Moving the mountain: Non-conventional human body monitoring to enable energy harvester powered systems
Moving the mountain: Non-conventional human body monitoring to enable energy harvester powered systems
批准号:
EP/M009262/1
负责人:
Alex Casson
金额:
$12.8万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2015
资助国家:
英国
项目状态:
已结题
起止时间:
2015 至 --
中文摘要
可穿戴传感器是高度小型化的电子设备,易于放置在人体上,可以方便地监测一系列身体参数,方便疾病诊断,甚至在危急情况下自动报警呼救。它们正迅速成为对人体进行长时间监测的下一代设备,并对管理我们的老龄化人口产生重大影响:在自动监测和老年受试者报警方面;在年轻人中提倡积极和预防性的保健和锻炼。然而,随着我们整合更多耗电的复杂电子产品,提供新的传感器,增强其功能,并保持电池寿命是一项重大的工程挑战。为了解决这个问题,未来的设备包括能量收集是至关重要的:在这里,现有的电池是通过利用环境中可用的固有能量来补充的。因此,能量收集是制造动力自主传感器的唯一方法,并且可以超越电池提供的有限寿命。然而,适合佩戴在人体上的最先进的微型能量采集器只能提供非常少量的输出功率。为了充分实现这些潜在的好处,有必要设计新的技术来缩小目前可穿戴传感器所需的功率和微型能量采集器提供的功率之间的差距。该项目将通过在人体非传统部位进行人体监测来弥补这一差距。目前的方法是把能量收集器放在需要的生理信号最强的地方;该项目将设计技术,将生理监测转移到可以收获最大能量的地方。测量身体非传统部位的生理参数,如手臂和腿,意味着信号较弱,更容易受到由于运动而产生的人工制品的干扰。这也意味着有更多的能量可用于采集,并为传感器和信号处理提供动力,以纠正人工制品的存在。随着可穿戴传感器开始包括能量收集器,这项研究将调查这些新的折衷方案。特别是,它将建立之间的权衡:生理信号强度,运动伪影损坏收集的信号,和能量收集潜力。这将涉及从身体的非常规部位收集生理数据,并创建用于分析信号的数字信号处理方法,并处理与传统监测相比的新运动伪影。成功的结果将有助于我们在数字信号处理方面的知识,并增强我们创建可以执行复杂信号处理的自供电传感器的能力。这将为未来的可穿戴传感器、个性化和预防性医疗保健以及我们解决英国人口老龄化对医疗、社会和个人影响的能力带来重大好处。
英文摘要
Wearable sensors are highly miniaturised electronic devices that are easily placed on the human body and can conveniently monitor a range of body parameters, facilitate diagnosis of diseases, and even automatically raise alarms to summon help in critical situations. They are quickly emerging as next generation devices for the prolonged monitoring of the human body and have substantial impacts for managing our ageing population: both in terms of automatic monitoring and alarm generation in older subjects; and in promoting proactive and preventative healthcare and exercise in younger subjects. However, delivering new sensors, enhancing their functionality, and maintaining battery life as we incorporate more power hungry complex electronics is a major engineering challenge. To resolve this it is crucial that future devices include energy harvesting: here the batteries present are supplemented by using the intrinsic energy available in the environment to power the sensor. As a result, energy harvesting is the only method for creating sensors which are power autonomous and can go beyond the limited lifetimes provided by batteries. However, state-of-the-art miniature energy harvesters which are suitable for wearing on the human body can only provide very small amounts of output power. To realise the full potential benefits from these it is necessary to devise new techniques for closing the current gap between the power required by wearable sensors and the power provided by miniature energy harvesters. This project will bridge this gap by performing human body monitoring in non-conventional places on the body. Current approaches place the energy harvester where the wanted physiological signal is strongest; this project will devise techniques to move the physiological monitoring to where the most power can be harvested. Measuring physiological parameters in non-conventional locations on the body, such as the arms and legs, means the signals are weaker and more prone to interference from artefacts due to motion. It also means that substantially more energy is available for harvesting and to power both the sensor and the signal processing required to correct for the presence of artefacts. The research will investigate these new trade-offs that are available as wearable sensors begin to include energy harvesters. In particular it will establish the trade-off between: physiological signal strength, motion artefact corruption of the collected signal, and energy harvesting potential. This will involve collecting physiological data from non-conventional places on the body and creating digital signal processing approaches for analysing the signals and dealing with the new motion artefacts compared to conventional monitoring. The successful outcomes will contribute to our knowledge on digital signal processing and enhance our ability to create self-powered sensors that can perform complex signal processing. This will provide major benefits to future wearable sensors, to personalised and preventative healthcare, and to our ability to tackle the healthcare, societal, and personal implications of the UK's ageing population.
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Printed electrodes for long term m-Health ECG monitoring
用于长期移动健康心电图监测的印刷电极
DOI:
--
发表时间:
2015
期刊:
影响因子:
--
作者:
[Bachelor, J. C.]
通讯作者:
Bachelor, J. C.
DOI:
10.1016/j.icte.2016.11.003
发表时间:
2016-12-01
期刊:
ICT EXPRESS
影响因子:
5.4
作者:
[Casson, Alexander J., Galvez, Arturo Vazquez, Jarchi, Delaram]
通讯作者:
Jarchi, Delaram
Inkjet printed ECG electrodes for long term biosignal monitoring in personalized and ubiquitous healthcare.
喷墨打印心电图电极,用于个性化和无处不在的医疗保健中的长期生物信号监测。
DOI:
10.1109/embc.2015.7319274
发表时间:
2015
期刊:
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
影响因子:
--
作者:
[Batchelor JC]
通讯作者:
Batchelor JC
DOI:
10.3390/s151229897
发表时间:
2015-12-17
期刊:
Sensors (Basel, Switzerland)
影响因子:
--
作者:
[Casson AJ]
通讯作者:
Casson AJ
DOI:
10.1109/eusipco.2015.7362418
发表时间:
2015-12
期刊:
2015 23rd European Signal Processing Conference (EUSIPCO)
影响因子:
--
作者:
[A. Casson]
通讯作者:
A. Casson
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