Sensors, Signals and Imaging Group
The Sensors, Signals and Imaging (SSI) Research Group consists of six members of academic staff, two postdoctoral research associates and over twenty PhD students actively engaged in research in sensors, signal processing and imaging with applications in medical image analysis, medical informatics, health and sports monitoring, human motion analysis and other application areas.
As a group we have extensive experience of working with ultrasound, PET and SPECT imaging, underwater acoustics, human body acoustics, polynomial matrix algorithms for broadband sensor array signal processing, body sensor networks, image and video segmentation, human motion analysis and human action and activity recognition. We have close links with Velindre, Llandough Hospital and the University Hospital of Wales, which support our activity in medical research.
Various techniques have been explored to detect and isolate circulating tumour cells (CTCs), in which microfluidic devices provide a unique opportunity for cell sorting and detection; they have been applied for flow cytometry, as well as size- and adhesion-based separation requiring less cumbersome instrumentation. Prospectively, aptamers integrating with other techniques have been demonstrated as good candidates for the analysis of the single CTC in parallel with capture, ultrasonic, and microfluidic technologies in the characterisation and sorting of single CTCs for real-time applications. This project aims to develop a hybrid lab-on-a-chip embracing the three techniques, to characterise single CTCs, with the following objectives:
- Integrating characterisation and isolation in a single lab-on-a-chip, to facilitate real-time and label-free investigation of single CTCs.
- Establishing the initial dielectric signature and model of CTCs, to approach the application of molecular identifications to cancer early detection and personalized cancer therapy.
- Applying the sensor to measure cancer cell samples, to register the dielectric characterisation and understand the cancer biology and metastasis.
Personalisation of cancer treatment
We have an ongoing programme of externally funded successful research in cancer imaging, personalisation of treatment and treatment outcome analysis. There are currently 4 PhD student projects in medical imaging and therapy, two ongoing clinical trials with radiotherapy and PET imaging (FIGARO and BIOPROP), both part-funded by Velindre NHS Trust and cancer charities and one clinical trial to be launched in Apr 2017. There is an increasing interest in this field as discussed at a recent Radiomics event jointly organised in Cardiff by Velindre and the School of Engineering.
Early dementia detection
This research develops technologies for timely and accurate early detection of dementia in a primary care context, which will enable evidence based decision making by medical professionals. We are investigating the development and integration of a number of tests for assessing the neurocognitive ability of subjects with a view to developing a tool for primary medical care for assessing the early stages of dementia and pre-dementia. The key social outcome of early diagnosis of dementia is to provide an opportunity for the diagnosed person to receive the appropriate information, advice, support and care at an early stage of the condition, which will allow the patient to continue to live well with dementia within the community in which they are based. The key medical outcome of early diagnosis of dementia is to provide an opportunity for applying future preventative and reversing treatments to dementia patients at an early stage of the disease.
So far, our research has been focused on automatic assessment of the Clock Drawing Tests, with several PhD students having contributed to this project over the last eight years. This is an ongoing collaboration with Professor Antony Bayer from Cardiff School of Medicine and Professor Rossi Setchi.
Human action and activity recognition
The popularisation of video surveillance and the vast increase of video content on the web has rendered video one of the fastest growing resources of data. In such videos, humans are arguably the most interesting subjects. The aim of this project is to develop algorithms capable of accurately recognising human activities in videos and possibly other complementary data sources. The activity on this project is supported by the EPSCRC grant “Signal processing solutions for the networked battlespace”.
Signal processing for health and sports monitoring
In this research, we develop advanced signal processing and data fusion algorithms for analysis of the data obtained with a variety of devices, such as mobile phones, video cameras, inertial measurement units (IMU) and electromyography (EMG) units. The data is analysed and appropriate feedback is provided to the subject and the medical professionals in order to monitor the condition of the patient and to develop personalised treatment appropriate for the condition. This research is supported by the Wellcome Trust grant “Automated assessment of timing and movement signatures in Huntingdon's disease”. There is an active collaboration with Professor Monica Busse from Cardiff School of Medicine and Professor Cathy Holt from the Biomedical Engineering Research Group, both of which support this research.
Below are examples of the currently active research grants held by the members of the group:
Busse M, Holt C, Hicks Y
Title: “Automated assessment of timing and movement signatures in Huntingdon's disease”
Sponsor: Wellcome Trust
Duration: 01/01/2016 - 31/12/2016
Title: “Advanced Personalised 3D Dosimetry for a clinical trial in peptide radionuclide therapy”
Sponsor: Cancer Research Wales
Duration: 01/10/2015 - 30/09/2018
McWhirter J, Hicks Y
Title: “Signal processing solutions for the networked battlespace”
Duration: 01/04/2013 - 31/03/2018
Title: A lab-on-a-chip for characterising and sorting cancer cells
Duration: 01/08/2016 – 31/07/2017
Lecturer - Teaching and Research
- +44 (0)29 2087 5919
Lecturer in Medical Imaging
- +44 (0)29 2087 0045
Distinguished Research Professor
- +44 (0)29 2087 0627
Reader - Teaching and Research
- +44 (0)29 2087 6521
Lecturer - Teaching and Research
- +44 (0)29 2087 5708