Digital Health: Innovative engineering technologies to improve the understanding and management of fatigue

数字健康：创新工程技术，提高对疲劳的理解和管理

• 批准号: EP/W003228/1
• 负责人: Rosalind Adam
• 金额: $ 51.54万
• 依托单位: University of Aberdeen
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FW003228%2F1
• 关键词: Digital; Health; Innovative; engineering; technologies

Fatigue is considered as a "final common pathway": a vague clinical symptom that can result from many different diseases and mechanisms. Our limited understanding of fatigue stems, in part, from its subjective and fluctuating nature and its complex interplay of parameters associated with "tiredness" such as sleep, exercise, and mood. This project will investigate sensory technologies to objectively, accurately and unobtrusively measure fatiguability, as an indicator of fatigue. These measurements will be correlated to sensed data (activity levels, sleep, heart rate, and others) and individuals' self-reports. Granular details will be obtained about patterns in the human fatigue experience. The results will reveal whether there could be distinct, clinically relevant fatigue phenotypes. We will also use longitudinal research (studying participants closely over a several week period). To date, longitudinal fatigue research been limited by statistical analysis methods (such as multilevel modelling) which are unable to detect subtle or complex relationships between fatigue and related life-style factors over time. We will use artificial intelligence algorithms to help analyse and classify these correlations within the sensed data, self-reports and qualitative data.

疲劳被认为是一种“最终共同途径”：一种模糊的临床症状，可由许多不同的疾病和机制引起。我们对疲劳的有限理解部分源于其主观性和波动性，以及与“疲劳”相关的参数（如睡眠，运动和情绪）的复杂相互作用。该项目将研究感官技术，以客观，准确和不显眼地测量疲劳，作为疲劳的指标。这些测量将与感知数据（活动水平，睡眠，心率等）和个人的自我报告相关。将获得关于人类疲劳体验中的模式的颗粒细节。结果将揭示是否可能存在不同的、临床相关的疲劳表型。我们还将使用纵向研究（在几周内密切研究参与者）。迄今为止，纵向疲劳研究受到统计分析方法（如多层次建模）的限制，无法检测疲劳与相关生活方式因素之间随时间变化的微妙或复杂关系。我们将使用人工智能算法来帮助分析和分类感知数据，自我报告和定性数据中的这些相关性。

项目成果

LoGait: LoRa Sensing System of Human Gait Recognition Using Dynamic Time Warping

• DOI: 10.1109/jsen.2023.3297438
• 发表时间: 2023-09
• 期刊: IEEE Sensors Journal
• 影响因子: 4.3
• 作者: Y. Ge;Wenda Li;Muhammad Farooq;Adnan Qayyum;Jingyan Wang;Zikang Chen;Jonathan Cooper;M. Imran;Q. Abbasi

"A Switch Went off in my Whole Body": Lived Experiences of Fatigue and Post-Exertional Malaise in Long Covid

“我全身的开关都关掉了”：长期新冠期间疲劳和劳累后不适的亲身经历

• DOI: 10.1145/3544549.3585846
• 发表时间: 2023
• 作者: Sas C