21 citing papers in PubMed, 1 synthesis or guideline pooled it, 84 citations in OpenAlex.
- Control strategies used in lower limb exoskeletons for gait rehabilitation after brain injury: a systematic review and analysis of clinical effectiveness.Journal of neuroengineering and rehabilitation · 2023Pooled it
- Assessment-driven selection and adaptation of exercise difficulty in robot-assisted therapy: a pilot study with a hand rehabilitation robot.Journal of neuroengineering and rehabilitation · 2014Trial
- Cardiopulmonary exercise testing early after stroke using feedback-controlled robotics-assisted treadmill exercise: test-retest reliability and repeatability.Journal of neuroengineering and rehabilitation · 2014Trial
- Artificial intelligence tools for engagement prediction in neuromotor disorder patients during rehabilitation.Journal of neuroengineering and rehabilitation · 2024Article
- Robotic exoskeleton-assisted walking rehabilitation for stroke patients: a bibliometric and visual analysis.Frontiers in bioengineering and biotechnology · 2024Review
- Robot-assisted gait training in patients with various neurological diseases: A mixed methods feasibility study.PloS one · 2024Article
- Efficacy and Safety Study of Wearable Cyborg HAL (Hybrid Assistive Limb) in Hemiplegic Patients With Acute Stroke (EARLY GAIT Study): Protocols for a Randomized Controlled Trial.Frontiers in neuroscience · 2021Article
- Challenges and solutions for application and wider adoption of wearable robots.Wearable technologies · 2021Review
- Classification of Multiple Psychological Dimensions in Computer Game Players Using Physiology, Performance, and Personality Characteristics.Frontiers in neuroscience · 2019Article
- Robotic Rehabilitation and Spinal Cord Injury: a Narrative Review.Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics · 2018Review
- A multisession evaluation of an adaptive competitive arm rehabilitation game.Journal of neuroengineering and rehabilitation · 2017Article
- Difficulty adaptation in a competitive arm rehabilitation game using real-time control of arm electromyogram and respiration.IEEE ... International Conference on Rehabilitation Robotics : [proceedings] · 2017Article
- Differences in muscle activity and temporal step parameters between Lokomat guided walking and treadmill walking in post-stroke hemiparetic patients and healthy walkers.Journal of neuroengineering and rehabilitation · 2017Article
- Improving Challenge/Skill Ratio in a Multimodal Interface by Simultaneously Adapting Game Difficulty and Haptic Assistance through Psychophysiological and Performance Feedback.Frontiers in neuroscience · 2017Article
- Article
- Assist-as-Needed Robot-Aided Gait Training Improves Walking Function in Individuals Following Stroke.IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society · 2015Article
- Neurophysiology of robot-mediated training and therapy: a perspective for future use in clinical populations.Frontiers in neurology · 2013Review
- Technological advances in interventions to enhance poststroke gait.Physical medicine and rehabilitation clinics of North America · 2013Review
- Kinematic, muscular, and metabolic responses during exoskeletal-, elliptical-, or therapist-assisted stepping in people with incomplete spinal cord injury.Physical therapy · 2012Article
- Should body weight-supported treadmill training and robotic-assistive steppers for locomotor training trot back to the starting gate?Neurorehabilitation and neural repair · 2012Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe overall goal of this paper was to investigate approaches to controlling active participation in stroke patients during robot-assisted gait therapy. Although active physical participation during gait rehabilitation after stroke was shown to improve therapy outcome, some patients can behave passively during rehabilitation, not maximally benefiting from the gait training. Up to now, there has not been an effective method for forcing patient activity to the desired level that would most benefit stroke patients with a broad variety of cognitive and biomechanical impairments.
methodsPatient activity was quantified in two ways: by heart rate (HR), a physiological parameter that reflected physical effort during body weight supported treadmill training, and by a weighted sum of the interaction torques (WIT) between robot and patient, recorded from hip and knee joints of both legs. We recorded data in three experiments, each with five stroke patients, and controlled HR and WIT to a desired temporal profile. Depending on the patient's cognitive capabilities, two different approaches were taken: either by allowing voluntary patient effort via visual instructions or by forcing the patient to vary physical effort by adapting the treadmill speed.
resultsWe successfully controlled patient activity quantified by WIT and by HR to a desired level. The setup was thereby individually adaptable to the specific cognitive and biomechanical needs of each patient.
conclusionBased on the three successful approaches to controlling patient participation, we propose a metric which enables clinicians to select the best strategy for each patient, according to the patient's physical and cognitive capabilities. Our framework will enable therapists to challenge the patient to more activity by automatically controlling the patient effort to a desired level. We expect that the increase in activity will lead to improved rehabilitation outcome.
Indexed as
Identifiers
What OpenQuestion holds
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.