Low power CMOS Op-Amp for IoT and Biomedical Applications
Keywords:
Low-Power CMOS Amplifier, Operational Amplifier, IoT Systems, Biomedical Signal Processing, Low-Voltage Design, Cadence Virtuoso, Analog Integrated Circuits, Sensor Interface CircuitsAbstract
Energy-efficient analog circuit design has become increasingly important due to the rapid growth of Internet of Things (IoT) devices and biomedical monitoring systems. These systems typically operate using limited battery resources and must process extremely weak sensor signals. Therefore, operational amplifiers used in such applications must provide adequate gain and stability while consuming minimal power. This work presents the design of a low-power CMOS operational amplifier intended for IoT and biomedical signal conditioning applications.The proposed amplifier architecture employs a CMOS differential input stage combined with current mirror biasing and a gain stage to achieve efficient signal amplification under low supply voltage conditions. The design focuses on reducing bias currents in order to minimize overall power dissipation without significantly affecting amplifier performance. Such characteristics make the circuit suitable for portable, wearable, and implantable electronic devices.Operational amplifiers are essential in amplifying small bio-signals generated by sensors such as electrocardiogram (ECG), electroencephalogram (EEG), and electromyogram (EMG) sensors, as well as in sensor interface circuits commonly used in IoT systems. The designed amplifier provides reliable amplification of low-level signals while maintaining stability and sufficient bandwidth for low-frequency applications.The circuit design and performance evaluation were carried out using Cadence Virtuoso simulation tools. Simulation results confirm that the proposed CMOS operational amplifier achieves low power consumption while maintaining satisfactory voltage gain, bandwidth, and stability. These characteristics demonstrate the suitability of the design for energy-constrained biomedical instruments and IoT sensor interfaces. The proposed approach contributes to improved battery life and reliable signal processing in next-generation low-power electronic systems.











