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Threshold and Trend Artifacts in Localized Multi-Frequency Bioimpedance Measurements.

Todd J Freeborn¹, Shelby Critcher¹

¹Department of Electrical and Computer Engineering, University of Alabama, Tuscaloosa, AL 35404 USA.

Ifac-Papersonline

|April 25, 2023

Summary

This study introduces two methods to detect artifacts in bioimpedance measurements for wearable health devices. These techniques ensure data quality for continuous physiological monitoring, reducing errors in wearable bioimpedance analysis.

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Area of Science:

Biomedical Engineering
Physiological Monitoring
Wearable Technology

Background:

Localized tissue bioimpedance is crucial for health monitoring applications.
Translating bioimpedance into wearable systems requires robust data quality assessment.
Artifacts in measurements can compromise the integrity of analyzed datasets.

Purpose of the Study:

To present and evaluate two methods for identifying artifacts in bioimpedance resistance measurements.
To ensure the reliability of data collected for continuous monitoring systems.
To reduce errors from equipment or environmental conditions in bioimpedance datasets.

Main Methods:

Two artifact identification methods were developed: thresholding and trend detection.
These methods were applied to localized knee bioimpedance data.
Data was collected from two knee sites over seven days under free-living conditions.

Main Results:

Threshold artifacts were identified in 0.04% of longitudinal and transverse data.
Longitudinal data showed 0.69% threshold artifacts.
Transverse data exhibited 3.50% threshold artifacts.

Conclusions:

The proposed methods effectively identify artifacts in localized bioimpedance measurements.
Data quality assessment is vital for the successful implementation of wearable bioimpedance monitoring.
These techniques support the development of reliable continuous health monitoring systems.