We are developing a set of machine learning softwares and hardware using various physiological signals from human body to generate actionable commands, that enables users, both able and disabled to seamlessly and intuitively interact with the surroundings. EXGwear is aiming at developing promising solutions that give human extra controllability and augment sensing abilities to communicate with the world. It can solve various kinds of problems, from helping disabled people interact with the environment as assistive tools, to simplifying the current complicated/cumbersome control devices to enable a natural way of interaction with the smart-home/industrial IoTs/robotic devices and XR displays "hands-free" using facial gestures.

We have recently developed working prototypes for our EXG technologies using brain-computer interface (BCI) and proprietary machine learning platforms. Our device - EXGbuds (please see our product pitch video here at: youtu.be/50G_CJxmcvY) provide...
We are developing a set of machine learning softwares and hardware using various physiological signals from human body to generate actionable commands, that enables users, both able and disabled to seamlessly and intuitively interact with the surroundings. EXGwear is aiming at developing promising solutions that give human extra controllability and augment sensing abilities to communicate with the world. It can solve various kinds of problems, from helping disabled people interact with the environment as assistive tools, to simplifying the current complicated/cumbersome control devices to enable a natural way of interaction with the smart-home/industrial IoTs/robotic devices and XR displays "hands-free" using facial gestures.

We have recently developed working prototypes for our EXG technologies using brain-computer interface (BCI) and proprietary machine learning platforms. Our device - EXGbuds (please see our product pitch video here at: youtu.be/50G_CJxmcvY) provides miniature sensors along with the machine learning physiological activity identification method, which allows “Hands-Free” control of smart devices using simple eye movements and facial gestures. Our innovation places two simple non-invasive electrodes on the side of the face to identify eye movement activity with over 95% accuracy. With voice cue instructions, users can then quickly learn how to control different applications, such as a surgical robot, wheel chair, cell phone, smart home, or other Internet of Things (IoT) devices with just simple eye/facial gestures.

We envision that in the next 5 years, the complementary technologies in AR, VR and smart-home devices will rapidly grow and numerous innovations in these field will accelerate the innovation-powered economy and a multi-billion $ market potential in consumer electronics. This will also change the way we interact with our surroundings and the devices we currently use.

Current assistive devices are often cumbersome, bulky, invasive, and intrusive to users, causing slower adoption of BCI-enabled wearables. To truly harness the potential of wearable IoTs, it is highly imminent to develop and design non-obtrusive, simple, compact and human-centered products that users can wear for long hours with utmost comfort. EXGbuds offer solution to all these problems through simple, accurate, user-friendly wearables. Our project has earned several international awards by IEEE (Canada), ICRA (Australia), Japan & China.
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