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All Journal Journal International Dakwah and Communication International Journal of Educational Narratives Journal of World Future Medicine, Health and Nursing Journal of Computer Science Advancements Journal of Moeslim Research Technik Research Psychologie, Orientation et Conseil Journal of Tecnologia Quantica Journal of Loomingulisus ja Innovatsioon Research of Scientia Naturalis Journal of Biomedical and Techno Nanomaterials Journal of Multidisciplinary Sustainability Asean
Tan, Marcus
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Journal : Journal of Computer Science Advancements

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GOODBYE LATENCY: WHY FUTURE MEDICAL DEVICES NEED ARTIFICIAL BRAINS Koh, Megan; Tan, Marcus; Wong, Lucas
Journal of Computer Science Advancements Vol. 3 No. 4 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jsca.v3i4.3332

Abstract

The transition of medical technology from passive monitoring to autonomous, closed-loop intervention is critically impeded by the latency and power inefficiencies of traditional Von Neumann computing architectures. This study investigates the efficacy of neuromorphic hardware as a solution, aiming to validate a bio-inspired architecture capable of sub-millisecond decision-making for life-critical applications. Employing a rigorous hardware-in-the-loop simulation framework, we benchmarked a custom Spiking Neural Network (SNN) against industry-standard microcontrollers, utilizing large-scale cardiac and neurological datasets to evaluate inference speed, energy consumption, and signal fidelity. Quantitative results reveal that the neuromorphic system achieved a 94% reduction in end-to-end latency and a thirty-eight-fold improvement in energy efficiency compared to the digital baseline. The event-driven architecture successfully maintained 96.4% diagnostic accuracy while operating within a negligible thermal envelope suitable for implantation. These findings definitively establish that mimicking biological asynchronous processing eliminates fatal temporal delays, validating neuromorphic “artificial brains” as the essential technological foundation for the next generation of responsive, privacy-secure, and energy-autonomous medical implants.
Co-Authors Ambarwati, Rini Chai, Napat Chan, Rachel Gankhuyag, Baasandorj Harjoni Harjoni I Putu Astawa Khan, Omar Koh, Megan Lee, Ava Lim, Sofia Linm, Sofia Mendes, Clara Nampira, Ardi Azhar Ng, Isabelle Rocha, Thiago Suhartin Dewi Astuti Suzuki, Ren Tan, Ethan Tan, Jaden Verma, Aditi Wong, Lucas