Dr Clare Martin
MA, MSc, DPhil (Oxon)
Principal Lecturer for Student Experience
School of Engineering, Computing and Mathematics
Role
As a Principal Lecturer Student Experience for the Faculty of Technology, Design and Environment, I am involved in work across the University that is designed to enhance the time that our students spend with us. For example I have managed projects on sustainable mentoring and getting students’ work published as part of the University Programme for Enhancing the Student Experience.
Teaching and supervision
Courses
My teaching activities include programming, and research and study skills.
Research
My research interests lie in healthcare technology and formal methods for computer science. I have been involved in the research, development and evaluation of various tools to support the self-management of chronic health conditions. The roles of human factors and artificial intelligence in the development diabetes technology are particular areas of focus. I am also interested in the use of mathematics to reason about the semantics and general algebraic properties of programming and specification languages.
Centres and institutes
Groups
- Applied Software Engineering and Data Analytics Group (ASEDA)
- Machine Learning and Robotics Group (MLAIR)
Projects
- Avatar Based LEarning for Diabetes Optimal Control (ABLE DOC)
- CAVE-based Patient Education Tool (CAVEPET)
- Cloud-based Tool for Diabetes Management and Research in Colombia (COORDINATE)
- Criticality Analysis of Energetic Control in Diabetic Gait (CARDIGAN)
- Patient Empowerment through Predictive PERsonalised decision support (PEPPER)
Publications
Journal articles
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Eltanani Shadi, Olde Scheper Tjeerd, Munoz-Balbontin Mireya, Aldea Arantza, Cossington Jo, Lawrie Sophie, Villalpando-Carrion Salvador, Adame Maria Jose, Felgueres Daniela, Martin Clare, Dawes Helen, 'A Novel Criticality Analysis Method for Assessing Obesity Treatment Efficacy'
Applied Sciences 13 (24) (2023)
ISSN: 2076-3417 eISSN: 2076-3417AbstractPublished here Open Access on RADARHuman gait is a significant indicator of overall health and well-being due to its dependence on metabolic requirements. Abnormalities in gait can indicate the presence of metabolic dysfunction, such as diabetes or obesity. However, detecting these can be challenging using classical methods, which often involve subjective clinical assessments or invasive procedures. In this work, a novel methodology known as Criticality Analysis (CA) was applied to the monitoring of the gait of teenagers with varying amounts of metabolic stress who are taking part in an clinical intervention to increase their activity and reduce overall weight. The CA approach analysed gait using inertial measurement units (IMU) by mapping the dynamic gait pattern into a nonlinear representation space. The resulting dynamic paths were then classified using a Support Vector Machine (SVM) algorithm, which is well-suited for this task due to its ability to handle nonlinear and dynamic data. The combination of the CA approach and the SVM algorithm demonstrated high accuracy and non-invasive detection of metabolic stress. It resulted in an average accuracy within the range of 78.2% to 90%. Additionally, at the group level, it was observed to improve fitness and health during the period of the intervention. Therefore, this methodology showed a great potential to be a valuable tool for healthcare professionals in detecting and monitoring metabolic stress, as well as other associated disorders.
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Bishop E, Allington D, Ringrose T, Martin C, Aldea A, García-Jaramillo M, León-Vargas F, Leal Y, Henao D, Gómez AM, 'Design and usability of an avatar-based learning program to support diabetes education – Quality improvement study in Colombia'
Journal of Diabetes Science and Technology 17 (5) (2022) pp.1142-1153
ISSN: 1932-2968 eISSN: 1932-2968AbstractPublished here Open Access on RADARBackground: This quality improvement study, entitled Avatar-Based LEarning for Diabetes Optimal Control (ABLEDOC), explored the feasibility of delivering an educational programme to people with diabetes in Colombia. The aim was to discover how this approach could be used to improve awareness and understanding of the condition, the effects of treatment, and strategies for effective management of blood-glucose control.
Methods: Individuals with diabetes were recruited by Colombian endocrinologists to a human-centred study to co-design the educational programme, using the Double Diamond model. Participants contributed to two phases. The first phase focused on gathering unmet educational needs, and choice of curriculum. Three prototypes were developed as a result. During Phase Two, a different group of participants engaged with the programme for several weeks, before reporting back.
Results: Thirty-six participants completed a web survey during Phase One, and five were also interviewed by telephone. The majority (33 of 36, 91%) were receptive to the prospect of educational interventions, and ranked the chosen topic of hypoglycemia highly. In Phase Two, the three prototypes were tested by seventeen participants, ten of which also gave feedback in focus groups. The response was overwhelmingly positive, with 16 of 17 (94%) stating they would use a program like this again. The 3D version was the most highly rated.
Conclusion: Immersive, avatar-based programmes, delivered via smartphone, have the potential to deliver educational information that is trusted, engaging and useful. Future work includes expansion of the curriculum, evaluation with a larger group, and exploration of the prospective role of artificial intelligence in personalising this form of educational intervention.
