EXGbuds

Product Description

EXGbuds is a compact headset/earbud that generates actionable commands from simple eye movements and facial gestures. It allows users to interact with surrounding smart devices hands-free.

Target SDGs

SDG 3: Good Health and Well-Being

SDG 9: Industry, Innovation and Infrastructure

Target Users (Target Impact Group)

Household

Distributors / Implementing Organizations

EXG-wear

Manufacturing/Building Method

EXGbuds consists of customizable hardware and software, with biosensors placed on top of the ears combined with machine learning algorithms to measure various physiological signals to satisfy a variety of user needs. The team developed their own patented Electroencephalogram (EEG) dry electrode sensors and microscale Bluetooth communication modules.

Intellectural Property Type

Trademark

User Provision Model

Directly from manufacturer

Distributions to Date Status

Unknown

Telecommunication service required (Y/N)

Communication protocol used

Bluetooth

Permanent network connectivity required (Y[specify]/N)

Type of data collected

Raw signals of eye and facial activities

Propietary hardware used (Y/N)

Yes

Sensors used (Y/N)

Yes, the device uses non-invasive biosensors

Open source code (Y/N)

Open source data (Y/N/ Other)

Operating system and version

Unknown

Power requirements

Unknown

Application

Assistive technologies, smart devices, virtual reality

Remote system diagnostics available (Y/N)

Design Specifications

By placing sensors and electronic modules in a compact and ergonomic way, EXGbuds provides a human-centered product design. Users can customize their own ergonomic design to place sensors at different locations to measure different physiological signals.

Product Schematics

Technical Support

From manufacturer

Replacement Components

None

Lifecycle

Unknown

Manufacturer Specified Performance Parameters

Assist people with disabilities and improve productivity with augmented sensing.

Vetted Performance Status

The classification of the eye and facial gestures under the developed machine learning algorithm can reach to above 95% accuracy.

Safety

N/A

Complementary Technical Systems

None

Academic Research and References

Wang, K. J., Tung, H. W., Huang, Z., Thakur, P., Mao, Z. H. and You, M. X., 2018, EXGbuds: Universal Wearable Assistive Device for Disabled People to Interact with the Environment Seamlessly, Companion of the 2018 ACM/IEEE International Conference on Human-Robot Interaction, pp. 369-370.

Wang, K. J., Liu, Q., Zhao, Y., Zheng, C. Y., Vhasure, S., Liu, Q. and Mao, Z. H., 2018, Intelligent Wearable Virtual Reality (VR) Gaming Controller for People with Motor Disabilities, 2018 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR), pp. 161-164.

Wang, K. J., You, K., Chen, F., Thakur, P., Urich, M., Vhasure, S. and Mao, Z. H., 2018, Development of Seamless Telepresence Robot Control Methods to Interact with the Environment Using Physiological Signals, in Companion of the 2018 ACM/IEEE International Conference on Human-Robot Interaction, pp. 44-44.

Wang, K. J., Zhang, A., You, K., Chen, F., Liu, Q., Liu, Y. and Mao, Z. H. , 2018, Ergonomic and Human-Centered Design of Wearable Gaming Controller Using Eye Movements and Facial Expressions, 2018 IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW), pp. 1-5.

Wang, K. J., Liu, Q., Vhasure, S., Liu, Q., Zheng, C. Y. and Thakur, P., 2018, EXG Wearable Human-Machine Interface for Natural Multimodal Interaction in VR Environment, Proceedings of the 24th ACM Symposium on Virtual Reality Software and Technology, p.49.

Home. (n.d.). EXG Wear. Retrieved June 29, 2024, from https://www.exg-wear.com

Modern Workplace. (n.d.). DXC Technology. Retrieved June 29, 2024, from https://dxc.com/us/en/offerings/modern-workplace

Goal 3. (n.d.). Sdgs.Un.Org. Retrieved June 29, 2024, from https://sdgs.un.org/goals/goal3

Goal 9. (n.d.). Sdgs.Un.Org. Retrieved June 29, 2024, from https://sdgs.un.org/goals/goal9

Shop. (n.d.). EXG Wear. Retrieved June 29, 2024, from https://www.exg-wear.com/shop

Wang, K.-J., Tung, H.-W., Huang, Z., Thakur, P., Mao, Z.-H., & You, M.-X. (2018). EXGbuds: Universal wearable assistive device for disabled people to interact with the environment seamlessly. Companion of the 2018 ACM/IEEE International Conference on Human-Robot Interaction, 369–370. https://dl.acm.org/doi/10.1145/3173386.3177836

Compliance with regulations

Unknown

Evaluation methods

Academic research: several papers evaluated the accuracy of the machine learning algorithm that classifies human gestures into interaction with the device.

Other Information

None

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