Study on Optimized Hardware Design for High Speed and Noise Resilient Bio Signal Transmission Using Chaotic Memristor-Capacitor Integrated Cryptosystem with RealTime Alarm System
Recent advancements in bio-signal transmission focus primarily on enhancing security. Memristor-based cryptosystems have gained attention due to the ability to introduce complex chaotic behaviors, which improve the encryption of bio-signals such as ECGs, making the transmission more secure. The Logistic-coupled Memristor (LCM) map, which combines discrete memristors with a one-dimensional (1D) chaotic logistic map which is used to increase the unpredictability and encryption strength of signals. The novelty of this paper is bio-signal communication through speed and intelligent noise cancellation. This article presents a study of hardware-based cryptosystem using Raspberry Pi 4 Model B as the main single-board computer with an integrated Logistics-coupled memristor coupled to a capacitor to reduce noise further. The system also takes advantage of this generation of Raspberry Pi because it has very high processing power and memory, making it suitable for exceptionally complex tasks of encryption and advanced noise filtering. The proposed review was furtherly improved with the use of LPF and HPF and signal transformation. The system has a real time alarm system that notifies medical personnel in case of any emergencies such as heart attacks. Previous realization has used ATmega328P microcontroller, which is used in Arduino Uno and Nano, allowing chaos encryption but with a limited range, slow processing, poor filtering of noise, and quite limited memory. This particular study just concerned optimizing transmission speed and noise filtering efficiency by having a capacitor in parallel with the Logistic Coupled Memristor (LCM) map to ensure the best solution for real-time bio-signal communication and alerting.
Authors
- S Hemavathy
- Angel Jolina A
- M Harshanya
Institutions
- Chennai Mathematical Institute (IN)
Publication Details
- Published
- 2025-03-04
- DOI
- https://doi.org/10.1109/autocom64127.2025.10956271
- Primary Topic
- stochastic dynamics and bifurcation
- Type
- article
- Field-Weighted Citation Impact
- 0.00