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Gomez AM, Henao DC, Vargas FL, Muñoz OM, Lucero OD, García Jaramillo M, Aldea A, Martin C, Rodríguez Hortúa LM, Rubio Reyes CP, Páez Hortúa MA, Rondon M, 'Efficacy of the mHealth application in patients with type 2 diabetes transitioning from inpatient to outpatient care: A randomized controlled clinical trial'
Diabetes Research and Clinical Practice 189 (2022)
ISSN: 0168-8227 eISSN: 1872-8227AbstractPublished here Open Access on RADARIntroduction
No studies have assessed the efficacy of telemedicine using a platform for recording and adjusting insulin doses in patients with diabetes mellitus type 2 (DM2) transitioning from inpatient to outpatient care. This study aimed to assess, in a population of patients with DM2, discharged from a tertiary referral hospital, whether treatment based on the use of an mHealth application was associated with better glycemic control at the 3-month follow-up, than standard care.
Methods
This open, randomized, controlled clinical trial included adult DM2 patients who were transitioning from inpatient to outpatient care. The efficacy and safety of patient management with and without mHealth was compared at the 3-month follow-up. The primary outcome was the change in the Glycosylated hemoglobin (HbA1c) levels. The secondary outcomes were the rates of hypoglycemic and hyperglycemic events and treatment satisfaction measured using the Insulin Treatment Satisfaction Questionnaire (ITSQ).
Results
In total, 86 patients (41 using mHealth) were included in the clinical trial. HbA1c levels showed a significant decrease in both groups. The mean HbA1c level was significantly lower in the mHealth group. Patients using mHealth showed decreased incidence rate ratios of hypoglycemia 3.0 mmol/L [
Conclusion
Using mHealth in patients with DM2 transitioning from inpatient to outpatient care improves metabolic control and may reduce the hypoglycemia rates.
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León-Vargas F, Martin C, Garcia-Jaramillo M, Aldea A, Leal Y, Herrero P, Reyes A, Henao D, Gomez AM, 'Is a Cloud-based Platform Useful for Diabetes Management in Colombia? The Tidepool Experience '
Computer Methods and Programs in Biomedicine 208 (2021)
ISSN: 0169-2607 eISSN: 0169-2607AbstractPublished here Open Access on RADARBackground
There are several medical devices used in Colombia for diabetes management, most of which have an associated telemedicine platform to access the data. In this work, we present the results of a pilot study evaluating the use of the Tidepool telemedicine platform for providing remote diabetes health services in Colombia across multiple devices.
Method
Individuals with Type 1 and Type 2 diabetes using multiple diabetes devices were recruited to evaluate the user experience with Tidepool over three months. Two endocrinologists used the Tidepool software to maintain a weekly communication with participants reviewing the devices data remotely. Demographic, clinical, psychological and usability data were collected at several stages of the study.
Results
Six participants, from ten at the baseline (five MDI and five CSII), completed this pilot study. Three different diabetes devices were employed by the participants: a glucose meter (Abbot), an intermittently-scanned glucose monitor (Abbot), and an insulin pump (Medtronic). A score of 81.3 in the system usability scale revealed that overall, most participants found the system easy to use, especially the web interface. The system also compared highly favourably against the proprietary platforms. The ability to upload and share data and communicate remotely with the clinicians was raised consistently by participants. Clinicians cited the lockdown imposed by the Covid-19 pandemic as a valuable test for this platform. Inability to upload data from mobile devices was identified as one of the main limitations.
Conclusion
Tidepool has the potential to be used as a tool to facilitate remote diabetes care in Colombia. Users, both participants and clinicians, agreed to recommend the use of platforms like Tidepool to achieve better disease management and communication with the health care team. Some improvements were identified to enhance the user experience.
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Avari P, Leal Y, Herrero P, Wos M, Jugnee N, Arnoriaga-Rodríguez M, Thomas M, Liu C, Massana Q, Lopez B, Nita L, Martin C, Fernández-Real JM, Oliver N, Fernández-Balsells M, Reddy M, 'Safety and feasibility of the PEPPER adaptive bolus advisor and safety system; a randomized control study.'
Diabetes Technology & Therapeutics 23 (3) (2021) pp.175-186
ISSN: 1520-9156 eISSN: 1557-8593AbstractPublished here Open Access on RADARBackground: The Patient Empowerment through Predictive Personalized Decision Support (PEPPER) system provides personalized bolus advice for people with type 1 diabetes. The system incorporates an adaptive insulin recommender system (based on case-based reasoning, an artificial intelligence methodology), coupled with a safety system, which includes predictive glucose alerts and alarms, predictive low-glucose suspend, personalized carbohydrate recommendations, and dynamic bolus insulin constraint. We evaluated the safety and efficacy of the PEPPER system compared to a standard bolus calculator.
