Calibration of off-the-shelf low-cost wearable EEG headset for application in field studies
Manvi Jain, C.M. Markan

TL;DR
This paper introduces a calibration method for low-cost dry EEG headsets to determine their suitability for specific cognitive tasks in field studies, using simulated and real data analysis.
Contribution
It presents a novel calibration methodology that identifies the brain regions and cognitive tasks suitable for low-cost EEG devices, enhancing their practical utility outside labs.
Findings
Identifies brain regions scanned by LCDE devices.
Characterizes LCDE for specific cognitive tasks.
Suggests LCDE can replace traditional EEG in various settings.
Abstract
Electroencephalography (EEG) is an integral tool in neurocognitive research worldwide. However, research grade EEG (32/64ch) systems are expensive and have cumbersome setup designed for clinical usage not suited for rugged environment of field-studies outside lab. Further, the long setup-time of EEG can be intimidating to those who are restless subjects e.g., children or elderly. Off-the-shelf, low-cost, dry EEG devices (LCDE) have been proposed as promising options. However, small number of electrodes in LCDE limit the detection scalp-area reducing the utility of an LCDE only to a specific set of cognitive tasks based on the brain lobe scanned. This paper proposes a novel methodology for calibration of an LCDE (e.g., DREEM Headband) to identify the specific class of cognitive tasks a LCDE is likely suited for. The methodology involves comparative analysis of the recorded data using…
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Taxonomy
TopicsEEG and Brain-Computer Interfaces · Neuroscience and Neural Engineering · Neural dynamics and brain function
