Miss Claire Barnes

Lecturer (SPEC Analytics for Human Centred Data)

Biomedical Engineering

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Basic Welsh Speaker

Office - 412
Fourth Floor
Engineering North
Bay Campus

Available For Postgraduate Supervision

Research Links

https://orcid.org/0000-0003-1031-7127

About

My interests lie in the analytics of Human Centred data. I am interested in the use of various methods to transform both structured and unstructured data into actionable knowledge, enabling the end-user to gain insight from vast data sets. The use of BioImaging analysis together with machine learning techniques on large scale, high throughput cellular and molecular images, has been my most recent area of research.

Publications

Research Highlights

Rees, P., Rocha, J., Barnes, C., Rees, P., Clark, C., Stratton, G., & Summers, H. (2019). Activity Mapping of Children in Play Using Multivariate Analysis of Movement Events. Medicine & Science in Sports & Exercise, 1
https://doi.org/10.1249/MSS.0000000000002119, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa51987
Clark, C., Barnes, C., Stratton, G., McNarry, M., Mackintosh, K., & Summers, H. (2016). A Review of Emerging Analytical Techniques for Objective Physical Activity Measurement in Humans. Sports Medicine
https://doi.org/10.1007/s40279-016-0585-y, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa29308
Clark, C., Barnes, C., Holton, M., Summers, H., & Stratton, G. (2016). Profiling movement quality and gait characteristics according to body-mass index in children (9–11 y). Human Movement Science, 49, 291-300.
https://doi.org/10.1016/j.humov.2016.08.003, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa29588
Barnes, C., Clark, C., Rees, P., Stratton, G., & Summers, H. (2018). Objective profiling of varied human motion based on normative assessment of magnetometer time series data. Physiological Measurement, 39(4), 045007
https://doi.org/10.1088/1361-6579/aab9de, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa39198
Barnes, C., Clark, C., Holton, M., Stratton, G., & Summers, H. (2017). Quantitative Time Profiling of Children's Activity and Motion. Medicine & Science in Sports & Exercise, 49(1), 183-190.
https://doi.org/10.1249/mss.0000000000001085, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa49765

All Research

Journal Articles

Carreras, F., Moulin, C., Tales, A., Barnes, C., & Souchay, C. (2024). Metacognitive processes accompanying the first stages of autobiographical retrieval in the self-memory system. Memory, 32(6), 776-789.
https://doi.org/10.1080/09658211.2024.2370532, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa67156
Barnes, C., Sonwane, A., Sonnenschein, E., & Del Giudice, F. (2023). Machine learning enhanced droplet microfluidics. Physics of Fluids, 35(9)
https://doi.org/10.1063/5.0163806, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa66580
Wills, J., Robertson, J., Tourlomousis, P., Gillis, C., Barnes, C., Miniter, M., Hewitt, R., Bryant, C., Summers, H., Powell, J., & Rees, P. (2023). Label-free cell segmentation of diverse lymphoid tissues in 2D and 3D. Cell Reports Methods, 3(2), 100398
https://doi.org/10.1016/j.crmeth.2023.100398, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa62581
http://dx.doi.org/10.1016/j.crmeth.2023.100398
Del Giudice, F. & Barnes, C. (2022). Rapid Temperature-Dependent Rheological Measurements of Non-Newtonian Solutions Using a Machine-Learning Aided Microfluidic Rheometer. Analytical Chemistry, 94(8), 3617-3628.
https://doi.org/10.1021/acs.analchem.1c05208, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa59330
Wills, J., Verma, J., Rees, B., Harte, D., Haxhiraj, C., Barnes, C., Barnes, R., Rodrigues, M., Doan, M., Filby, A., Hewitt, R., Thornton, C., Cronin, J., Kenny, J., Buckley, R., Lynch, A., Carpenter, A., Summers, H., Johnson, G., & Rees, P. (2021). Inter-laboratory automation of the in vitro micronucleus assay using imaging flow cytometry and deep learning. Archives of Toxicology, 95(9), 3101-3115.
https://doi.org/10.1007/s00204-021-03113-0, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa57403
Doan, M., Barnes, C., McQuin, C., Caicedo, J., Goodman, A., Carpenter, A., & Rees, P. (2021). Deepometry, a framework for applying supervised and weakly supervised deep learning to imaging cytometry. Nature Protocols, 16(7), 3572-3595.
https://doi.org/10.1038/s41596-021-00549-7, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa57174
Wills, J., Robertson, J., Summers, H., Miniter, M., Barnes, C., Hewitt, R., Keita, Å., Söderholm, J., Rees, P., & Powell, J. (2020). Image‐Based Cell Profiling Enables Quantitative Tissue Microscopy in Gastroenterology. Cytometry Part A, 97(12), 1222-1237.
https://doi.org/10.1002/cyto.a.24042, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa56782
Clark, C., Barnes, C., Duncan, M., Summers, H., & Stratton, G. (2019). Physical activity, motor competence and movement and gait quality: A principal component analysis. Human Movement Science, 68, 102523
https://doi.org/10.1016/j.humov.2019.102523, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa52054
http://dx.doi.org/10.1016/j.humov.2019.102523
Rees, P., Wills, J., Brown, R., Barnes, C., & Summers, H. (2019). The origin of heterogeneous nanoparticle uptake by cells. Nature Communications, 10(1)
https://doi.org/10.1038/s41467-019-10112-4, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa50105
http://dx.doi.org/10.1038/s41467-019-10112-4
Rees, P., Rocha, J., Barnes, C., Rees, P., Clark, C., Stratton, G., & Summers, H. (2019). Activity Mapping of Children in Play Using Multivariate Analysis of Movement Events. Medicine & Science in Sports & Exercise, 1
https://doi.org/10.1249/MSS.0000000000002119, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa51987
Barnes, C., Clark, C., Rees, P., Stratton, G., & Summers, H. (2018). Objective profiling of varied human motion based on normative assessment of magnetometer time series data. Physiological Measurement, 39(4), 045007
https://doi.org/10.1088/1361-6579/aab9de, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa39198
Barnes, C., Clark, C., Holton, M., Stratton, G., & Summers, H. (2017). Quantitative Time Profiling of Children's Activity and Motion. Medicine & Science in Sports & Exercise, 49(1), 183-190.
https://doi.org/10.1249/mss.0000000000001085, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa49765
Clark, C., Barnes, C., Stratton, G., McNarry, M., Mackintosh, K., & Summers, H. (2016). A Review of Emerging Analytical Techniques for Objective Physical Activity Measurement in Humans. Sports Medicine
https://doi.org/10.1007/s40279-016-0585-y, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa29308
Clark, C., Barnes, C., Holton, M., Summers, H., & Stratton, G. (2016). A Kinematic Analysis of Fundamental Movement Skills. Sport Science Review, 25(3-4), 261-275.
https://doi.org/10.1515/ssr-2016-0014, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa49766
Clark, C., Barnes, C., Holton, M., Summers, H., & Stratton, G. (2016). Profiling movement quality and gait characteristics according to body-mass index in children (9–11 y). Human Movement Science, 49, 291-300.
https://doi.org/10.1016/j.humov.2016.08.003, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa29588

