HEROIC: a platform for remote collection of electroencephalographic data using consumer-grade brain wearables

• Published in: BMC bioinformatics 2024-07, Vol.25 (1), p.243-10, Article 243
• Main Authors: Sugden, Richard James, Campbell, Ingrid, Pham-Kim-Nghiem-Phu, Viet-Linh Luke, Higazy, Randa, Dent, Eliza, Edelstein, Kim, Leon, Alberto, Diamandis, Phedias
• Format: Article
• Language: English
• Subjects: Brain; Brain - physiology; Brain research; Cognition; Cost analysis; Data collection; Data entry; Design; EEG; Electrodes; Electroencephalography; Electroencephalography - methods; Event-related potentials; Evoked Potentials - physiology; Humans; Longitudinal studies; Low cost; Male; Marketing research; Modularity; Nervous system diseases; Neurological diseases; Open source software; Public software; Recording sessions; Remote medicine; Software; Task complexity; Wearable computers; Wearable devices; Wearable Electronic Devices
• ISSN: 1471-2105; 1471-2105
• DOI: 10.1186/s12859-024-05865-9

The growing number of portable consumer-grade electroencephalography (EEG) wearables offers potential to track brain activity and neurological disease in real-world environments. However, accompanying open software tools to standardize custom recordings and help guide independent operation by users is lacking. To address this gap, we developed HEROIC, an open-source software that allows participants to remotely collect advanced EEG data without the aid of an expert technician. The aim of HEROIC is to provide an open software platform that can be coupled with consumer grade wearables to record EEG data during customized neurocognitive tasks outside of traditional research environments. This article contains a description of HEROIC's implementation, how it can be used by researchers and a proof-of-concept demonstration highlighting the potential for HEROIC to be used as a scalable and low-cost EEG data collection tool. Specifically, we used HEROIC to guide healthy participants through standardized neurocognitive tasks and captured complex brain data including event-related potentials (ERPs) and powerband changes in participants' homes. Our results demonstrate HEROIC's capability to generate data precisely synchronized to presented stimuli, using a low-cost, remote protocol without reliance on an expert operator to administer sessions. Together, our software and its capabilities provide the first democratized and scalable platform for large-scale remote and longitudinal analysis of brain health and disease.