Sensors, Volume 23, Issue 24
2023 December-2 - 295 articles
Cover Story: A lightweight, compliant sensorised glove capable of detecting scratching with Machine Learning (ML) using data from flexible microtubular sensors and inertial measurement unit (IMU) has been developed. The sensorised glove provides the user and clinicians with quantifiable information of scratching intensity, frequency, and duration as a proxy to classify the itch severity caused by atopic dermatitis (AD). The paper describes the design of the sensorised glove, training the ML model to detect scratching with the purpose of assaying scratching objectively and a pilot daytime clinical study to validate the device with patients. The sensorised glove can detect 94.4% scratching with the dominant hand where the glove was worn. View this paper - Issues are regarded as officially published after their release is announced to the table of contents alert mailing list .
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