教学人员
陈朗遇教授
助理教授
PhD (UNSW), MSc Epidemiology and Biostatistics (CUHK), BSc (Hons) Physiotherapy (PolyU), Registered Physiotherapist (Hong Kong and Australia)
- ST519
- +852 2766 7093
- lloydly.chan@polyu.edu.hk
ORCID ID简历
陈朗遇教授于香港理工大学(理大)取得物理治疗学(荣誉)理学士学位，并于香港中文大学完成流行病学与生物统计学理学硕士课程，获颁最佳学业成绩及毕业生代表奬。透过澳洲研究培训计划，他其后获新南韦尔斯大学(UNSW)颁授哲学博士学位。
他的临床经验涵盖香港公立医院的急症、门诊及复康服务，以及悉尼的临床工作。在重返理大前，他曾任新南韦尔斯大学讲师，负责设计及统筹神经物理治疗课程。他统筹的「神经系统临床实践」课程于2025年获颁健康科学学院年度最佳课程奖。
陈教授主导开发的WatchWalk算法，利用腕戴式传感器量度日常步行速度、步态质素及活动水平。该算法已应用于多项大型国际人口研究，并透过网上数据处理平台供国际研究团队使用。这项技术亦已独家授权予一家于澳洲证券交易所上市的科技公司，推动研究成果的知识转移及商业应用。他的研究获澳洲中风基金会及慈善捐助者支持。此外，陈教授在香港政府支持的社会创新计划资助下，将研究成果转化为小区活动能力筛查工具，应用于香港长者的活动能力评估，协助识别需要进一步支持的人士。
陈教授的研究成果刊登于多份具领导地位的学术期刊，包括《Age and Ageing》及《The Journals of Gerontology: Series A》。其研究工作屡获殊荣，包括UNSW健康科学学院年度最佳早期职涯研究学者奖（2025年）、UNSW生物医学工程研究生学院年度最佳数码医学与数码生物学论文奖（2024年），以及澳洲神经科学研究院（NeuRA）杰出学术出版奖（2023年）。他亦透过担任学术期刊编辑、参与研究资助评审及国际科学委员会工作，为学术界作出贡献。
学历
- Doctor of Philosophy, The University of New South Wales
- Master of Science in Epidemiology and Biostatistics, The Chinese University of Hong Kong
- Bachelor of Science (Honours) in Physiotherapy, The Hong Kong Polytechnic University
专业资格
- Registered Physiotherapist, Hong Kong
- Registered Physiotherapist, Australia
研究兴趣
- Toapanta Gaibor CL, Bellés Andreu S, Lord SR, Chan LLY. Real-world walking patterns from wrist-worn wearables predict incident type 2 diabetes: a UK Biobank WatchWalk study. Journal of Diabetes Science and Technology. 2026. doi: 10.1177/19322968261464535.
- Fernandez N, Wong AY, Brodie MA, van Schooten KS, Chan LLY, Lord SR. Are real-world mobility patterns early indicators of COPD onset? Insights from wrist-worn sensors. International Journal of Chronic Obstructive Pulmonary Disease. 2026;21:605234. doi: 10.2147/COPD.S605234.
- Herrero Pinilla B, Hong S, Brodie MA, Lord SR, Chan LLY. More than step counts: slow walking speed, limited running, and fewer long walks predict cardiovascular mortality in the Walk Watch UK Biobank study. The Journals of Gerontology: Series A. 2025;80(10). doi: 10.1093/gerona/glaf184.
- Tajimi T, Chan LLY, Okubo Y, Lord SR. Real-world walking patterns are associated with regional brain atrophy and white matter lesions in middle-aged and older people: a Watch Walk-UK Biobank study. GeroScience. 2026;48(3):4247-4261. doi: 10.1007/s11357-025-01878-1.
- Osuka Y, Chan LLY, Brodie M, Okubo Y, Lord SR. Frailty assessed by a wrist-worn device can predict hospitalisation and mortality in middle-aged and older adults: a UK Biobank study. Age and Ageing. 2025;54(8). doi: 10.1093/ageing/afaf210.
- Chan LLY, Espinoza Cerda MT, Brodie MA, Lord SR, Taylor ME. Daily-life walking speed, running duration and bedtime from wrist-worn sensors predict incident dementia: a Watch Walk-UK Biobank study. International Psychogeriatrics. 2025:100031. doi: 10.1016/j.inpsyc.2024.100031.
- Sturnieks DL, Chan LLY, Cerda MTE, Arbona CH, Pinilla BH, Martinez PS, et al. Cognitive functioning and falls in older people: a systematic review and meta-analysis. Archives of Gerontology and Geriatrics. 2025;128:105638. doi: 10.1016/j.archger.2024.105638.
- Chan LLY, Lord SR, Brodie MA. Daily-life walking speed, quality and quantity derived from a wrist motion sensor: large-scale normative data for middle-aged and older adults. Sensors. 2024;24(16).
- Chan LLY, Yang S, Aswani M, Kark L, Henderson E, Lord SR, et al. Development, validation, and limits of freezing of gait detection using a single waist-worn device. IEEE Transactions on Biomedical Engineering. 2024;71(10):3024-3031. doi: 10.1109/TBME.2024.3407059.
- Chan LLY, Herrera Arbona C, Brodie MA, Lord SR. Prediction of injurious falls in older adults using digital gait biomarkers extracted from large-scale wrist sensor data. Age and Ageing. 2023;52(9).
