Department of Bioengineering, University of California San Diego, La Jolla, San Diego, CA 92093, USA.
Department of Computer Science and Engineering, University of California San Diego, La Jolla, San Diego, CA 92093, USA.
Sensors (Basel). 2020 Apr 30;20(9):2570. doi: 10.3390/s20092570.
Glaucoma, the leading cause of irreversible blindness, affects >70 million people worldwide. Lowering intraocular pressure via topical administration of eye drops is the most common first-line therapy for glaucoma. This treatment paradigm has notoriously high non-adherence rates: ranging from 30% to 80%. The advent of smart phone enabled technologies creates promise for improving eyedrop adherence. However, previous eyedrop electronic monitoring solutions had awkward medication bottle adjuncts and crude software for monitoring the administration of a drop that adversely affected their ability to foster sustainable improvements in adherence. The current work begins to address this unmet need for wireless technology by creating a "smart drop" bottle. This medication bottle is instrumented with sensing electronics that enable detection of each eyedrop administered while maintaining the shape and size of the bottle. This is achieved by a thin electronic force sensor wrapped around the bottle and underneath the label, interfaced with a thin electronic circuit underneath the bottle that allows for detection and wireless transmission to a smart-phone application. We demonstrate 100% success rate of wireless communication over 75 feet with <1% false positive and false negative rates of single drop deliveries, thus providing a viable solution for eyedrop monitoring for glaucoma patients.
青光眼是全球导致不可逆性失明的主要原因，影响着全球超过 7000 万人。通过局部滴眼药水来降低眼内压是治疗青光眼最常用的一线疗法。这种治疗模式的不遵医嘱率很高：从 30%到 80%不等。智能手机技术的出现为提高滴眼剂的依从性带来了希望。然而，以前的滴眼电子监测解决方案需要使用不自然的滴眼药瓶附件和简陋的软件来监测滴药，这对提高其在提高依从性方面的可持续性产生了不利影响。目前的工作通过创建一个“智能滴药瓶”开始解决这一未满足的无线技术需求。这种药瓶配备了感应电子设备，能够在保持瓶身形状和大小的同时检测每次滴眼剂的使用情况。这是通过在瓶子周围和标签下方包裹一个薄的电子力传感器，并与瓶子下方的一个薄电子电路接口来实现的，从而可以进行检测并将无线传输到智能手机应用程序。我们演示了在超过 75 英尺的距离内，无线通信的成功率为 100%，单个滴液的误报和漏报率<1%，从而为青光眼患者的滴眼监测提供了一种可行的解决方案。
