Background and Motivation: As the COVID-19 disease began to spread across the world, the elderly population (aged 65+) experienced greater adverse effects from the pandemic, including more severe complications, higher mortality and disruptions to monitoring their ADL, including critical events (falls and wandering behavior) and access to care [13]. This disruption has been observed at homes and in care homes, where contact with family members and caregivers became more limited, due to isolation and lockdown. Statistics indicate that more than 70% of the elderly experience the types of critical events mentioned earlier when performing ADL, and their consequences can lead to a decreased quality of life and serious injuries, as well as heavy financial impact on the health and social care services. Innovative technological solutions, such as remote continuous monitoring using sensing devices, have the potential to improve quality of life and preserve safe, independent living with dignity, especially under isolation and lockdown, in homes or care homes.
State-of-the-art RADAR systems have only been used to detect the ADL of single individuals in direct line-of-sight (LOS) and in a well-controlled environment. To the best of our knowledge, this study will be the first to adopt a novel approach of using RADAR sensing and two novel deep learning algorithms for not only detecting, but also identifying and tracking the ADL of multiple individuals. Specifically, the approach aims to capture critical events (such as falls and wandering behavior) in LOS and non-LOS in a well-controlled controlled environment, and in a number of natural heterogeneous environments in a non-intrusive way.
To apply, click on project title :
https://www.coventry.ac.uk/research/research-opportunities/research-students/research-studentships/
Further information about the research of Dr. Syed Aziz Shah can be found at https://pureportal.coventry.ac.uk/en/persons/syed-shah . For queries regarding the studentship, please contact Dr Aziz (email: [Email Address Removed]).
Entry criteria for applicants to PhD
- A minimum of a 2:1 first degree in a relevant discipline/subject area with a minimum 60% mark in the project element or equivalent with a minimum 60% overall module average.
PLUS
- the potential to engage in innovative research and to complete the PhD within a 3.5 years
- a minimum of English language proficiency (IELTS overall minimum score of 7.0 with a minimum of 6.5 in each component)
For further details see:
https://www.coventry.ac.uk/research/research-students/making-an-application/
To find out more about the project please contact: Dr. Syed Aziz Shah, [Email Address Removed]
To apply online please visit: https://pgrplus.coventry.ac.uk/
All applications require full supporting documentation, a covering letter, plus a 2000-word supporting statement showing how the applicant’s expertise and interests are relevant to the project.
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