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Related Experiment Video

Updated: Sep 28, 2025

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface

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Decoding Intent With Control Theory: Comparing Muscle Versus Manual Interface Performance.

Momona Yamagami¹, Katherine M Steele¹, Samuel A Burden¹

¹University of Washington Seattle, WA.

Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. CHI Conference

|March 28, 2022

Summary

This summary is machine-generated.

Muscle interfaces offer better performance for continuous tasks compared to manual control, especially for complex activities like driving. This technology may improve device interaction for individuals with motor impairments.

Keywords:

Human-centered computing → User models User intent User studies accessibility control theory electromyography interaction motor impairments muscle interfaces

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Last Updated: Sep 28, 2025

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Published on: May 8, 2021

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Area of Science:

Human-Computer Interaction
Rehabilitation Engineering
Assistive Technology

Background:

Manual device interaction demands fine motor skills, posing challenges for individuals with motor impairments.
Muscle interfaces present an alternative interaction method, but their efficacy in continuous tasks remains unevaluated.
Control theory offers a framework to analyze user performance by distinguishing intent from error correction.

Purpose of the Study:

To compare the effectiveness of manual versus muscle interfaces for continuous tasks.
To quantify the impact of motor impairments on device interaction using control theory.
To assess user preference and performance across different task complexities.

Main Methods:

Evaluated manual and muscle interfaces with eleven unimpaired users and three users with motor impairments.
Utilized control theory to separate user input into intent and error correction components.
Assessed performance in both simple (e.g., mouse tracking) and complex (e.g., driving) continuous tasks.

Main Results:

Both unimpaired and motor-impaired users preferred and performed better with the muscle interface.
The performance advantage of the muscle interface was particularly evident in the complex continuous task (driving).
Muscle interfaces demonstrated enhanced usability for continuous device control.

Conclusions:

Muscle interfaces show significant potential for improving device interaction, especially for continuous tasks.
Algorithms that detect and augment user intent within muscle interfaces could be crucial for future designs.
These findings suggest muscle interfaces are a promising avenue for enhancing usability for individuals with motor impairments.