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PhD Studentship: Risk detection for the prevention of stairs falls in older people
A fully funded cross-Faculty studentship between the Research Institute for Sport and Exercise Sciences (RISES) in the Faculty of Science and the Built Environment and Sustainable Technologies Research Institute (BEST) in the Faculty of Engineering and Technology, Liverpool John Moores University (LJMU). This studentship provides support to cover tuition fees, an annual stipend of £13,726 and experimental costs.
Our research in the area of stair negotiation in older age has examined factors such as differences in biomechanical strategies and eye-gaze between age groups, and the effect of exercise training interventions. This PhD will extend this work by developing and investigating the use of a fall risk detection approach based on wearable sensors in instrumented garments and footwear for prediction of people that are likely to encounter a fall on stairs. The system of wearable sensors for stair fall risk prediction will be developed specially for detecting relevant biomechanical parameters that our previous research has shown to be risk factors for falling. The custom-build sensors will be developed in collaboration with the BEST Research Institute of the Faculty of Engineering and Technology at LJMU. This will allow the collection of large sets of relevant and specific biomechanical, behavioural and environmental data in the actual living environment of a large number of older individuals when they are actually using their own home staircases as part of their daily living activities using the unobtrusive sensing technology. Incidences of stair accidents and falls by the participants and the conditions under which they experienced falls will also be monitored. A data mining algorithm based on machine learning/neural networks will be developed to identify common patterns in biomechanical, environmental, behavioural and co-morbidity parameters in users that have encountered a fall in order to develop robust and accurate algorithms for predicting the risk of falling on stairs.
Entry requirements
We are seeking excellent candidates who preferably have a Master’s degree in human movement sciences, or other sports engineering, bioengineering or electronic engineering related disciplines. Expertise in biomechanics and motion analysis is essential, and any experience with sensors, neural networks and electronic engineering will be advantageous. It is essential that candidates can demonstrate the personal skills to recruit older participants within the community and maintain engagement throughout the course of the project.
How to apply
Applicants should send a CV and a personal statement (max one page A4) outlining their experience and suitability for this project to Prof V. Baltzopoulos by email to v.baltzopoulos@ljmu.ac.uk. Your personal statement should make clear how you meet the essential/desirable criteria for the role, highlighting key evidence to support your points.
The closing date for applications is midnight on Monday 27th June 2016.
Shortlisted candidates will be invited to an interview. The successful candidate will be expected to be in post before July 31st 2016.
Informal enquiries for this studentship are welcome and should be addressed to Prof V. Baltzopoulos, Head of RISES: e: v.baltzopoulos@ljmu.ac.uk t: +44 (0) 151 904 6272.
Relevant Websites:
https://www.ljmu.ac.uk/research/centres-and-institutes/faculty-of-engineering-and-technology-research-institute/built-environment-and-sustainable-technologies-research-institute
A fully funded cross-Faculty studentship between the Research Institute for Sport and Exercise Sciences (RISES) in the Faculty of Science and the Built Environment and Sustainable Technologies Research Institute (BEST) in the Faculty of Engineering and Technology, Liverpool John Moores University (LJMU). This studentship provides support to cover tuition fees, an annual stipend of £13,726 and experimental costs.
Our research in the area of stair negotiation in older age has examined factors such as differences in biomechanical strategies and eye-gaze between age groups, and the effect of exercise training interventions. This PhD will extend this work by developing and investigating the use of a fall risk detection approach based on wearable sensors in instrumented garments and footwear for prediction of people that are likely to encounter a fall on stairs. The system of wearable sensors for stair fall risk prediction will be developed specially for detecting relevant biomechanical parameters that our previous research has shown to be risk factors for falling. The custom-build sensors will be developed in collaboration with the BEST Research Institute of the Faculty of Engineering and Technology at LJMU. This will allow the collection of large sets of relevant and specific biomechanical, behavioural and environmental data in the actual living environment of a large number of older individuals when they are actually using their own home staircases as part of their daily living activities using the unobtrusive sensing technology. Incidences of stair accidents and falls by the participants and the conditions under which they experienced falls will also be monitored. A data mining algorithm based on machine learning/neural networks will be developed to identify common patterns in biomechanical, environmental, behavioural and co-morbidity parameters in users that have encountered a fall in order to develop robust and accurate algorithms for predicting the risk of falling on stairs.
Entry requirements
We are seeking excellent candidates who preferably have a Master’s degree in human movement sciences, or other sports engineering, bioengineering or electronic engineering related disciplines. Expertise in biomechanics and motion analysis is essential, and any experience with sensors, neural networks and electronic engineering will be advantageous. It is essential that candidates can demonstrate the personal skills to recruit older participants within the community and maintain engagement throughout the course of the project.
How to apply
Applicants should send a CV and a personal statement (max one page A4) outlining their experience and suitability for this project to Prof V. Baltzopoulos by email to v.baltzopoulos@ljmu.ac.uk. Your personal statement should make clear how you meet the essential/desirable criteria for the role, highlighting key evidence to support your points.
The closing date for applications is midnight on Monday 27th June 2016.
Shortlisted candidates will be invited to an interview. The successful candidate will be expected to be in post before July 31st 2016.
Informal enquiries for this studentship are welcome and should be addressed to Prof V. Baltzopoulos, Head of RISES: e: v.baltzopoulos@ljmu.ac.uk t: +44 (0) 151 904 6272.
Relevant Websites:
https://www.ljmu.ac.uk/research/centres-and-institutes/faculty-of-engineering-and-technology-research-institute/built-environment-and-sustainable-technologies-research-institute