Self-Calibrating Mixed-Signal Analog Front-End with Adaptive Bias for Multimodal Biopotential Sensing

Vithyalakshmi N; Narmatha P; Reddy Prasad A; Kamal Kishore Y; Senthilkumar V; Balamanikandan A

doi:10.31838/JVCS/07.01.25

Authors

Vithyalakshmi N Department of Electronics Engineering—VLSI Design and Technology, Rajalakshmi Institute of Technology, Kuthambakkam, Chennai, India
Narmatha P Department of Electronics and Communication Engineering, Sri Sairam College of Engineering, Anekal, Bangalore, India
Reddy Prasad A Department of CSE (Data Science), Mother Theresa Institute of Engineering and Technology, Palamaner, India
Kamal Kishore Y Department of Electrical & Electronics Engineering, Ballari Institute of Technology and Management, Ballari, India
Senthilkumar V Department of Electronics and Communication Engineering, R P Sarathy institute of Technology, Salem, India
Balamanikandan A Department of Electronics and Communication Engineering, Mohan Babu University (Erstwhile Sree Vidyanikethan Engineering College), Tirupati, India

DOI:

https://doi.org/10.31838/JVCS/07.01.25

Keywords:

Self-calibrating analog front-end, Adaptive biasing, Multi-modal signal conditioning, Capacitive cross-coupled common-gate amplifier, Biomedical sensor interfaces

Abstract

This research presents a self‐calibrating mixed‐signal analog front-end (AFE) for multi-modal biomedical sensing, implemented in a 180 nm CMOS process. A capacitive cross-coupled common-gate Class-E amplifier with adaptive biasing sustains linearity and gain across amplitude and temperature swings. A low-noise instrumentation amplifier and a programmable gain stage use digitally controlled offset and noise-aware bias tuning to support ECG, EMG, and temperature channels. A hybrid calibration engine comprising a 10-bit SAR ADC and on-chip finite-state machine enables closed-loop bias and offset compensation based on real-time signal statistics. Multi-phase, charge-controlled clocking ensures inter-channel synchronization with minimal jitter, while active-RC biquad filters with FDNRs enhance common-mode rejection and out-of-band suppression. Post‐layout simulations demonstrate 3.2 μVrms input-referred noise, 92 dB dynamic range, and 1.2 μW/channel power consumption, with robust operation across process-voltage-temperature variations. These results validate a reconfigurable, ultra-low-power AFE suited for next‐generation IoT-enabled biomedical SoCs.