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Closing date: 1st December
A competition-funded PhD at the University of Southampton, developing wearable sensors and machine learning to spot early signs of mobility decline and fall risk in people over 65 with cognitive impairment and other long-term conditions. Supervised by Professor Liudi Jiang and Professor Michael Hornberger. Open to UK and EU students. See more funded PhDs.
Competition Funded PhD Project (European/UK Students Only)
About the Project
Supervisors: Professor Liudi Jiang and Professor Michael Hornberger
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.
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
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 doctoralcollege-admissions@soton.ac.uk.
Project leader
For an initial conversation, l.jiang@soton.ac.uk.
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.
To apply for this job please visit www.findaphd.com.
