Havey Robert M, Patwardhan Avinash G, Stuck Rodney M, Keen Stephanie A, Muriuki Muturi G
Edward Hines, Jr. VA Hospital, Hines, IL, USA.
Loyola University Medical Center, Maywood, IL, USA.
J Diabetes Sci Technol. 2024 Dec 23:19322968241304751. doi: 10.1177/19322968241304751.
Treatment of diabetes and its complications is a primary health care expense. Up to 25% of people with diabetes will develop diabetic foot ulcers (DFUs). Removable cast walker (RCW) boots commonly prescribed for DFU treatment, promote healing, and provide offloading and wound protection. Patient RCW removal for hygiene and wound care can lead to decreased adherence and treatment effectiveness. This study evaluated a new system for wear-time adherence measurement using multiple sensor types.
An electronic wear-time monitor was developed, which included internal and external temperature sensors, an accelerometer, and capacitive proximity foot and ankle sensors. Time-stamped and date-stamped data were saved once per minute for up to 22 days. Ten healthy volunteer subjects were recruited to wear an RCW for two weeks while keeping a diary of don/doff times. Sensor data were then compared with volunteers' wear diaries using confusion matrix predictive analytics.
Algorithms were developed for data processing. Correlation coefficients between algorithms and diaries were calculated for individual and multiple sensor combinations. Differential temperature and accelerometer algorithms were significantly better at predicting subject wear-time than individual temperature sensor algorithms ( = .009, = .001, respectively). Foot proximity had significantly better correlation with subject diaries than temperature ( = .024), and acceleration algorithms ( = .005). Multi-sensor analysis showed high correlation (.96) with wear-time from subject diaries.
Removable cast walker wear-time can be accurately determined using an electronic data recorder and multiple sensors. Wear-time measurement accuracy can be improved using algorithms that operate on data from multiple sensors that use a variety of sensor technologies.
糖尿病及其并发症的治疗是一项主要的医疗保健费用。高达25%的糖尿病患者会发展为糖尿病足溃疡（DFU）。常用于DFU治疗的可拆卸石膏步行靴（RCW）可促进愈合，并提供减压和伤口保护。患者为了卫生和伤口护理而取下RCW可能会导致依从性和治疗效果下降。本研究评估了一种使用多种传感器类型测量佩戴时间依从性的新系统。
开发了一种电子佩戴时间监测器，其中包括内部和外部温度传感器、加速度计以及电容式接近脚部和脚踝传感器。带有时间戳和日期戳的数据每分钟保存一次，最长保存22天。招募了10名健康志愿者受试者，让他们穿着RCW两周，同时记录穿上/脱下的时间。然后使用混淆矩阵预测分析将传感器数据与志愿者的佩戴日记进行比较。
开发了用于数据处理的算法。计算了个体和多个传感器组合的算法与日记之间的相关系数。差分温度和加速度计算法在预测受试者佩戴时间方面明显优于单个温度传感器算法（分别为P = 0.009，P = 0.001）。足部接近度与受试者日记的相关性明显优于温度（P = 0.024）和加速度算法（P = 0.005）。多传感器分析显示与受试者日记中的佩戴时间具有高度相关性（0.96）。
使用电子数据记录器和多个传感器可以准确确定可拆卸石膏步行靴的佩戴时间。使用对来自多种传感器技术的多个传感器的数据进行操作的算法可以提高佩戴时间测量的准确性。
