Hello, I'm currently engaged in research that involves the development of smartphone-based pupillometry for applications in neurofeedback training, real-time cognitive load assessment, and preliminary screening for ADHD, Autism, and Parkinson's disease. Given the extensive groundwork that already exists in this domain, I am exploring potential collaborations from computer vision, and neuropyschology domains that could enhance the precision and efficacy of my project. My research focuses not only on the measurement of pupil diameter but also on how these measurements can inform us about various neural and cognitive processes. With this in mind, I am keen on understanding how Pupil Labs' technology could be leveraged in my work, especially in terms of data collection and processing capabilities, as well as the algorithmic aspect of measuring pupil size with precision without the need for auxiliary equipments. The main challenges I foresee with smartphone camera integration involve accounting for variables such as gaze angle discrepancies and ambient lighting conditions, which could potentially interfere with the near-infrared (NIR) camera's ability to capture precise pupillary data. Given these constraints, I'm curious to learn about any existing or developing solutions that Pupil Labs may offer to address these issues, particularly for NIR camera usage without a focal lens.
Hi @user-51bca2 👋. Thanks for introducing us and the community to your project! It sounds interesting. Just to be clear, do you mean to measure pupil size using the smartphone's camera?