Healthcare Wearables for Independent Living

独立生活的医疗保健可穿戴设备

• 批准号: EP/W031744/1
• 负责人: David Clifton
• 金额: $ 154.95万
• 依托单位: University of Oxford
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FW031744%2F1
• 关键词: Healthcare; Wearables; Independent; Living

Around 1 in 4 people have multiple long-term conditions (MLTCs) rising to up to two-thirds in people over the age of 65 years. Treatment for this group is estimated to take up 70% of health care expenditure. Such people have poorer health, poorer quality of life, and a higher risk of dying. Key challenges for this group of people include maintaining their independence in their homes, avoiding developing further conditions that can threaten their health, and which would further impair their quality of life and minimising the high burden of healthcare for this group potentially made worse by uncoordinated health and social care. Our challenge is to improve outcomes through informed self-care and maintaining independence, while reducing healthcare costs. The current model for many MLTCs is for people to present to urgent care services when they can no longer cope at home. This reactive approach leads to frequent use of emergency hospital services when a severe episode occurs, shifting the focus of care to hospitals. Management then follows generic pathways within acute healthcare, in an attempt to stabilise the condition of the patient. Information-driven technologies will enable people to perform their own health management, which will change the model of care. Individuals will be able to manage their condition proactively. The integration of knowledge concerning individuals' co-morbidities (which are common in MLTCs) will allow personalised therapy, further maintaining independence, improving patient outcomes, and optimising the use of resources.The proposed programme "Healthcare Wearables for Independent Living" (HW-IL) aims to develop, for the first time, a suite of predictive tools, based on regular wearable devices, to allow a step-change in the self-care of patients with MLTCs, and in the maintenance of their independence by avoiding deterioration. Patients and their carers will be guided, using such tools, to preventative management. For the first time, such tools will incorporate an integrated approach, exploiting patient-worn devices (at or near the patient), and healthcare data (from GPs and hospital information systems), working in real-time. All work will be ethically approved, and accord to the highest standards of patient confidentiality.

大约四分之一的人患有多种长期疾病(MLTC)，65岁以上的人高达三分之二。据估计，这一群体的治疗占卫生保健支出的70%。这些人的健康状况较差，生活质量较差，死亡风险较高。这群人面临的关键挑战包括保持他们在家中的独立性，避免进一步发展可能威胁他们健康并进一步损害他们的生活质量的疾病，以及最大限度地减少这一群体的沉重医疗负担，这些负担可能会因不协调的医疗保健和社会护理而恶化。我们的挑战是通过知情的自我护理和保持独立性来改善结果，同时降低医疗成本。许多MLTC目前的模式是，当人们在家里不能再应付时，他们向紧急护理服务提出。这种反应性方法导致在发生严重事件时频繁使用紧急医院服务，将护理重点转移到医院。然后，管理层遵循急性医疗保健的一般路径，试图稳定患者的病情。信息驱动的技术将使人们能够进行自己的健康管理，这将改变护理模式。个人将能够主动管理自己的病情。整合有关个人共病的知识(在MLTC中很常见)将允许个性化治疗，进一步保持独立性，改善患者预后，并优化资源的使用。拟议的计划“独立生活医疗可穿戴设备”(HW-IL)旨在首次开发一套基于常规可穿戴设备的预测工具，以允许MLTC患者的自我护理和通过避免恶化来保持他们的独立性的阶段性变化。将使用这些工具指导患者及其照顾者进行预防性管理。这类工具将首次融入一种集成方法，利用患者佩戴的设备(在患者或患者附近)和医疗数据(来自全科医生和医院信息系统)，实时工作。所有工作都将得到道德上的批准，并符合患者保密的最高标准。

项目成果

Digital Health and Machine Learning Technologies for Blood Glucose Monitoring and Management of Gestational Diabetes.

• DOI: 10.1109/rbme.2023.3242261
• 发表时间: 2024
• 期刊: IEEE reviews in biomedical engineering
• 影响因子: 17.6
• 作者: Lu HY;Ding X;Hirst JE;Yang Y;Yang J;Mackillop L;Clifton DA
• 通讯作者: Clifton DA

Tetanus Severity Classification in Low-Middle Income Countries through ECG Wearable Sensors and a 1D-Vision Transformer

• DOI: 10.3390/biomedinformatics4010016
• 发表时间: 2024-01
• 期刊: BioMedInformatics
• 作者: Ping Lu;Zihao Wang;Hai Duong Ha Thi;Ho Bich Hai;Louise Thwaites;David A. Clifton

Data Encoding For Healthcare Data Democratisation and Information Leakage Prevention

医疗保健数据民主化和信息泄露预防的数据编码

• DOI: 10.21203/rs.3.rs-2922432/v1
• 发表时间: 2023
• 作者: Zhu T

Digital Health and Machine Learning Technologies for Blood Glucose Monitoring and Management of Gestational Diabetes

用于血糖监测和妊娠糖尿病管理的数字健康和机器学习技术

• DOI: 10.36227/techrxiv.21919254
• 发表时间: 2023
• 作者: Clifton D

2D-WinSpatt-Net: A Dual Spatial Self-Attention Vision Transformer Boosts Classification of Tetanus Severity for Patients Wearing ECG Sensors in Low- and Middle-Income Countries.

• DOI: 10.3390/s23187705
• 发表时间: 2023-09-06
• 期刊: Sensors (Basel, Switzerland)
• 作者: Lu P;Creagh AP;Lu HY;Hai HB;Vital Consortium;Thwaites L;Clifton DA
• 通讯作者: Clifton DA