AbstractContext. Acromegaly is a rare and progressive disorder often diagnosed late due to its insidious onset and gradually evolving facial features. Earl

Event owners are using facial analysis to capture analytic data on attendees. Here's why the meeting industry should ditch this technology.

Background: Photography has been a mainstay of aesthetic medicine for decades. Many practices today use sophisticated equipment and studios to maximize image quality and consistency. However, the quality of mobile device cameras now rivals that of digital single-lens reflex (DSLR) cameras of just a few years ago. In the context of clinical trials, image self-capture using mobile devices may help reduce the burden on clinic resources, increase data collection opportunities and quality, and lower barriers for study participation. Objective: Develop and validate a mobile device application designed to help subjects self-capture clinically usable images. Methods: The Allergan Aesthetic Mobile Image Application auto-captures images while directing study subjects on distance, head position (angle and tilt), and expression to capture a high-quality clinical image. Resolution and optimal lighting conditions for the application were compared with a Canfield VISIA-CR system. Objective image quality assessment for iPhone XR, iPhone 12, Canfield VISIA-CR with a DSLR, and the Canfield Mobile Image Capture Application with a variety of Android and iOS devices was conducted using the Blind/Referenceless Image Spatial Quality Evaluator (BRISQUE). Clinical utility was assessed using images of lateral canthal lines (LCL) or forehead lines (FHL) in subjects who were also evaluated by a physician. The inter- and intra-rater variability of image rating was assessed and compared to in-person rating. #usability of the application was assessed according to ISO/IEC 250101. Results: The Allergan Aesthetic Mobile Image Application performs best under natural light conditions, and while image resolution is insufficient for assessment of minor facial structures, it can be used to assess larger structures such as FHL. A total of 3968 images were assessed using BRISQUE. Images captured with the application had better image quality, as indicated by lower mean BRISQUE scores of 14.05–19.81, compared with images captured with Canfield VISIA-CR with a DSLR (34.47) and the Canfield Mobile Image Capture Application (23.43). LCL and FHL were rated both in person and digitally in 68 and 71 primarily White female subjects, respectively. Inter-rater reliability between clinician live evaluations and independent photo review of self-captured photos was substantial to almost perfect for all raters (LCL: intraclass correlation coefficient [ICC] = 0.75–0.91 at rest, 0.79–0.89 at maximum contraction; FHL: ICC = 0.77–0.93 at rest, 0.70–0.89 at maximum contraction). After 2 iterations of improvements to the app, subjects rated its #usability above average. Conclusions: The Allergan Aesthetic Mobile Image Application delivers consistent, high-quality images that allow for assessment of LCL and FHL in good agreement with in-person evaluation. #usability will be further optimized in future iterations of the application. Image self-capture using mobile devices can transform the conduct of clinical trials in aesthetic medicine by reducing clinic costs and removing barriers to participation. Clinical Trial: NA

A core claim of facial analysis technology — that it can reliably measure attendee emotions at events — is seriously flawed.