Artificial Intelligence-Enabled Wearable Devices and Nocturnal Scratching in Mild Atopic Dermatitis.

Area of Science:

• Biomedical Engineering
• Dermatology
• Artificial Intelligence

Background:

• Pruritus affects over 10% of the population, with limited non-pharmacological interventions for continuous scratch reduction.
• Atopic dermatitis patients frequently experience moderate to severe nocturnal scratching, impacting sleep and quality of life.

Purpose of the Study:

• To evaluate an AI-enabled wearable sensor with closed-loop haptic feedback for reducing nocturnal scratching in mild atopic dermatitis.
• To assess the accuracy and efficacy of this technology in a real-world, at-home setting.

Main Methods:

• A single-arm, two-stage cohort study with within-participant design was conducted.
• Participants (n=10) with mild atopic dermatitis used a wearable sensor for 7 nights (sensing only) followed by 7 nights with AI-driven haptic feedback.
• Scratch events and duration were retrospectively analyzed using paired t-tests.

Main Results:

• The AI-enabled haptic feedback sensor significantly decreased nightly scratch events by 28% (P=.03) and scratch duration by 50% (P=.01).
• Nocturnal scratching reduction was achieved without impacting total sleep opportunity.
• All 10 participants completed the study, with no loss to follow-up.

Conclusions:

• Haptic feedback from an AI-powered wearable sensor presents a viable non-pharmacological intervention for reducing nocturnal scratching in mild atopic dermatitis.
• Further randomized controlled trials are warranted to confirm these findings and explore broader applications.