Multimodal Biomedical Signal Acquisition Setup to Assess Chronic Pain in Older Adults With Alzheimer’s Disease

Chronic pain often goes unrecognized and untreated in individuals with Alzheimer's disease and related dementias (ADRD), mainly due to limited capacity to verbalize pain. Addressing this issue requires the development of reliable objective biomarkers for pain. In the present pilot study, we explored the feasibility and acceptability of using a wearable electroencephalograph (EEG) and a screen-based eye tracker system to identify neural signatures of chronic pain in this population. First, we developed a multimodality biomedical signal acquisition setup with four parts: hardware to record biomedical signals, software to monitor and synchronize multiple inputs, an experimental paradigm with resting state and a cognitive task to assess pain, and an online database to collect subject demographics and subjective measures in a secure environment. EEG signals were recorded using an FDA-cleared 32-channel EEG device with 3-axis accelerometer while gaze and pupil dilation were captured via a head-free, video-based eye tracker. A cognitive task was designed using 32 custom-generated images representing pain/no-pain conditions in addition to 16 images with painful and neuter expressions from the Delaware Pain Database. EEGs, accelerometer, and eye tracker data were synchronized with the behavioral paradigm by sending digital triggers from paradigm module on a MATLAB/Simulink model that was designed for the study. Finally, a database was created on RedCap with 16 separate instruments from cognitive and pain assessment tools to the feasibility and acceptability surveys.