老年共病人群行动能力下降早期检测的可穿戴传感博士研究员
Wearable sensing for early detection of mobility decline in older people with comorbidities
原帖优先：申请材料、截止时间与资格以原帖和学校官方说明为准。
博士招生与资助公告
- 申请年度
- 2027；原帖说明：How to apply Apply now You need to: • choose programme type (Research), 2027/28, Faculty of Engineering and Physical Sciences • select Full time or Part time • search for programme PhD Engineering & the Environment (7175) • add name of the supervisor in section 2 of the application Applications should include: • your CV (resumé) • 2 academic references • degree transcripts and certificates to date • English language qualification (if applicable)
- 最近申请截止
- 2026-12-01
- 全部申请截止
- （Europe/London）
- 资助原文
- Fees and funding We offer a range of funding opportunities for both UK and international students. Horizon Europe fee waivers automatically cover the difference between overseas and UK fees for qualifying students. Competition-based Presidential Bursaries from the University cover the difference between overseas and UK fees for top-ranked applicants. Competition-based studentships offered by our schools typically cover UK-level tuition fees and a stipend for living costs for top-ranked applicants. Funding will be awarded on a rolling basis, so apply early for the best opportunity to be considered. For more information, please visit our postgraduate research funding pages.
- 资助条件
- 原帖为竞争性或附条件资助说明，未确认本项目获资助及申请人能获奖；不作为保证全奖。
- 原帖材料说明
- • your CV (resumé)
- • 2 academic references
- • degree transcripts and certificates to date
- • English language qualification (if applicable)
确定性信息来自对应版本的完整原帖。原帖只提供日期，日末和学校当地时区为本站转换假设。筛选使用最后申请截止；资助与录取以学校审核结果为准。
AI 中文速览
- 研究内容
- 本项目利用可穿戴传感、数据分析和医疗AI技术，识别65岁及以上人群（包括伴有认知障碍等长期慢性病患者）功能衰退和跌倒风险的早期行动及生物力学指标，支持个性化干预与独立生活。项目将研究用于持续监测日常生活中运动运动学和动力学的新型可穿戴传感技术，并将行动测量与相关临床信息相结合，利用高级信号处理、数据分析和机器学习方法进行分析。
- 申请条件
- 申请人必须拥有英国2:1荣誉学士学位或其国际同等学历。本职位仅向英国和欧盟候选人开放。
- 待遇
- 学校提供竞争性奖学金，通常为顶尖申请者涵盖英国水平的学费以及生活费津贴。同时还设有总统奖学金（Presidential Bursaries）及地平线欧洲费减（Horizon Europe fee waivers）等资助机会。
- 申请方式
- 请通过南安普顿大学申请系统进行申请，选择项目类型（Research）、2027/28学年、工程与物理科学学院，选择全职或兼职，搜索项目 PhD Engineering & the Environment (7175)，并在申请的第二部分添加导师姓名。
- 材料清单
- 个人简历 (CV)
- 2封学术推荐信
- 迄今为止的学位成绩单和证书
- 英语语言资格证明（如适用）
由 gemini-2.5-flash-lite 生成，博士岗判定置信度 100%。
岗位信息
- 最终轮次截止
- 2026-12-01
- 学科
- 工程
- 合同类型
- 项目资助
- 本站收录
- 内容更新
- 导师
- Liudi Jiang
- 来源
- 南安普顿大学博士研究项目招生 · 最近核对 2026-10-10
- 详情核验
判定依据（原文摘录）
- is_phd
Type of degree Doctor of Philosophy
- english_ok
English language qualification (if applicable)
- bachelor_ok
You must have a UK 2:1 honours degree, or its international equivalent.
