A comprehensive evaluation framework for consumer-grade EEG devices: signal quality, robustness, and usability

Abstract

The widespread adoption of consumer-grade electroencephalogram (EEG) devices has introduced new opportunities for applications beyond traditional clinical and laboratory settings. However, the lack of standardized evaluation methodologies for these devices raises concerns regarding their signal validity and usability. This study proposes a comprehensive evaluation paradigm for consumer-grade EEG devices, encompassing three levels of signal assessment: the detection of non-neural physiological artefacts signals, the validation of brain waves, and robustness to noise. Using a participant pool of 30 individuals, we assessed four popular consumer-grade EEG devices—BrainLink Pro, NeuroNicle FX2, Mindwave Mobile2, and Muse2—against a research-grade reference device, DSI-24 (Wearable Sensing Inc.). Experimental paradigms involved tasks such as eye blinking, jaw clenching, eyes-open/closed conditions for brain wave detection, and controlled head movements. The results indicate that all tested devices successfully detected both non-neural physiological artefacts and brain wave signals, with consumer-grade devices displaying comparable alpha rhythm characteristics and noise robustness to the research-grade device. User experience was evaluated through a structured questionnaire, revealing significantly higher usability scores for consumer-grade devices, particularly Mindwave Mobile2. The findings highlight the feasibility of using consumer-grade EEG devices for practical applications, provided that validation is performed using structured evaluation protocols as proposed.