Soft Wireless Headband Bioelectronics and Electrooculography for Persistent Human–Machine Interfaces
Source abstract
Abstract
Recent advances in wearable technologies have enabled ways for people to interact with external devices, known as human-machine interfaces (HMIs). Among them, electrooculography (EOG), measured by wearable devices, is used for eye movement-enabled HMI. Most prior studies have utilized conventional gel electrodes for EOG recording. However, the gel is problematic due to skin irritation, while separate bulky electronics cause motion artifacts. Here, we introduce a low-profile, headband-type, soft wearable electronic system with embedded stretchable electrodes, and a flexible wireless circuit to detect EOG signals for persistent HMIs. The headband with dry electrodes is printed with flexible thermoplastic polyurethane. Nanomembrane electrodes are prepared by thin-film deposition and laser cutting techniques. A set of signal processing data from dry electrodes demonstrate successful real-time classification of eye motions, including blink, up, down, left, and right. Our study shows that the convolutional neural network performs exceptionally well compared to other machine learning methods, showing 98.3% accuracy with six classes: the highest performance till date in EOG classification with only four electrodes. Collectively, the real-time demonstration of continuous wireless control of a two-wheeled radio-controlled car captures the potential of the bioelectronic system and the algorithm for targeting various HMI and virtual reality applications.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Gaze Tracking and Assistive Technology · Advanced Sensor and Energy Harvesting Materials · EEG and Brain-Computer Interfaces
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Engineering and Computer Science, Washington State University, Vancouver, Washington 98686, United States
IEN Center for Human-Centric Interfaces and Engineering at the Institute for Electronics and Nanotechnology, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
George W. Woodruff School of Mechanical Engineering, College of Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York 10029, United States
Department of Otolaryngology Head and Neck Surgery, School of Medicine, Chungnam National University Hospital, Daejeon 35015, Republic of Korea
Department of Mechanical Engineering, University of Washington, Seattle, Washington 98195, United States
Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University School of Medicine, Atlanta, Georgia 30332, United States
Parker H. Petit Institute for Bioengineering and Biosciences, Institute for Materials, Neural Engineering Center, Institute for Robotics and Intelligent Machines, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
Funding
Georgia Institute of Technology · Korea Medical Device Development Fund · Division of Chemical, Bioengineering, Environmental, and Transport Systems
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