The Neurotech application team works at the intersection of basic neuroscience research and its application in industry. We provide services that combine neuroscience and Araya’s advanced AI technology to support our customers. Also, we developed products that utilized AI technology to access mental states with non-invasive brain data. We care about human welfare and aim to break through the limitation of the human body and brain.
Members
Shuntaro is a Team Leader of the Neurotechnology R&D unit at Araya Inc. After graduating from the College of Arts and Sciences at the University of Tokyo in 2008, he received his Ph.D. in the Graduate School of Education at the University of Tokyo in 2013. Since 2013, he is a member of the Center for Sleep and Consciousness at the University of Wisconsin at Madison. His research interests are in understanding the brain-consciousness relationship and developing brain-machine interface techniques enabling cross-brain communications. Currently, he focuses on modeling the brain’s wiring architectures supporting conscious experience and cognitive functions.
Chiaki is a business development officer in Araya. After graduating from Hokkaido University in 2011, she received her M.S. in Kyoto University in 2013.
She worked as a researcher and business developer in Dermatology, Oral health care for 9 years in a consumables manufacturer company. She joined Araya in 2022. Now she focuses on business development in neuroscience.
Nomura is a researcher at Araya. In his previous job, he has been studying pain using EEG. His research interests include neurotech using EEG and deep learning.
Yi-Chen is a post-doctoral researcher at Araya. She received her Ph.D. at National Yang-Ming University in 2019. Her research interest are cognitive neuroscience and neuroimaging.
Masaru received his Ph.D. in cognitive neuroscience from Osaka University. After his postdoc research in neuroeconomics, he joined Araya in 2019. His research interests are consciouness, AI inspired neurosicence and application of neuroTech.
Anna is a Junior Researcher at Araya. She received her B.S. in Computer Science at the University of Wisconsin - Madison in 2019, and her M.S. in Information Science & Technology at Hokkaido University in 2022. Her research interests are natural language processing and artificial consciousness.
Highlights
Brain activity estimation from facial video
NeuroTech (also called BrainTech) is a rising field of industrial application of Neuroscience. In this field, non-invasive recording of brain activity plays a pivotal role, and for that purpose Electroencephalography (EEG) is widely used because of its higher time resolution, wearability, and cost-effectiveness. Nonetheless, even wearable EEG devices are hard to implement in some real-life (working) situations. Thus, our team developed a system that estimates a frequency-specific EEG power from the facial feature captured by a conventional digital camera, by harnessing the power of deep learning (patent applied for). The video on the left shows an example of estimation by our system. Here, the target is the power of delta-wave, which has a strong relation with wakefulness/sleepiness. The blue line shows an actual recording from an EEG system and an orange line shows estimation from facial video. We will develop various products/solutions based on this technology, including drowsiness detection and alert systems for drivers and workers.
Brain Machine Interface (BMI)
While brain-sensing technologies enable us to objectively access our own mental state through brain activities, another NeuroTech technology enables us to control robotic arms or computer devices by our will. This technology field is called Brain-Machine Interface (BMI) or Brain-Computer Interface (BCI). In Araya, we are working on this technology too. The video on the left shows an example of our development. Here, one of our staff is controlling a racing car on the screen by his EEG, without touching a controller. This is achieved by detecting EEG activity evoked by visual stimuli that change in specific frequencies (Steady State Visual Evoked Potential： SSVEP). Only for demonstration purposes, the staff is indicating which direction he intends to turn with his finger. Through developing versatile BMI/BCI algorithms and compact wearable EEG devices (in collaboration with VIE STYLE, Inc.), we aim to quickly realize a future in which anyone can operate any device directly from the brain in a hands-free manner.