ArticleMyoelectric Controls and Upper Limb Prosthetics Symposium2022
SHARED-CONTROL DECREASES THE PHYSICAL AND COGNITIVE DEMANDS OF MAINTAINING A SECURE GRIP.
Article in Myoelectric Controls and Upper Limb Prosthetics Symposium, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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.
The trial behind it
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Who cites it
4 citing papers in PubMed.
- Shared human-machine control of an intelligent bionic hand improves grasping and decreases cognitive burden for transradial amputees.Nature communications · 2025Article
- Quantifying the Cognitive Demand of Controlling a Prosthesis with a Secondary Detection Response Task.Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · 2025Article
- Electromyographically controlled prosthetic wrist improves dexterity and reduces compensatory movements without added cognitive load.Scientific reports · 2024Article
- Context-informed incremental learning improves both the performance and resilience of myoelectric control.Journal of neuroengineering and rehabilitation · 2024Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Upper-limb amputees commonly cite difficulty of control as one of the main reasons why they abandon their prostheses. Combining myoelectric control with autonomous sensor-based control could improve prosthesis control. However, the cognitive and physical impact of shared control and semi-autonomous systems on users has yet to be fully explored. In this study we introduce a novel shared-control algorithm that blends proportional position control predicted from electromyography (EMG) with proportional position control predicted from an autonomous machine using infrared sensors embedded in the prosthetic hand's fingers to detect the distance to objects. The user's EMG control is damped in proportion to the machine's prediction of an object's position in relation to a given finger. The shared-control algorithm was validated using three intact individuals completing a holding task where they attempted to hold an object for as long as possible without dropping it. Shared control resulted in fewer object drops, 32% less cognitive demand, and 49% less physical effort (measured by EMG) relative to the participant's EMG control alone. These results indicate that shared control can reduce the physiological burdens on the user as well as increase prosthetic control.
Identifiers
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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.