A Sensorised Glove to Detect Scratching for Patients with Atopic Dermatitis.

ABSTRACT: In this work, a lightweight compliant glove that detects scratching using data from microtubular stretchable sensors on each finger and an inertial measurement unit (IMU) on the palm through a machine learning model is presented: the SensorIsed Glove for Monitoring Atopic Dermatitis (SIGMA). SIGMA provides the user and clinicians with a quantifiable way of assaying scratch as a proxy to itch. With the quantitative information detailing scratching frequency and duration, the clinicians would be able to better classify the severity of itch and scratching caused by atopic dermatitis (AD) more objectively to optimise treatment for the patients, as opposed to the current subjective methods of assessments that are currently in use in hospitals and research settings. The validation data demonstra

SUBMITTER: Au CY 

PROVIDER: S-EPMC10748247 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature