Development and Validation of an Algorithm to Objectively Quantify Adherence to Offloading Interventions

Area of Science:

• Biomedical Engineering
• Orthopedics
• Wearable Technology

Background:

• Diabetic foot ulcers (DFUs) necessitate offloading for effective healing.
• Poor adherence to removable offloading devices is a significant clinical challenge.
• Previous adherence measurement methods had limitations, hindering accurate behavioral insights.

Purpose of the Study:

• To develop and validate a novel method for objectively tracking adherence to offloading devices during ambulation and static weight-bearing.
• To assess adherence to both a removable cast walker (RCW) and a contralateral shoe-lift simultaneously.

Main Methods:

• Thirty healthy adults were monitored using accelerometers on RCWs, shoe-lifts, and thighs.
• A custom algorithm was developed to classify adherence based on variance thresholds during walking and standing.
• Adherence data was compared against investigator logs and participant diaries over 24 hours.

Main Results:

• The algorithm demonstrated over 99% accuracy in detecting steps and standing in laboratory settings.
• Excellent agreement (ICC > 0.96) was observed between algorithm-derived adherence and diary entries in community monitoring.
• Misclassification error rates were below 3%.

Conclusions:

• A validated method for objectively quantifying adherence to RCWs and shoe-lifts has been established.
• The findings support the use of this method for monitoring real-world offloading behavior in clinical trials.
• This technology has the potential to enhance adherence assessments and be integrated into clinical practice for patient monitoring.