Electrochemical Impedance Spectroscopy Analog Frontend Optimized for Mobile Biosensing Applications

Electrochemical impedance spectroscopy (EIS) represents a promising and rapidly growing biosensing technique, enabling researchers and clinicians to perform label-free analyte detection; however, the scarcity of small, low-cost, and energy-efficient mobile devices for impedance measurement presents a major obstacle to further utilization of this method. Many EIS analog frontend (AFE) integrated circuits meeting these criteria are not commercially available; equivalent discrete circuits are frequently too expensive, large, or energy-inefficient for broad deployment. We present a discrete EIS-AFE which encodes impedance magnitude and phase as DC potentials; our AFE is optimized to minimize energy expenditure (<21 μJ per point at 10 kHz), size (<91 mm 2 for the detector circuits), computational overhead (requiring only three ADC samples), and design complexity to target edge sensing applications (such as single-frequency EIS). We characterize the performance of the custom AFE, perform a comparative power analysis, and demonstrate successful EIS sensing using a series of dummy cells and a synthetic tissue analog saturated with artificial sweat. Our AFE enables accurate acquisition of impedance data with considerable power and cost savings relative to similar devices, while enabling modular expansion of the system to facilitate EIS sensing in a variety of mobile sensing applications.

Authors

Publication Details

Journal
ECS Sensors Plus
Published
2025-12-01
DOI
https://doi.org/10.1149/2754-2726/ae27e0
Primary Topic
Biosensors and Analytical Detection
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Electrochemical Impedance Spectroscopy Analog Frontend Optimized for Mobile Biosensing Applications

Chris Sharkey, Koji Sode, Jack Twiddy, Michael Angelo-Anthony Daniele et al.
ECS Sensors Plus
Biosensors and Analytical Detection
article

Electrochemical Impedance Spectroscopy Analog Frontend Optimized for Mobile Biosensing Applications

Chris Sharkey, Koji Sode, Jack Twiddy, Michael Angelo-Anthony Daniele, Ethan Cove
article en

Abstract

Electrochemical impedance spectroscopy (EIS) represents a promising and rapidly growing biosensing technique, enabling researchers and clinicians to perform label-free analyte detection; however, the scarcity of small, low-cost, and energy-efficient mobile devices for impedance measurement presents a major obstacle to further utilization of this method. Many EIS analog frontend (AFE) integrated circuits meeting these criteria are not commercially available; equivalent discrete circuits are frequently too expensive, large, or energy-inefficient for broad deployment. We present a discrete EIS-AFE which encodes impedance magnitude and phase as DC potentials; our AFE is optimized to minimize energy expenditure (<21 μJ per point at 10 kHz), size (<91 mm 2 for the detector circuits), computational overhead (requiring only three ADC samples), and design complexity to target edge sensing applications (such as single-frequency EIS). We characterize the performance of the custom AFE, perform a comparative power analysis, and demonstrate successful EIS sensing using a series of dummy cells and a synthetic tissue analog saturated with artificial sweat. Our AFE enables accurate acquisition of impedance data with considerable power and cost savings relative to similar devices, while enabling modular expansion of the system to facilitate EIS sensing in a variety of mobile sensing applications.

ECS Sensors PlusVol. 4(4)
Openalex Percentile: Top 62%
Biosensors and Analytical Detection
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.