Research and Development of Senti-AI: Tech-enabled precision & predictive respiratory medicine leveraging an innovative wearable medical device
Research and Development of Senti-AI: Tech-enabled precision & predictive respiratory medicine leveraging an innovative wearable medical device
批准号:
10020413
负责人:
金额:
$44.39万
依托单位:
依托单位国家:
英国
项目类别:
Collaborative R&D
财政年份:
2022
资助国家:
英国
项目状态:
已结题
起止时间:
2022 至 --
中文摘要
**背景**:想象一下,对于全球5亿患有长期呼吸系统疾病的人来说,如果他们的肺能准确地告诉他们哪里出了问题,他们的疾病是如何发展的,以及确切的治疗方法,世界将会是什么样子?嗯,它们可以:问题是,在过去的200年里,我们一直在听肺部告诉我们的东西,通过两个连接在金属锥体上的橡胶管。听诊器钝了。全世界有五分之一的人患有呼吸道疾病。它是**第三大死因**,仅NHS每年就花费91亿英镑。在整个欧盟/英国,有形和无形成本分别达到690亿英镑/年和2400亿英镑/年。提供患者护理依赖于接受过听诊(听胸音)培训的医疗保健专业人员来诊断、监测和确定治疗方法。通过优化护理,至少**50%的慢性阻塞性肺病住院** (Echevarria, 2018年)、**75%的哮喘急诊入院** (NHS, 2010年)和**三分之二的哮喘死亡** (NRAD, 2014年)**是可以预防的。**连续的自主家庭胸音监测每天可以挽救数千人的生命,并改善数百万人的生活质量。目前的方法,包括听诊器,都不能做到这一点。**创新**:sentii - tech将从根本上解决这一问题,通过在其正在申请专利的创新智能服装sentii - wear上构建人工智能,提供优化和个性化的呼吸护理。通过在睡觉时经常穿这件t恤,sentii - ai将优化医疗方法,让人们重新控制自己的呼吸健康,并为他们提供最好的生活质量。sentii - ai将检测到这些疾病的发作,并创造机会,在这些疾病发作的最早时刻进行干预——避免住院治疗,提高康复速度。sentii - ai会在需要帮助时自动呼叫帮助。sentii - ai是不受束缚的听诊器。**结果**:该项目将使sentiti - tech能够构建、培训和验证人工智能,以监测sentiti - wear捕获的呼吸和心音,并提供量身定制的建议和建议。大多数呼吸系统疾病可以在家中得到充分治疗,只要在适当的时间发现并开始进行适当的监测。sentii - ai智能设备系统将使这种卓越的护理民主化,消除很大一部分呼吸系统住院。这一创新将提高生活质量,并通过及时和个性化的治疗减少可避免的死亡:技术支持的精确和预测性呼吸医学。
英文摘要
**Background**: Imagine what the world would be like for the 500 million people globally suffering with long-term respiratory illnesses, if their lungs could tell them exactly what was wrong, how their illness was progressing, and precisely what to do about it? Well, they can: the problem is we've been listening to what the lungs can tell us, for the past 200 years, with two rubber tubes attached to a metal cone.The stethoscope is blunt.Respiratory disease affects one-in-five people worldwide. It is the **third leading cause-of-death**, costing the NHS alone £9.1bn/year_._ Across the EU/UK combined, tangible and intangible costs reach **£69bn/year** an**d £240bn/year** respectively.Providing patient care relies on healthcare professionals trained in auscultation (listening to chest sounds) to diagnose, monitor, and determine treatments. At least **50% of COPD hospitalisations** (Echevarria, 2018), **75% of asthma emergency admissions** (NHS, 2010), and **two-thirds of asthma deaths** (NRAD, 2014) **are preventable with optimised care.** Continuous autonomous home monitoring of chest sounds could save thousands of lives each day and improve quality-of-life for millions.Current approaches, including the stethoscope, cannot deliver this.**Innovation**: Senti-Tech will radically address this problem by delivering optimised and personalised respiratory care, through artificial intelligence built onto their patent-pending innovative smart garment, Senti-Wear. By wearing this T-shirt regularly whilst sleeping, Senti-AI will optimise medical treatments giving people back control over their respiratory health and offering them the best possible quality of life. Senti-AI will detect attacks of these diseases and create opportunities for intervening at the earliest possible moment in these attacks -avoiding hospitalisation and improving speed of recovery. Senti-AI will automatically call for help when help is needed.Senti-AI is the stethoscope unchained.**Outcomes**: This project will enable Senti-Tech to build, train, and validate anArtificial Intelligence to monitor the breath and heart sounds captured by Senti-Wear, providing tailored recommendations and advice. Most respiratory illnesses can be treated adequately at home, provided attacks are caught at the right time and appropriate monitoring is initiated.The Senti-AI intelligent device system will democratise this excellence-in-care, eliminating a large portion of respiratory hospital admissions. This innovation will improve quality-of-life, and reduce avoidable deaths through prompt and personalised treatment: tech-enabled precision and predictive respiratory medicine.
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国内基金
海外基金
水稻边界发育缺陷突变体abnormal boundary development(abd)的基因克隆与功能分析
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批准号:32070202
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项目类别:面上项目
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资助金额:58.0万元
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批准年份:2020
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负责人:汪泉
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依托单位:
Development of a Linear Stochastic Model for Wind Field Reconstruction from Limited Measurement Data
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批准号:--
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项目类别:--
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资助金额:40万元
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批准年份:2020
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负责人:Vikrant Gupta
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依托单位: