Non-invasive control interfaces for intention detection in active movement-assistive devices

Area of Science:

• Biomedical Engineering
• Rehabilitation Technology
• Human-Computer Interaction

Background:

• Active movement-assistive devices enhance life quality for individuals with neuromusculoskeletal disorders.
• Effective device operation relies on control interfaces detecting user movement intentions.
• A diverse range of invasive and non-invasive control interfaces have been developed.

Purpose of the Study:

• To provide a comprehensive review of non-invasive control interfaces for active movement-assistive devices.
• To introduce a novel systematic classification method for these interfaces.
• To outline current challenges and future research directions.

Main Methods:

• Systematic literature review of non-invasive control interfaces.
• Development of a novel classification framework based on signal source, physiological phenomena, and sensor type.
• Categorization of existing control interfaces using the proposed framework.

Main Results:

• A systematic classification method is proposed, categorizing interfaces by signal origin, physiological basis, and sensing technology.
• The classification successfully encompasses all current non-invasive control interface strategies.
• Each sensing modality is described within the established classification structure.

Conclusions:

• The proposed classification provides a structured overview of non-invasive control interfaces for assistive devices.
• This framework aids in understanding the state-of-the-art and identifying research gaps.
• Further research should address design considerations, challenges, and future directions in this field.