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- Source :
- HRI (Companion)
- Publication Year :
- 2018
- Publisher :
- ACM, 2018.
-
Abstract
- Current assistive technologies need complicated, cumbersome, and expensive equipment, which are not user-friendly, not portable, and often require extensive fine motor control. Our approach aims at solving these problems by developing, a compact, non-obtrusive and ergonomic wearable device, to measure signals associated with human physiological gestures, and thereafter generate useful commands to interact with the environment. Our innovation uses machine learning and non- invasive biosensors on top of the ears to identify eye movements and facial expressions with over 95% accuracy. Users can control different applications, such as a robot, powered wheelchair, cell phone, smart home, or other Internet of Things (IoT) devices. Combined with VR headset and hand gesture recognition devices, user can use our technology to control a camera-mounted robot (e.g., telepresence robot, drones, or any robotic manipulator) to navigate around the environment in first-person's view simply by eye movements and facial expressions. It enables a human- intuitive way of interaction totally 'touch-free'. The experimental results show satisfactory performance in different applications, which can be a powerful tool to help disabled people interact with the environment and measure other physiological signals as a universal controller and health monitoring device.
- Subjects :
- 030506 rehabilitation
Telerobotics
business.industry
Computer science
05 social sciences
Wearable computer
050105 experimental psychology
Human–robot interaction
03 medical and health sciences
Human–computer interaction
Gesture recognition
Teleoperation
Robot
0501 psychology and cognitive sciences
0305 other medical science
business
Wearable technology
Gesture
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- Companion of the 2018 ACM/IEEE International Conference on Human-Robot Interaction
- Accession number :
- edsair.doi...........2afb3c5b5e4625bfdf5ceddaa5849b2a
- Full Text :
- https://doi.org/10.1145/3173386.3177836