Toru Imai

Papers

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About

Toru Imai is a researcher at the frontier of human-robot interaction and healthcare technology, with a primary focus on developing intelligent robotic systems for geriatric care and emergency medical detection. His most impactful work centers on using ubiquitous sensing and social robots to assess cognitive health, particularly through his highly cited 2019 paper "Dementia Scale Classification Based on Ubiquitous Daily Activity and Interaction Sensing" (14 citations). In this study, Imai pioneered a novel approach that integrates indoor daily activity monitoring with humanoid robot interaction patterns to automatically predict dementia severity scores, offering a non-invasive, continuous assessment method that could revolutionize early dementia screening. He further expanded the clinical utility of social robots in his 2020 work on "Stroke Signs Detection System by SNS Agency Robot" (2 citations), where he implemented the Cincinnati Prehospital Stroke Scale (CPSS) within a communication robot. This system leverages cloud-based AI to analyze real-time video during human-robot conversations, enabling automatic detection of stroke symptoms. Imai's contributions are particularly notable for bridging the gap between ambient assisted living technologies and clinical diagnostic tools, demonstrating how everyday robotic interactions can serve as powerful, accessible platforms for both cognitive and neurological health monitoring.