Skin sensing and wearable technology as tools to measure atopic dermatitis severity.

Wearable medical technology encompasses a range of electronic devices that act as biosensors. Atopic dermatitis (AD) is the commonest inflammatory skin disease and represents an important area of need in which to leverage the power of wearable biosensor technology, especially as the impact of COVID-19 increases the likelihood of virtual consultations becoming an integrated part of clinical practice. The aim of this review is to systematically define the published evidence for the utility of wearable biosensors in assessment and management of atopic dermatitis (AD). A systematic literature search was conducted for publications from 1995 onwards for 'sensor' OR 'sensing' OR 'biosensor' OR 'biomarker'. Results were combined ('AND') with a search for 'wearable' OR 'actigraphy' OR 'Internet of things' OR 'microneedle' OR 'patch' OR 'e-textile' OR 'smart textile' and atopic dermatitis (MESH terms). Fifty seven abstracts were identified from the database search of which 39 were selected for detailed review. Broadly, wearable sensing systems in atopic dermatitis were split into three categories: wearable biosensor modules (actigraphy and smartwatches), clothing and integrated fabrics placed onto the epidermis and intradermal or subcutaneous sensors. The best evidence for correlation with AD disease severity was with actigraphy measurements of itch. However, newer approaches including sensing skin barrier function, inflammation and small molecule analysis as well as employing artificial intelligence offer more potential for advanced disease monitoring. Skin diseases, specifically AD, stand to benefit greatly from wearable technology, because of the ease of direct contact to the skin, the high prevalence of the disease and the large unmet need for better disease control in this group. However, important emphasis must be placed on validating the correlation of data from such technology with patient-reported outcomes. Wearable biosensors offer a huge potential to deliver better diagnostics, monitoring and treatment outcomes for patients.