原文
View all current projects
Postgraduate research project
Wearable sensing for early detection of mobility decline in older people with comorbidities
Funding
Competition funded
Competition funded
View fees and funding
Type of degree
Doctor of Philosophy
Entry requirements
2:1 honours degree
2:1 honours degree
View full entry requirements
Faculty graduate school
Faculty of Engineering and Physical Sciences
Closing date
1 Dec 2026
On this page
About the project
Potential supervisors
Entry requirements
Fees and funding
How to apply
Contact us
About the project
Potential supervisors
Entry requirements
Fees and funding
How to apply
Contact us
About the project
Harness advances in wearable sensing, data analytics and medical AI to identify early mobility and biomechanical indicators of functional decline and fall risk in people aged 65 and over, including those with cognitive impairment and other coexisting long-term conditions, supporting timely, personalised interventions and independent living.
Multiple coexisting long-term conditions are increasingly prevalent among older people, substantially reducing quality of life. Conditions such as cognitive impairment, diabetes, and musculoskeletal or cardiovascular disease can interact to impair sensation, neurological control, muscle strength, gait and balance, increasing the risk of falls and loss of independence. Cognitive impairment may further affect attention, spatial awareness, motor planning and dual-task walking, but its impact on everyday mobility is not fully captured by conventional assessments. These assessments are typically episodic and clinic-based, relying on brief performance tests or self-reported falls, and may therefore miss subtle or progressive functional deterioration. Continuous monitoring of real-world mobility could reveal early changes and enable timely, personalised interventions.
This project will investigate novel wearable sensing technologies for continuously monitoring movement kinematics and kinetics during daily living in people aged 65 and over with comorbidities, including cognitive impairment. Mobility measurements will be integrated with relevant clinical information and analysed using advanced signal-processing, data-analytics and machine-learning methods.
The aim is to identify mobility and biomechanical indicators associated with cognitive and functional decline and to develop approaches for the early detection and prediction of fall risk.
This interdisciplinary project would suit students seeking to apply engineering skills in wearable sensing, signal processing, data analytics and machine learning to unmet healthcare challenges, with a view to improving quality of life and supporting independent living. You will benefit from multidisciplinary training and supervision spanning clinical neuroscience and wearable sensing.
The School of Engineering is committed to promoting equality, diversity inclusivity as demonstrated by our Athena SWAN award. We welcome all applicants regardless of their gender, ethnicity, disability, sexual orientation or age, and will give full consideration to applicants seeking flexible working patterns and those who have taken a career break. The University has a generous maternity policy, onsite childcare facilities, and offers a range of benefits to help ensure employees’ well-being and work-life balance. The University of Southampton is committed to sustainability and has been awarded the Platinum EcoAward.
Potential supervisors
Lead supervisor
Professor Liudi Jiang
Professor of Materials & Electromechanical Systems
Research interests
• Wearable sensors
• Healthcare technologies
• Musculoskeletal biomechanics
Supervisors
Professor Michael Hornberger
Professor of Applied Dementia Research
Research interests
• Personalised cognition in preclinical and clinical dementia
• Cortical and subcortical neuroimaging changes in dementia
• Sensors/Wearables to detect real-world changes in dementia
Entry requirements
You must have a UK 2:1 honours degree, or its international equivalent.
This project is available to UK and EU candidates only.
Fees and funding
We offer a range of funding opportunities for both UK and international students. Horizon Europe fee waivers automatically cover the difference between overseas and UK fees for qualifying students.
Competition-based Presidential Bursaries from the University cover the difference between overseas and UK fees for top-ranked applicants.
Competition-based studentships offered by our schools typically cover UK-level tuition fees and a stipend for living costs for top-ranked applicants.
Funding will be awarded on a rolling basis, so apply early for the best opportunity to be considered.
For more information, please visit our postgraduate research funding pages.
How to apply
Apply now
You need to:
• choose programme type (Research), 2027/28, Faculty of Engineering and Physical Sciences
• select Full time or Part time
• search for programme PhD Engineering & the Environment (7175)
• add name of the supervisor in section 2 of the application
Applications should include:
• your CV (resumé)
• 2 academic references
• degree transcripts and certificates to date
• English language qualification (if applicable)
Contact us
Faculty of Engineering and Physical Sciences
For questions about applying, please email our Doctoral College: doctoralcollege-admissions@soton.ac.uk.
Project leader
For an initial conversation, email Professor Liudi Jiang (l.jiang@soton.ac.uk).