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Staff Profile

Chloe Hinchliffe

Research Associate

Background

I received my integrated master's degree in Medical Engineering MEng at the University of Surrey in 2018. My final year project was supervised by Dr Daniel Abasolo and Dr Mahinda Yogarajah and was titled “Electroencephalogram Analysis with Advanced Signal Processing Techniques for the Characterisation of Seizures”. 

I continued on with Dr Abasolo and Dr Yogarajah at the University of Surrey where completed my PhD in Biomedical Engineering in 2022. The title of my PhD thesis was "Application of Machine Learning to Electroencephalograms and Electrocardiograms for the Differential Diagnosis of Psychogenic Non-epileptic Seizures and Epilepsy". 

From October 2022, I have been a Research Assistant in the Brain and Movement (BAM) Research Group at the Translational and Clinical Research Institute of Newcastle University. 

Research

I am part of the Translational and Clinical Research Institute of Newcastle University. Here, I am working on the IDEA-FAST project, an international collaboration to identify digital endpoints to assess fatigue, sleep, and activities in daily living in neurodegenerative and immune disorders.


My research investigates the associations of macro and micro changes in gait with patient reported physical fatigue, mental fatigue, and daytime sleepiness. In this position, I am using advanced biomedical signal processing methods and machine/deep learning to develop towards an objective, low-cost method of identifying fatigue and sleepiness from digital wearables.

 

My responsibilities include:

· Development of advanced and novel features from triaxial accelerometer data

· Analysis of characteristics, patterns, and variability of gait from real-world recordings

· Evaluating associations with statistical measures and machine learning

· Production of high quality publications to prestigious scientific conferences and journals

 

My area of expertise is in biomedical signal processing with a focus on feature engineering and machine/deep learning. My interests include diagnosis/classification, development of novel features, and pipeline design. 

Publications

  • Article

  • Conference Proceedings (inc. Abstract)

    • Hinchliffe C, Yogarajah M, Tang L, Abasolo D. Electroencephalogram Connectivity for the Diagnosis of Psychogenic Non-epileptic Seizures. In: 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). 2022, Glasgow, Scotland. In Preparation.