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@article{173695,
author = {Yash Samant and Akash Tiwari and Varsha Mashoria and Aditya Shukla and Harsh Mishra},
title = {Between Life and Code: The Rise of Adaptive Artificial Heart},
journal = {International Journal of Innovative Research in Technology},
year = {2025},
volume = {11},
number = {10},
pages = {1220-1229},
issn = {2349-6002},
url = {https://ijirt.org/article?manuscript=173695},
abstract = {The evolution of artificial heart technology has reached a transformative era where intelligence and adaptability define its future. Traditional artificial hearts, constrained by fixed operational rates, fail to dynamically respond to a patient’s physiological demands, limiting their effectiveness in real-world scenarios. This research introduces an innovative machine learning-powered artificial heart that autonomously regulates heartbeat in real time, optimizing patient safety and comfort.
The proposed system integrates a network of biometric sensors to monitor critical health parameters such as heart rate, blood pressure, oxygen levels, and activity status. A sophisticated machine learning algorithm processes these real-time inputs, predicts the required adjustments, and modulates the artificial heart’s pumping rate accordingly. By leveraging adaptive cardiac support, this system significantly enhances patient autonomy, device efficiency, and long-term performance.
Preliminary simulations validate its effectiveness, achieving 92% accuracy in predicting optimal heart rate variations while improving battery efficiency by 35% compared to traditional models. This research paves the way for the future of intelligent cardiac prosthetics, aiming to integrate deep learning models, remote connectivity, and clinical validation to further enhance its real-world application.},
keywords = {Artificial Heart, Machine Learning, Real-Time Adaptation, Biometric Sensors, Intelligent Cardiac Prosthetics, Cardiac Healthcare.},
month = {March},
}
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