Preprint: Towards Smart Glasses for Facial Expression Recognition Using OMG and Machine Learning

This study aimed to evaluate the use of novel optomyography (OMG) based smart glasses, OCOsense™, for the monitoring and recognition of facial expressions. Experiments were conducted on data gathered from 27 young adult participants, who performed facial expressions varying in intensity, duration, and head movement. The facial expressions included smiling, frowning, raising the eyebrows, and squeezing the eyes. The statistical analysis demonstrated that: (i) OCO™ sensors based on the principles of OMG can capture distinct variations in cheek and brow movements with a high degree of accuracy and specificity; (ii) Head movement does not have a significant impact on how well these facial expressions are detected. The collected data were also used to train a machine learning model to recognise the four facial expressions and when the face enters a neutral state. We evaluated this model in conditions intended to simulate real-world use, including variations in expression intensity, head movement and glasses position relative to the face. The model demonstrated an overall accuracy of 93% (0.90 f1-score) – evaluated using a leave-one-subject-out cross-validation technique. ### Competing Interest Statement Dr. M. Gjoreski and dr. H. Gjoreski have previously worked as consultants with the funding company, though they did not receive funding for this study. I. Kiprijanovska, S. Stankoski, J. Archer, M. Fatoorechi, and dr. M. J. Broulidakis are employees at the funding company. Dr. C. Nduka MA, MD, FRCS, is the founder of the funding company. ### Funding Statement This work was supported by Innovate UK under the project Mobile Observation of Depression (MOOD) platform for digital phenotyping (Grant number 105207). H. Gjoreski's work was partially funded by the WideHealth project (EU's Horizon 2020 research and innovation programme, grant agreement No 952279). ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: Ethical approval was obtained from the London - Riverside Research Ethics Committee on 15 July 2022 (ref: 22/LIO/0415). I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes The data is available on demand.