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Biomimetic versus arbitrary motor control strategies for bionic hand skill learning
Hunter R Schone1,2,3,4, Malcolm Udeozor5, Mae Moninghoff5
1Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA. schonehunter@gmail.com.
Nature Human Behaviour
|March 19, 2024
Summary
Biomimetic control offers faster initial learning for bionic hands, but arbitrary control leads to better long-term adaptation and generalization. A flexible strategy combining both may be optimal for bionic limb control.
Area of Science:
- Biomedical Engineering
- Neuroscience
- Rehabilitation Robotics
Background:
- Designing anthropomorphic bionic limbs that mimic biological control (biomimetic) is an engineering goal.
- It is assumed biomimetic control enhances embodiment, learning, generalization, and automaticity in users.
- However, the effectiveness of biomimetic versus non-biomimetic strategies requires empirical testing.
Purpose of the Study:
- To compare biomimetic and arbitrary control strategies for learning to use a myoelectric bionic hand.
- To evaluate motor learning, embodiment, and generalization in non-disabled participants under different control conditions.
Main Methods:
- Participants learned to control a wearable myoelectric bionic hand using an eight-channel electromyography pattern-recognition system.
- Two training groups were compared: biomimetic (mimicking gestures) and arbitrary control (unrelated gestures).
- Motor learning was assessed across days and behavioral tasks.
Main Results:
- Both groups showed improved bionic hand control, reduced cognitive load, and increased embodiment.
- Biomimetic control resulted in more intuitive and faster initial learning.
- Arbitrary control users matched biomimetic performance later and demonstrated superior generalization to new control strategies.
Conclusions:
- Biomimetic and arbitrary control strategies offer distinct advantages for bionic limb use.
- The optimal control strategy is likely a flexible approach along the biomimetic-arbitrary spectrum, tailored to individual user needs and training contexts.
