New signal processing, circuits and materials for robust and affordable capacitively-coupled electrocardiography
新的信号处理、电路和材料,用于稳定且经济实惠的电容耦合心电图
基本信息
- 批准号:514369-2017
- 负责人:
- 金额:$ 14.82万
- 依托单位:
- 依托单位国家:加拿大
- 项目类别:Collaborative Research and Development Grants
- 财政年份:2018
- 资助国家:加拿大
- 起止时间:2018-01-01 至 2019-12-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
The electrocardiogram (ECG) is one of the best tools available to clinicians to diagnose heart disease. Unfortunately, it is unsuitable for long-term monitoring because present-day systems use adhesive electrodes and cumbersome wires to connect to the patient. In recent years, a new contactless capacitively-coupled ECG (cECG) technology has been proposed, which uses capacitive effects to unobtrusively capture the heart's electrical signals. Not only does this greatly improve patient comfort by avoiding the electrodes' adhesion to the skin, the electrodes can be integrated into a mattress allowing for convenient long-term monitoring. *This project is partnership between three professors across two universities and two industrial partners, namely SIG.NUM Pre-emptive Health Care and SPERA Medical Technologies. SIG.NUM has a prototype cECG system that is presently advancing through the regulatory milestones and clinical trials. Although it is a great step forward for patient comfort and enabling long-term monitoring, several research challenges have been identified whose resolution will help SIG.NUM develop a very-low-cost cECG. The research will focus on novel signal processing algorithms and custom integrated circuits to capture the heart's electrical signals and decrease the device's sensitivity to body movements. *SPERA Medical Technologies is investigating ECG signals in conjunction with genetic markers for cardiac disease. Their involvement in the project will ensure that the ECG signals measured by the next-generation of contactless system will have the signal quality needed to early diagnosis of cardiac disease.*In addition to NSERC, this project is supported by MEDTEQ, Quebec's Consortium for Industrial Research and Innovation in Medical Technology.*Over the course of the project, six PhD students, two MASc students and one post-doctoral fellow will be trained to address state-of-the art challenges in microelectronics, sensors, distributed signal processing and printable circuit materials.
心电图(ECG)是临床医生可诊断心脏病的最佳工具之一。不幸的是,它不适合长期监测,因为当今的系统使用粘合电极和繁琐的电线与患者连接。近年来,已经提出了一种新的非接触电容耦合ECG(CECG)技术,该技术使用电容效应来毫不客气地捕获心脏的电信号。这不仅可以通过避免电极对皮肤的粘附来极大地改善患者的舒适感,而且可以将电极集成到床垫中,从而可以方便地进行长期监测。 *该项目是两所大学的三位教授与两名工业伙伴的合作伙伴关系,即Sig.num先发制人的医疗保健和Spera医疗技术。 SIG.NUM具有一个原型CECG系统,目前正在通过监管里程碑和临床试验进行前进。尽管这是患者舒适并实现长期监测的迈出的一大步,但已经确定了一些研究挑战,它们的分辨率将有助于SIG.NUM开发出非常低的成本CECG。该研究将重点放在新型的信号处理算法和自定义集成电路上,以捕获心脏的电信号并降低设备对人体运动的敏感性。 *Spera Medical Technologies正在研究心电图和心脏病的遗传标记。他们参与该项目将确保通过非接触式系统的下一代衡量的心电图信号具有早期诊断心脏病所需的信号质量。医疗技术研究与创新。电路材料。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Gagnon, Ghyslain其他文献
Multistatic Radar Placement Optimization for Cooperative Radar-Communication Systems
- DOI:
10.1109/lcomm.2018.2837913 - 发表时间:
2018-08-01 - 期刊:
