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Bernard Parsons is a researcher whose work lies at the intersection of human-computer interaction and assistive robotics, with a primary focus on developing accessible control systems for rehabilitation robots. His research centers on gesture recognition technologies and adaptable user interfaces designed to empower individuals with varied functional abilities. Parsons' major contributions include pioneering the use of low-cost electrolytic tilt sensors for gesture measurement and classification, comparing dynamic programming algorithms with artificial neural networks to improve control accuracy. His 2007 paper on gesture recognition for rehabilitation robot control, which has garnered 12 citations, stands as his most influential work, demonstrating practical applications for assistive technology. Parsons also developed an adaptable user interface and controller for a rehabilitation robotic arm, addressing the critical need for customizable systems that accommodate diverse user requirements. His thesis on the design and evaluation of an interface for a novel kinematic configuration of a rehabilitation robot arm further underscores his commitment to user-centered design. With a cumulative citation count of 30 across his key publications, Parsons has laid foundational groundwork for accessible robotic assistance, making him a notable contributor to the field of rehabilitation engineering.