Smart Footwear with Embedded Wireless Sensors for Healthcare Applications

用于医疗保健应用的带有嵌入式无线传感器的智能鞋类

• 批准号: 2464869
• 金额: --
• 依托单位: University College London
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2020
• 资助国家: 英国
• 起止时间: 2020 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2464869
• 关键词: Smart; Footwear; Embedded; Wireless; Sensors

This project aims to develop smart footwear to monitor foot loading and gait complications. We will explore several micro/nanomanufacturing techniques to develop pressure/force sensors and integrate them into common footwear products. Such smart footwears and related plantar pressure/force mapping can have direct implications for applications as diverse as gait analysis, performance analysis for sports personnel and for clinically significant applications such as detection and management of diabetic foot ulcers. This involves conceiving miniature wearable pressure/force sensors to address global health challenges, such as the staggering financial and clinical burden of diabetic wound care and amputation. We will exploit high-resolution 3D printing to overcome the prototyping challenges to realise such sensors and integrate them on common footwear products in a cost-effective manner. Finite element modelling of footwear loading and machine learning techniques will support the material selection, sensor placement and the design of embedded electronics for wireless sensing. The sensor data may also be exploited to inform healthcare engineering and clinical decisions, and could also enable real-time feedback training systems (e.g. using a smartphone based wireless monitoring system). The technology developed here could enable early and timely intervention to correct the biomechanical abnormalities underlying typical injuries and diagnosis of diabetic foot ulcers.

该项目旨在开发智能鞋来监控足部负荷和步态并发症。我们将探索几种微/纳米制造技术来开发压力/力传感器，并将它们集成到常见的鞋类产品中。这种智能鞋服和相关的足底压力/力量图可以直接应用于各种应用，如步态分析、运动人员的性能分析，以及临床上重要的应用，如糖尿病足部溃疡的检测和管理。这包括构思微型可穿戴压力/力传感器，以应对全球健康挑战，例如糖尿病伤口护理和截肢带来的惊人经济和临床负担。我们将利用高分辨率3D打印来克服原型挑战，实现这种传感器，并以经济高效的方式将它们集成到常见的鞋类产品上。鞋类负载的有限元建模和机器学习技术将支持材料选择、传感器放置和用于无线传感的嵌入式电子设备的设计。传感器数据还可用于为医疗工程和临床决策提供信息，还可启用实时反馈培训系统(例如，使用基于智能手机的无线监控系统)。这里开发的技术可以使早期和及时的干预，以纠正糖尿病足部溃疡典型损伤和诊断背后的生物力学异常。