An An Efficient Baseline Restoration Circuit for Real-Time Impedance Cardiography: FPGA-based Calibration with Multi-Sensor Integration: AN EFFICIENT BASELINE RESTORATION CIRCUIT

Priya Darshini Kumari; Ksh Milan Singh; Zefree Lazarus Mayaluri; Natenaile Asmamaw Shiferaw; Ganapati Panda; Sujeevan Kumar Agir

doi:10.56042/jsir.v84i04.15207

Authors

Priya Darshini Kumari Department of Electrical Engineering, National Institute of Technology Meghalaya, Shillong, 793 003, Meghalaya, India
Ksh Milan Singh Department of Electrical Engineering, National Institute of Technology Meghalaya, Shillong, 793 003, Meghalaya, India
Zefree Lazarus Mayaluri Department of Electrical Engineering, C.V. Raman Global University, Bhubaneswar, 752 054, Odisha, India https://orcid.org/0000-0002-6910-126X
Natenaile Asmamaw Shiferaw Department of Computer Science and Engineering, C.V. Raman Global University, Bhubaneswar, 752 054, Odisha, India
Ganapati Panda Department of Electronics Communication and Engineering, C.V. Raman Global University, Bhubaneswar, 752 054, Odisha, India
Sujeevan Kumar Agir Department of Electronics and Communication Engineering, Jayaprakash Narayan College of Engineering, Mahabubnagar, 509 001, Telangana, India

DOI:

https://doi.org/10.56042/jsir.v84i04.15207

Keywords:

Adaptive calibration, Artifact suppression, Baseline correction, Multi-sensor fusion, Wearable monitoring

Abstract

Impedance Cardiography (ICG) is a widely used non-invasive technique for cardiovascular monitoring; however, baseline drift due to respiratory and motion artifacts presents a persistent challenge. This paper introduces an efficient baseline restoration circuit tailored for real-time artifact suppression in ICG signals, prioritizing low latency and optimal power consumption. The circuit leverages a Field-Programmable Gate Array (FPGA) for responsive processing, coupled with a microcontroller-based adaptive calibration algorithm that dynamically adjusts based on real-time input from accelerometers and gyroscopes. This multisensory fusion enables precise differentiation between motion-induced and respiratory artifacts, significantly enhancing drift correction accuracy. Experimental validation, conducted on simulated and real-world ICG data across diverse conditions, demonstrates an average Signal-to-Artifact Ratio (SAR) improvement within a typical range of 10−12 dB over baseline methods and achieves low Mean Square Error (MSE) values. Thermal data and recalibration frequency were optimized for wearable use, supporting continuous ICG monitoring. The proposed system is particularly beneficial for continuous remote monitoring of patients with chronic heart conditions, aiding in early detection of cardiovascular irregularities. This power-efficient design advances the potential for real-world application in wearable health monitoring devices.