Publication Date


Document Type


First Advisor

Ferdowsi, Hasan

Degree Name

M.S. (Master of Science)

Legacy Department

Department of Electrical Engineering


A fully solid-state, software-defined, one-handed, handle-type control device built around a machine-learning (ML) model that provides intuitive and simultaneous control in position and orientation each in a full three degrees-of-freedom (DOF) is proposed in this paper. The device, referred to as the “Smart Handle”, and it is compact, lightweight, and only reliant on low-cost and readily available sensors and materials for construction. Mobility chairs for persons with motor difficulties could make use of a control device that can learn to recognize arbitrary inputs as control commands. Upper-extremity exoskeletons used in occupational settings and rehabilitation require a natural control device like the Smart Handle that can detect and provide position and orientation trajectories to their kinematic models. Aerial and submersible vehicles that often require multiple inputs for positioning and throttling could see their control systems simplified by a technology like the Smart Handle which can offer both with the dedication of only one hand from the user. This study has shown that the Smart Handle device can learn to output a continuous range of translation and rotation information from simple training sets that consist only of examples where intended motion was restricted to varying magnitudes in a single DOF at a time. With personalized calibration, the Smart Handle can consistently classify movement with over ninety-five percent accuracy. Proof-of-concept experiments were successfully conducted on exoskeleton control applications as well as wheeled robot control.


101 pages




Northern Illinois University

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