Conference proceeding
Cognitive-Motor Processes During Arm Reaching Performance Through a Human Body-Machine Interface
FOUNDATIONS OF AUGMENTED COGNITION, AC 2015, v 9183, pp 381-392
01 Jan 2015
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Head controlled based systems represent a class of human body-machine interfaces that employ head motion to control an external device. Overall, the related work has focused on technical developments with limited user performance assessments while generally ignoring the underlying motor learning and cognitive processes. Thus, this study examined, during and after practice, the cognitive-motor states of users when controlling a robotic arm with limited head motion under various control modalities. As a first step, two groups having a different degree of control of the arm directions were considered. The preliminary results revealed that both groups: (i) similarly improved their reaching performance during practice; (ii) provided, after practice, a similar performance generalization while still relying on visual feedback and (iii) exhibited similar cognitive workload. This work can inform the human cognitive-motor processes during learning and performance of arm reaching movements as well as develop rehabilitation systems for disabled individuals.
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Details
- Title
- Cognitive-Motor Processes During Arm Reaching Performance Through a Human Body-Machine Interface
- Creators
- Rodolphe J. Gentili - University of Maryland, College ParkIsabelle M. Shuggi - University of Maryland, College ParkKristen M. King - University of Maryland, College ParkHyuk Oh - University of Maryland, College ParkPatricia A. Shewokis - Drexel University
- Contributors
- D D Schmorrow (Editor)C M Fidopiastis (Editor)
- Publication Details
- FOUNDATIONS OF AUGMENTED COGNITION, AC 2015, v 9183, pp 381-392
- Series
- Lecture Notes in Artificial Intelligence
- Publisher
- Springer Nature
- Number of pages
- 12
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Nutrition Sciences
- Web of Science ID
- WOS:000364809400036
- Scopus ID
- 2-s2.0-84947262689
- Other Identifier
- 991019167915104721
UN Sustainable Development Goals (SDGs)
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- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Computer Science, Artificial Intelligence
- Computer Science, Information Systems