Biomedical Simulations and Imaging Lab, School of Electrical and Computer Engineering, National Technical University of Athens, 15780 Athens, Greece.
Sensors (Basel). 2022 Aug 4;22(15):5818. doi: 10.3390/s22155818.
Patients usually deviate from prescribed medication schedules and show reduced adherence. Even when the adherence is sufficient, there are conditions where the medication schedule should be modified. Crucial drug-drug, food-drug, and supplement-drug interactions can lead to treatment failure. We present the development of an internet of medical things (IoMT) platform to improve medication adherence and enable remote treatment modifications. Based on photos of food and supplements provided by the patient, using a camera integrated to a portable 3D-printed low-power pillbox, dangerous interactions with treatment medicines can be detected and prevented. We compare the medication adherence of 14 participants following a complex medication schedule using a functional prototype that automatically receives remote adjustments, to a dummy pillbox where the adjustments are sent with text messages. The system usability scale (SUS) score was 86.79, which denotes excellent user acceptance. Total errors (wrong/no pill) between the functional prototype and the dummy pillbox did not demonstrate any statistically significant difference ( = 0.57), but the total delay of the intake time was higher ( = 0.03) during dummy pillbox use. Thus, the proposed low-cost IoMT pillbox improves medication adherence even with a complex regimen while supporting remote dose adjustment.
患者通常会偏离规定的用药时间表，表现出较低的依从性。即使依从性足够，也存在需要修改用药时间表的情况。关键的药物相互作用、食物与药物相互作用以及补充剂与药物相互作用可能导致治疗失败。我们提出了一种医疗物联网 (IoMT) 平台的开发，以提高用药依从性并实现远程治疗修改。基于患者提供的食物和补充剂的照片，使用集成在便携式 3D 打印低功耗药盒中的摄像头，可以检测和预防与治疗药物的危险相互作用。我们比较了使用自动接收远程调整的功能原型和发送调整信息的虚拟药盒的 14 名参与者的用药依从性。系统可用性量表 (SUS) 得分为 86.79，这表示用户接受度非常高。功能原型和虚拟药盒之间的总错误（漏服/错服）没有表现出任何统计学上的显著差异（ = 0.57），但在使用虚拟药盒时，摄入时间的总延迟更高（ = 0.03）。因此，所提出的低成本 IoMT 药盒可提高用药依从性，即使是在复杂的治疗方案下，同时支持远程剂量调整。
