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Quantum Imaging for Monitoring of Wellbeing & Disease in Communities

Quantum Imaging for Monitoring of Wellbeing & Disease in Communities
用于健康监测的量子成像
批准号:
EP/T021020/1
负责人:
Jonathan Cooper
金额:
$716.74万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2021
资助国家:
英国
项目状态:
未结题
起止时间:
2021 至 --

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中文摘要
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英文摘要
We have identified the home as the place where future transformational healthcare changes will occur with the greatest impact potential. Our vision is that the home of the future will be an environment that has the ability to follow our everyday movements, behaviour and wellness. In this sense, it will become an extension of our physical bodies, providing us with feedback, advice and alerts in the presence of anomalies in the data streams collected by new-generation sensors. The analysis of the data-streams from the sensors will be based on clinically approved models, thus effectively bringing highly trained expertise directly to the living environment. Remote detection and monitoring of parameters such as gait, macro and micro-movements, blood flow, heart rate and potentially even brain function, when combined with data-driven models, will allow to both monitor health and the onset of non-communicable diseases (NCDs) but also recovery from NCDs or surgery with personalised and continuously updated re-habilitation programmes. This therefore takes the concept of precision medicine and extends it to our overall physical and mental well-being, with the vision of enabling "precision healthcare" delivered to the home.The sensors we are proposing are based on new-generation quantum-inspired cameras. These cameras can detect extremely low levels of light, thus rendering their presence in the home completely unobtrusive. The cameras can also detect the arrival time of light at the sensor with very high precision and at very high frame rates. The combination of these features enables the measurement of both macro-movement (in a similar fashion to more common cameras) and micro-movement (not currently possible with current, low-cost or low form-factor cameras). Micro-movement detection is sufficiently precise to capture nanometric variations in skin/body shape and thus directly detect blood flow, monitoring the precise shape and variations of heart beat. Future, very ambitious plans, include extending this capability to the brain. Our cameras can also be combined with RF technology to provide richer data, e.g. Doppler signals directly related to speed of movement. All these indicators will be fed into machine learning models that monitor, learn and are updated over time and, most importantly, adapt to the individuals inhabiting the home environment. Thus, the systems will quickly adapt and evolve for bespoke individuals, providing precision healthcare monitoring and feedback.Alongside the engineers and computer scientists working on the sensors and data analysis, our programme involves clinicians who will provide the interpretation models for our data and also partners who will give us access to new-generation intelligent homes inhabited by users who are already beta-testing sensors monitoring for example gross movement.
期刊论文(10)
专著(0)
科研奖励(0)
会议论文
DOI: 10.1109/jsen.2020.3035960
发表时间: 2021-02-15
期刊: IEEE SENSORS JOURNAL
影响因子: 4.3
作者: [Ashleibta, Aboajeila Milad, Abbasi, Qammer H., Imran, Muhammad Ali]
通讯作者: Imran, Muhammad Ali
Alignment-free construction of double emulsion droplet generation devices incorporating surface wettability contrast.
结合表面润湿性对比的双乳液液滴生成装置的免对准结构。
DOI: 10.1039/d3lc00584d
发表时间: 2023
期刊: Lab on a chip
影响因子: 6.1
作者: [Aslan Y]
通讯作者: Aslan Y
LoRa-based Privacy-Aware and Contactless Surveillance in Next-generation Smart Homes
下一代智能家居中基于 LoRa 的隐私感知和非接触式监控
DOI: 10.1109/usnc-ursi52151.2023.10238314
发表时间: 2023
期刊:
影响因子: --
作者: [Farooq M]
通讯作者: Farooq M
DOI: 10.1080/19490976.2023.2199659
发表时间: 2023-01
期刊: Gut microbes
影响因子: 12.2
作者: []
通讯作者:
8
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