Massachusetts Institute of Technology

Brian Mayton

Joseph A Paradiso

Asaph Azaria

A sensor system detects hand-to-mouth behavior. The system includes an electrical bio-impedance spectrometer and an inertial measurement unit. The sensor system may be worn on the forearm. The sensor system recognizes hand-to-mouth behavior in real-time, facilitating monitoring and immediate interventions An electrode positioning strategy optimizes the device's sensitivity and accuracy. Machine learning algorithms are leveraged to infer the hand-to-mouth detection. A prototype of the sensor system achieves 92% detection accuracy for recurrent usage by a single user and 90% accuracy for users that have not been previously encountered.

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Somerville, MA, United States of America

Brian Mayton