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Paper ID:IJSREM62048

BRAIN-COMPUTER INTERFACE IN NEUROLINK PRO: A NEUROSCIENCE-BASED EEG/EOG SIGNAL PROCESSING AND ASSISTIVE TECHNOLOGY SYSTEM.

Stream/Area:

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Subject:

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Paper ID:

IJSREM62048

Volume:

10 |

4 |

April 2026

Pages:

1-5

Publication Frequency:

Monthly (12 issues per year)

DOI
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10.55041/IJSREM62048

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

VJS

Vedant J. Shipane

Department of Electronics and Telecommunication Engineering

Anuradha College of Engineering and Technology, Chikhli, Dist. Buldana (M.S.) India, Sant Gadge Baba Amravati University, Amravati 444602, India

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GRA

Gauri R. Ambuskar

Department of Electronics and Telecommunication Engineering

Anuradha College of Engineering and Technology, Chikhli, Dist. Buldana (M.S.) India, Sant Gadge Baba Amravati University, Amravati 444602, India

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DB

Dr. B.S.Lankeshwar

EXTC

Anuradha College of Engineering and Technology, Chikhli

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ORS

Omkar R. Shahakar

Department of Electronics and Telecommunication Engineering

Anuradha College of Engineering and Technology, Chikhli, Dist. Buldana (M.S.) India, Sant Gadge Baba Amravati University, Amravati 444602, India

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VMB

Vaishnavi M. Borkar

Department of Electronics and Telecommunication Engineering

Anuradha College of Engineering and Technology, Chikhli, Dist. Buldana (M.S.) India, Sant Gadge Baba Amravati University, Amravati 444602, India

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PGP

Pratiksha G. Patil

Department of Electronics and Telecommunication Engineering

Anuradha College of Engineering and Technology, Chikhli, Dist. Buldana (M.S.) India, Sant Gadge Baba Amravati University, Amravati 444602, India

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Abstract

Brain-Computer Interfaces (BCIs) represent a transformative technology enabling direct communication between the human brain and external computational systems without reliance on conventional neuromuscular pathways. This paper presents NeuroLink Pro v3.0, a complete non-invasive EEG/EOG-based BCI system utilizing the Upside Down Labs BioAmp EXG Pill v1.0 analogue front-end and the Arduino UNO R4 Minima microcontroller. A five-stage firmware-level signal processing pipeline implements adaptive baseline tracking, deviation computation, hysteresis-protected threshold comparison, and temporal double-blink classification at 250 Hz. The NeuroLink Pro v3.0 Electron desktop application delivers eleven BCI-controlled functional modules spanning communication, productivity, entertainment, and clinical data infrastructure. Systematic evaluation yielded single-blink detection accuracy exceeding 99%, double-blink detection exceeding 98%, 0% false-positive rate over 2-minute quiet rest intervals, and end-to-end latency below 50 ms. All eleven modules achieved 100% PASS rate in structured testing. Hardware implementation employs three disposable Ag/AgCl surface electrodes in a differential bipolar configuration, achieving electrode-skin impedance below 10 kΩ and instrumentation amplifier common-mode rejection exceeding 80 dB, ensuring high signal-to-noise ratio under real-world conditions. Auto-calibration autonomously computes the detection threshold from 750 ADC rest samples within 3 seconds, eliminating the manual parameter tuning required by prior systems. The four-tier layered software architecture spanning hardware acquisition, embedded firmware, Electron host application, and user interface—communicates via unidirectional serial interfaces at 250Hz to maintain sub-50 ms end-to-end latency. The complete system is realizable at approximately USD 50 in commodity hardware, representing a significant step toward democratizing assistive BCI technology for the estimated 75 million individuals worldwide living with severe motor disabilities including ALS, spinal cord injury, cerebral palsy, and locked-in syndrome.

KEYWORDS

Key Words: Brain-computer interface electroencephalography EOG signal processing assistive technology blink detection embedded systems Arduino NeuroLink Pro motor disability real-time signal processing.

Cite This Article

Vedant J. Shipane, Gauri R. Ambuskar, Dr. B.S.Lankeshwar, Omkar R. Shahakar, Vaishnavi M. Borkar, Pratiksha G. Patil, "BRAIN-COMPUTER INTERFACE IN NEUROLINK PRO: A NEUROSCIENCE-BASED EEG/EOG SIGNAL PROCESSING AND ASSISTIVE TECHNOLOGY SYSTEM.," International Journal of Scientific Research in Engineering and Management, vol. 10, no. 4, pp. 1-5, April 2026. https://doi.org/10.55041/IJSREM62048

Full Article/Conclusion

7.1 Summary of Achievements NeuroLink Pro v3.0 has been presented as a complete non-invasive EEG/EOG-based BCI system achieving all stated objectives. The five-stage firmware pipeline achieves >99% single-blink detection, >98% double-blink detection, 0% false-positive rate over 2-minute rest intervals, and <50 ms end-to-end latency. All eleven Electron application modules passed structured testing — a 100% module-level pass rate.   The system demonstrates that zero-training, rapidly deployable BCI assistive technology matching research-grade performance is achievable with commodity hardware (~USD 50 total). This is a meaningful contribution toward making BCI accessible to the 75 million individuals worldwide with severe motor disabilities [3].

References

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4/30/2026

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