Objective Measurement of Fluctuating Pain

A light-weight package for reading and processing Neon (Pupil Labs) multimodal eye-tracking data

Chang & Tang et al., Nature (2025), An open-source implementation of a real-time pupil tracking and closed-loop control system for neuroscience experiments

Computational modeling pipeline integrating pupillometry, behavioral data, and drift diffusion models (DDM) to understand the relationship between brain arousal and decision-making processes.

R functions for processing pupillary light reflex (PLR) recordings — artifact removal, feature extraction, and batch analysis

Foundation model evaluation on pupillary light reflex time series. Biosignal analysis with modern TSFMs.

Pupillometry and eyetracking with python

👁️ CRAN-published R package for reproducible pupillometry preprocessing with BIDS compliance, automated QC reports, and scalable pipeline tools.

A deep-learning-based web tool for translational and real-time pupillometry

PupEyes: Your Buddy for Pupil Size and Eye Movement Data Analysis

🛜 A utility to remotely yank .edf files from an EyeLink Eye Tracker Host PC and convert them to plain-text ASCII (.asc) on the fly.

Pupil size tracking pipeline based on PupilSense

Online Material for Vidal et al. (2024). Cholinergic-related pupil activity reflects level of emotionality during motor performance. EJN, 59(9):2193–2207.

Lauren's personal website

Python routines for parsing of combined EEG and eye-tracking data

Real time pupillometry in the web browser using a 4K webcam video feed processed by this WebGL and JavaScript library. 2 demo experiments are included 🔬

Official implementation of the pupillometry system called PupilSense proposed in the article "PupilSense: Detection of Depressive Episodes Through Pupillary Response in the Wild".

Official implementation of the affective mobile sensing system called FacePsy proposed in the article "FacePsy: An Open-Source Affective Mobile Sensing System - Analyzing Facial Behavior and Head Gesture for Depression Detection in Naturalistic Settings".

This project provides an end-to-end solution for pupil diameter estimation using accessible hardware (like webcams) and deep learning techniques.

Official implementation of a free pupillometry platform called PupilEXT proposed in the article "PupilEXT: flexible open-source platform for high resolution pupillometry in vision research".