- 影响因子:0
- 作者:
Ben Kilani, Moez;Gagnon, Ghyslain;Gagnon, Francois - 通讯作者:
Gagnon, Francois
Measuring Disentanglement: A Review of Metrics
- DOI:
10.1109/tnnls.2022.3218982 - 发表时间:
2022-11-14 - 期刊:
- 影响因子:10.4
- 作者:
Carbonneau, Marc-Andre;Zaidi, Julian;Gagnon, Ghyslain - 通讯作者:
Gagnon, Ghyslain
Multiple instance learning: A survey of problem characteristics and applications
- DOI:
10.1016/j.patcog.2017.10.009 - 发表时间:
2018-05-01 - 期刊:
- 影响因子:8
- 作者:
Carbonneau, Marc-Andre;Cheplygina, Veronika;Gagnon, Ghyslain - 通讯作者:
Gagnon, Ghyslain
Detection of alarms and warning signals on an digital in-ear device
- DOI:
10.1016/j.ergon.2012.07.001 - 发表时间:
2013-11-01 - 期刊:
- 影响因子:3.1
- 作者:
Carbonneau, Marc-Andre;Lezzoum, Narimene;Gagnon, Ghyslain - 通讯作者:
Gagnon, Ghyslain
Feature Learning from Spectrograms for Assessment of Personality Traits
- DOI:
10.1109/taffc.2017.2763132 - 发表时间:
2020-01-01 - 期刊:
- 影响因子:11.2
- 作者:
Carbonneau, Marc-Andre;Granger, Eric;Gagnon, Ghyslain - 通讯作者:
Gagnon, Ghyslain
Gagnon, Ghyslain的其他文献
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{{ truncateString('Gagnon, Ghyslain', 18)}}的其他基金
Advanced devices and algorithms for energy disaggregation in buildings
用于建筑物能量分解的先进设备和算法
- 批准号:
RGPIN-2017-06469 - 财政年份:2022
- 资助金额:
$ 14.82万 - 项目类别:
Discovery Grants Program - Individual
Advanced devices and algorithms for energy disaggregation in buildings
用于建筑物能量分解的先进设备和算法
- 批准号:
RGPIN-2017-06469 - 财政年份:2021
- 资助金额:
$ 14.82万 - 项目类别:
Discovery Grants Program - Individual
New signal processing, circuits and materials for robust and affordable capacitively-coupled electrocardiography
新的信号处理、电路和材料,用于稳定且经济实惠的电容耦合心电图
- 批准号:
514369-2017 - 财政年份:2020
- 资助金额:
$ 14.82万 - 项目类别:
Collaborative Research and Development Grants
Advanced devices and algorithms for energy disaggregation in buildings
用于建筑物能量分解的先进设备和算法
- 批准号:
RGPIN-2017-06469 - 财政年份:2020
- 资助金额:
$ 14.82万 - 项目类别:
Discovery Grants Program - Individual
Low Latency and Highly Secure Protocols for Critical Communications
适用于关键通信的低延迟和高度安全协议
- 批准号:
494694-2016 - 财政年份:2020
- 资助金额:
$ 14.82万 - 项目类别:
Collaborative Research and Development Grants
Feature Learning of Critical Live Performance Audio Characteristics for a Virtual Sound Engineer
虚拟音响工程师关键现场表演音频特征的特征学习
- 批准号:
538056-2019 - 财政年份:2019
- 资助金额:
$ 14.82万 - 项目类别:
Engage Grants Program
Low Latency and Highly Secure Protocols for Critical Communications
适用于关键通信的低延迟和高度安全协议
- 批准号:
494694-2016 - 财政年份:2019
- 资助金额:
$ 14.82万 - 项目类别:
Collaborative Research and Development Grants
Advanced devices and algorithms for energy disaggregation in buildings
用于建筑物能量分解的先进设备和算法
- 批准号:
RGPIN-2017-06469 - 财政年份:2019
- 资助金额:
$ 14.82万 - 项目类别:
Discovery Grants Program - Individual
Advanced devices and algorithms for energy disaggregation in buildings
用于建筑物能量分解的先进设备和算法
- 批准号:
RGPIN-2017-06469 - 财政年份:2018
- 资助金额:
$ 14.82万 - 项目类别:
Discovery Grants Program - Individual
Advanced devices and algorithms for energy disaggregation in buildings
用于建筑物能量分解的先进设备和算法
- 批准号:
RGPIN-2017-06469 - 财政年份:2017
- 资助金额:
$ 14.82万 - 项目类别:
Discovery Grants Program - Individual
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