ROLE OF VLSI IN MODERN BIOMEDICAL APPLICATIONS

Abstract

Very Large Scale Integration (VLSI) means integrating a number of transistors in a single chip to create an electronic circuit. It has become the necessity of modern biomedical systems, in which many microprocessors, memory chips and Integrated circuits (ICs) are fabricated for continuous sensing of patient’s health details and for data integration interface in which patient’s data are transferred securely. This review summarizes recent advancements (2021–2025) regarding the role of VLSI circuits in facilitating the entire continuum of patient-centered healthcare, ranging from analog front-ends that capture micro-volt bio signals to edge-AI accelerators that provide on-device diagnosis while ensuring privacy. We organized the application of VLSI circuits in biomedicals like wearable monitoring (ECG/EEG), implantable therapeutics (pacemakers, neuro stimulators), biomedical imaging (ultrasound/X-ray readout SoCs), and neuromorphic/AI-enabled bio signal processing in a table. In modern biomedical applications, VLSI plays three major roles: (1) Miniaturization i.e. fitting a large number of ICs in a single small silicon chip which is easy to wear and implanted inside the body due to its small size. Wearable and Implantable devices are made using these techniques; (2) Reliability i.e. less number of failures and long-term usage; (3) Low power consumption by using low power VLSI design. This review paper gives an overview of evolution of VLSI in biomedical engineering, wearables and implantable devices integration, Imaging, neuromorphic and AI enabled VLSI system and at last some challenges that we face for low power VLSI design and its principles. In future, Biomedical, VLSI and AI engineers if combined together can give rise to many advancements in the clinical needs by scaling it with limited resources while keeping in mind that cost should also be low. The whole healthcare system should make a strategic tool for making biomedical devices less costly, safer, more accurate, and easier to use for patients and it can only possible by combining VLSI and AI in it.