ArticleScientific reports2019
Age-dependent differences in learning to control a robot arm using a body-machine interface.
Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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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.
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Who cites it
8 citing papers in PubMed, 19 citations in OpenAlex.
- Human motor learning dynamics in high-dimensional tasks.PLoS computational biology · 2024Article
- Learning to Control Complex Robots Using High-Dimensional Body-Machine Interfaces.ACM transactions on human-robot interaction · 2024Article
- A Non-Linear Body Machine Interface for Controlling Assistive Robotic Arms.IEEE transactions on bio-medical engineering · 2023Article
- Development of a Vision-Guided Shared-Control System for Assistive Robotic Manipulators.Sensors (Basel, Switzerland) · 2022Article
- Recovery of Distal Arm Movements in Spinal Cord Injured Patients with a Body-Machine Interface: A Proof-of-Concept Study.Sensors (Basel, Switzerland) · 2021Article
- Article
- Providing low-dimensional feedback of a high-dimensional movement allows for improved performance of a skilled walking task.Scientific reports · 2019Article
- Online and offline contributions to motor learning change with practice, but are similar across development.Experimental brain research · 2019Article
Corrections and comments
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Body-machine interfaces, i.e. interfaces that rely on body movements to control external assistive devices, have been proposed as a safe and robust means of achieving movement and mobility; however, how children learn these novel interfaces is poorly understood. Here we characterized the learning of a body-machine interface in young unimpaired adults, two groups of typically developing children (9-year and 12-year olds), and one child with congenital limb deficiency. Participants had to control the end-effector of a robot arm in 2D using movements of the shoulder and torso. Results showed a striking effect of age - children had much greater difficulty in learning the task compared to adults, with a majority of the 9-year old group unable to even complete the task. The 12-year olds also showed poorer task performance compared to adults (as measured by longer movement times and greater path lengths), which were associated with less effective search strategies. The child with congenital limb deficiency showed superior task performance compared to age-matched children, but had qualitatively distinct coordination strategies from the adults. Taken together, these results imply that children have difficulty learning non-intuitive interfaces and that the design of body-machine interfaces should account for these differences in pediatric populations.
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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.