Daich Varela Malena, Sanders Villa Alejandro, Pontikos Nikolas, Crossland Michael D, Michaelides Michel
Moorfields Eye Hospital, London, UK.
UCL Institute of Ophthalmology, University College London, 11-43 Bath Street, London, EC1V 9EL, UK.
Graefes Arch Clin Exp Ophthalmol. 2025 Feb;263(2):279-289. doi: 10.1007/s00417-024-06634-3. Epub 2024 Sep 19.
Digital health is wielding a growing influence across all areas of healthcare, encompassing various facets such as telemedicine, artificial intelligence (AI), and electronic healthcare records. In Ophthalmology, digital health innovations can be broadly divided into four categories: (i) self-monitoring home devices and apps, (ii) virtual and augmented reality visual aids, (iii) AI software, and (iv) wearables. Wearable devices can work in the background, collecting large amounts of objective data while we do our day-to-day activities, which may be ecologically more valid and meaningful to patients than that acquired in traditional hospital settings. They can be a watch, wristband, piece of clothing, glasses, cane, smartphone in our pocket, earphones, or any other device with a sensor that we carry with us. Focusing on retinal diseases, a key challenge in developing novel therapeutics has been to prove a meaningful benefit in patients' lives and the creation of objective patient-centred endpoints in clinical trials. In this review, we will discuss wearable devices collecting different aspects of visual behaviour, visual field, central vision, and functional vision, as well as their potential implementation as outcome measures in research/clinical trial settings. The healthcare landscape is facing a paradigm shift. Clinicians have a key role of collaborating with the development and fine-tuning of digital health innovations, as well as identifying opportunities where they can be leveraged to enhance our understanding of retinal diseases and improve patient outcomes.
数字健康在医疗保健的各个领域正发挥着越来越大的影响力，涵盖远程医疗、人工智能（AI）和电子健康记录等多个方面。在眼科领域，数字健康创新大致可分为四类：（i）家庭自我监测设备和应用程序；（ii）虚拟现实和增强现实视觉辅助工具；（iii）人工智能软件；（iv）可穿戴设备。可穿戴设备可以在后台运行，在我们进行日常活动时收集大量客观数据，这对于患者来说，可能比在传统医院环境中获取的数据在生态学上更有效且更有意义。它们可以是手表、腕带、一件衣服、眼镜、手杖、我们口袋里的智能手机、耳机，或者任何其他我们随身携带的带有传感器的设备。聚焦于视网膜疾病，开发新型疗法的一个关键挑战在于证明对患者生活有显著益处，并在临床试验中创建以患者为中心的客观终点指标。在本综述中，我们将讨论收集视觉行为、视野、中心视力和功能性视力等不同方面信息的可穿戴设备，以及它们在研究/临床试验环境中作为结局指标的潜在应用。医疗保健格局正在经历范式转变。临床医生在数字健康创新的开发和微调过程中，以及在识别可利用这些创新来增进我们对视网膜疾病的理解并改善患者治疗效果的机会方面，发挥着关键作用。
