Comparative analysis of EEG sensors for consumer applications with neural signal processing

Electroencephalography (EEG) sensors have gained significant attention in consumer applications, ranging from brain-computer interfaces (BCIs) and neurofeedback to wellness tracking and gaming. This paper presents a comparative analysis of commercially available EEG sensors, evaluating their performance, affordability, usability, and suitability for various consumer applications. Key factors such as signal quality, electrode type, number of channels, connectivity, and software compatibility are assessed. We also discuss the trade-offs between low-cost, non-invasive solutions and high-fidelity research-grade devices. Our findings highlight the strengths and limitations of different EEG sensors, providing insights for consumers, developers, and researchers seeking the most appropriate solution for their needs.

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Publication Details

Published
2025-06-05
DOI
https://doi.org/10.1109/eaic66483.2025.11101382
Primary Topic
EEG and Brain-Computer Interfaces
Type
article
Field-Weighted Citation Impact
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article

Comparative analysis of EEG sensors for consumer applications with neural signal processing

Parveen Kumar, Ashish Kumar Pal, Raj Kumar, Sudhanshu Sudhanshu
EEG and Brain-Computer Interfaces
article

Comparative analysis of EEG sensors for consumer applications with neural signal processing

Parveen Kumar, Ashish Kumar Pal, Raj Kumar, Sudhanshu Sudhanshu
article en

Abstract

Electroencephalography (EEG) sensors have gained significant attention in consumer applications, ranging from brain-computer interfaces (BCIs) and neurofeedback to wellness tracking and gaming. This paper presents a comparative analysis of commercially available EEG sensors, evaluating their performance, affordability, usability, and suitability for various consumer applications. Key factors such as signal quality, electrode type, number of channels, connectivity, and software compatibility are assessed. We also discuss the trade-offs between low-cost, non-invasive solutions and high-fidelity research-grade devices. Our findings highlight the strengths and limitations of different EEG sensors, providing insights for consumers, developers, and researchers seeking the most appropriate solution for their needs.

Chandigarh University (IN), Punjab Engineering College (IN)
Openalex Percentile: Top 79%
EEG and Brain-Computer Interfaces
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Comparative analysis of EEG sensors for consumer applications with neural signal processing — Parveen Kumar, Ashish Kumar Pal, et al. · (2025) | TGRS Research Map | TGRS