Coherent ultra-wideband radar for biosensing in dementia

近年来，出现了广泛的用于医疗应用的数字和可穿戴传感技术。一个关键的挑战仍然是需要用户努力或输入的可穿戴设备的合规性。这是可穿戴设备影响有限的主要原因。因此，一种对用户没有负担的技术将是非常可取的。低功耗片上雷达的最新进展为室内应用中部署的微型、低成本系统提供了新的机会。这项研究将探索使用相干超宽带雷达来感知人类行为和生理。要考虑的感知目标包括：呼吸、心率、心率变异性、在二维空间中的位置、步态和运动速度。这些参数将作为智能家居平台的一部分进行检测，该平台用于护理远离医院的痴呆症患者。这将为在康复中感知步态、检测跌倒、监测生命体征变异性和睡眠活动、观察运动模式等提供一种强大、不引人注目的工具。这样的技术还将避免相机或成像技术存在的隐私问题。具体的研究目标包括：(1)开发基于先进的数字信号处理和机器学习技术从雷达数据中提取高级信息的实时方法；(2)通过验证试验对照黄金标准评估性能；(3)调查考虑不同空间配置、伪影和噪声源的现实世界部署情景；(4)进一步推进在现实世界情景中改进稳健性的方法；(5)展示方法在预期最终用途中的实用性。这项研究符合以下UKRI/EPSRC的研究主题：“辅助技术、康复和肌肉骨骼生物力学”、“临床技术”、“射频和微波设备”、“传感器和仪器”。

Recent years have seen a wide range of digital and wearable sensing technologies for medical applications. A key challenge remains the compliance of wearable devices that require effort or input from the user. This has been the main reason the impact of wearable device has been limited. A technology with no burden to the user would be thus highly desirable. Recent advances in low power radar-on-chip have enabled new opportunities for miniature, low cost systems deployed in indoor applications. This research will explore the use of coherent ultra-wideband radar for sensing human behaviour and physiology. Sensing targets that will be considered include: respiration, heart rate, heart rate variability, position in two-dimensional space, gait, and movement speed. These parameters will be detected as part of a smart-home platform for the care of people living with dementia, away from hospital premises. This will provide a powerful, unobtrusive tool for sensing gait in rehabilitation, detecting falls, monitoring vital sign variability and sleep activity, observing movement patterns, etc. Such a technology would additionally avoid privacy concerns that exist with camera or imaging technologies. Specific research objectives include: (1) to develop real-time methods for extracting high level information from radar data based on advanced digital signal processing and machine learning techniques; (2) to assess performance against gold standards through validation trials; (3) to investigate real-world scenarios for deployment considering different space configurations, artefact and noise sources; (4) to further advance methods for improving robustness in real-world scenarios; (5) to demonstrate utility of methods in the intended end use. This research aligns with the following UKRI/EPSRC research themes: "Assistive technology, rehabilitation and musculoskeletal biomechanics", "Clinical technologies", "RF and microwave devices", "Sensors and instrumentation".