Adherence Monitor for Measurement of Removable Cast Walker Wear-Time: Multiple Sensors and Predictive Analytics...

Area of Science:

• Biomedical Engineering
• Wearable Technology
• Diabetes Management

Background:

• Diabetic foot ulcers (DFUs) affect up to 25% of diabetes patients, necessitating specialized treatment like removable cast walker (RCW) boots.
• Patient adherence to RCW wear is crucial for healing but often compromised by device removal for hygiene.
• Accurate monitoring of RCW wear time is essential to ensure treatment effectiveness and improve patient outcomes.

Purpose of the Study:

• To evaluate a novel electronic system for measuring patient adherence to removable cast walker (RCW) therapy.
• To assess the accuracy of a multi-sensor system in determining RCW wear time compared to patient diaries.
• To identify optimal sensor combinations and algorithms for reliable wear-time adherence measurement.

Main Methods:

• Development of an electronic wear-time monitor incorporating temperature, accelerometer, and proximity sensors.
• Collection of time-stamped sensor data and patient-recorded don/doff times over a two-week period with healthy volunteers.
• Application of confusion matrix predictive analytics to compare sensor data with patient diaries for wear-time accuracy.

Main Results:

• Multi-sensor analysis demonstrated a high correlation (.96) with patient-reported wear time.
• Differential temperature and accelerometer algorithms significantly outperformed individual temperature sensor algorithms.
• Foot proximity sensors showed superior correlation with patient diaries compared to temperature or acceleration alone.

Conclusions:

• An electronic data recorder with multiple sensors can accurately determine removable cast walker (RCW) wear time.
• Utilizing algorithms that integrate data from diverse sensor types enhances the accuracy of wear-time measurement.
• This technology offers a promising solution for objective adherence monitoring in DFU treatment.