Supervision

Exploring metacognitive awareness of autobiographical memory in depression and healthy ageing (current)

PhD

Other supervisor: Prof Andrea Tales
Development of deepometry for the supervised and weakly supervised learning of imaging data (current)

PhD

Other supervisor: Prof Paul Rees
Coated subdermal wearable patches for real time continuous monitoring (current)

EngD

Other supervisor: Dr Francesco Del Giudice
Children's fitness and quality of movement (awarded 2023)

MSc

Other supervisor: Dr Richard Metcalfe

Other supervisor: Prof Gareth Stratton

Taught Modules

EG-219 Statistical Methods in Engineering

This module offers a balanced, streamlined one-semester introduction to Engineering Statistics that emphasizes the statistical tools most needed by practicing engineers. Using real engineering problems students see how statistics fits within the methods of engineering problem solving and learn how to apply statistical methodologies to their field of study. The module teaches students how to think like an engineer when analysing real data. Mini projects, tailored to each engineering discipline, are intended to simulate problems that students will encounter professionally during their future careers. Emphasis is placed on the use of statistical software for tackling engineering problems that require the use of statistics.
EG-238 Experimental Studies for Medical Engineers

The course introduces the students to experimental studies in a wide range of subjects. Each experiment is self contained and the student will present the findings in written form through a lab report which will have a set of experiment specific questions to answer. This written report also forms the basis for the assessment. All students work in groups and carry out five experiments which vary according to discipline, however the assignments are all individually submitted. The students keep a log-book of the experimental observations and results, which is used for reference for the technical report from each experiment written-up in the week after the experiment.
EGA219 Cell Biology and cell mechanics for engineers

This course provides an introduction to the biology and mechanical properties of cells from an engineering prospective. The basic structures within the cell and the core processes of cell function will be covered and related to the interaction of cells within large populations and the growth of tissue. i.e.membrane bilayer, cytoskeleton, energy production, signalling, growth, division and genetic duplication. The fundamental principles will be related to specific areas of interest to medical engineers - technology developments, the risk of infection from medical implants and the use of stem cells for tissue engineering.

Miss Claire Barnes

Email address

Welsh language proficiency

Research Links

About

Publications

Research Highlights

All Research

Journal Articles

Supervision

Exploring metacognitive awareness of autobiographical memory in depression and healthy ageing (current)

Development of deepometry for the supervised and weakly supervised learning of imaging data (current)

Coated subdermal wearable patches for real time continuous monitoring (current)

Children's fitness and quality of movement (awarded 2023)

Taught Modules

EG-219 Statistical Methods in Engineering

EG-238 Experimental Studies for Medical Engineers

EGA219 Cell Biology and cell mechanics for engineers