Methods: This was an open-labeled multicenter randomized controlled crossover study. Following 4-week run-in, participants were randomized to PEPPER/Control or Control/PEPPER in a 1:1 ratio for 12 weeks. Participants then crossed over after a washout period. The primary end-point was percentage time in range (TIR, 3.9–10.0 mmol/L [70–180 mg/dL]). Secondary outcomes included glycemic variability, quality of life, and outcomes on the safety system and insulin recommender.
Results: Fifty-four participants on multiple daily injections (MDI) or insulin pump completed the run-in period, making up the intention-to-treat analysis. Median (interquartile range) age was 41.5 (32.3–49.8) years, diabetes duration 21.0 (11.5–26.0) years, and HbA1c 61.0 (58.0–66.1) mmol/mol. No significant difference was observed for percentage TIR between the PEPPER and Control groups (62.5 [52.1–67.8] % vs. 58.4 [49.6–64.3] %, respectively, P = 0.27). For quality of life, participants reported higher perceived hypoglycemia with the PEPPER system despite no objective difference in time spent in hypoglycemia.
Conclusions: The PEPPER system was safe, but did not change glycemic outcomes, compared to control. There is wide scope for integrating PEPPER into routine diabetes management for pump and MDI users. Further studies are required to confirm overall effectiveness.
Clinical trial registration:ClinicalTrials.gov NCT03849755
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Henshall C, Davey Z, Jacelon C, Martin C, 'A usability study to test the effectiveness, efficiency and simplicity of a newly developed Internet-based Exercise focused Health App for Lung cancer survivors (iEXHALE): protocol paper'
Health Informatics Journal 26 (2) (2019) pp.1431-1442
ISSN: 1460-4582 eISSN: 1741-2811AbstractPublished here Open Access on RADARThe Internet-based Exercise-focused Health App for Lung cancer survivors (iEXHALE) is a mobile web app being developed to provide lung cancer survivors with an algorithm-based, tailor-made, self-management programme to inform their exercise choices and improve symptom severity. The aim of this protocol paper is to detail the plan for conducting the usability study to test the effectiveness, efficiency and simplicity of an exercise-focused self-management mobile web app for lung cancer survivors. The mixed methods study will consist of three consecutive phases, each interspersed with elements of data analysis and app prototype redevelopment. The study will take place in Oxford, United Kingdom. Ethical approvals have been obtained. The study will contribute to lung cancer survivorship research and is important in the app developmental process. This study contributes to the international forum for the exchange of practice, innovation and research, increases transparency in mobile health developmental processes and contributes to the methodological evidence base.
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Liu C, Avari P, Leal Y, Wos M, Sivasithamparam K, Georgiou P, Reddy M, Fernández-Real JM, Martin C, Fernández-Balsells M, Oliver N, Herrero P, 'A Modular Safety System for an Insulin Dose Recommender: a Feasibility Study'
Journal of Diabetes Science and Technology 14 (1) (2019) pp.87-96
ISSN: 1932-2968 eISSN: 1932-2968AbstractPublished here Open Access on RADARBackground: Delivering insulin in type 1 diabetes is a challenging, and potentially risky, activity; hence the importance of including safety measures as part of any insulin dosing or recommender system. This work presents and clinically evaluates a modular safety system that is part of an intelligent insulin dose recommender platform developed within the EU-funded PEPPER project.
Methods: The proposed safety system is composed of four modules which use a novel glucose forecasting algorithm. These modules are: predictive glucose alerts and alarms; a predictive low-glucose basal insulin suspension module; an advanced rescue carbohydrate recommender for resolving hypoglycaemia; and a personalised safety constraint applied to insulin recommendations. The technical feasibility of the proposed safety system was evaluated in a pilot study including eight adult subjects with type 1 diabetes on multiple daily injections over a duration of six weeks. Glycaemic control and safety system functioning were compared between the two-weeks run-in period and the end-point at eight weeks. A standard insulin bolus calculator was employed to recommend insulin doses.
Results: Overall, glycaemic control improved over the evaluated period. In particular, percentage time in the hypoglycaemia range (
Conclusion: A safety system for an insulin dose recommender has been proven to be a viable solution to reduce the number of adverse events associated to glucose control in type 1 diabetes.
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Franklin R, Waite MA, Martin CE, 'The Use of Mobile Technology to facilitate self-management in adults with Type 1 Diabetes: A qualitative explorative approach'
Nursing Open 6 (3) (2019) pp.1013-1021
ISSN: 2054-1058AbstractPublished here Open Access on RADARAims: (a) To explore how mobile technology can support self‐management in adults with type 1 diabetes (T1DM). (b) To inform a usability study in the design of a mobile application to facilitate self‐management of T1DM. Design: Qualitative exploratory design. Methods: Semi‐structured interviews were undertaken with adults with T1DM (N = 8). The data collected were analysed using a thematic analysis approach. Results: Mobile technology has the potential to support adults in their self‐management of T1DM through facilitating their decision‐making, saving time and enabling them to easily share their data with their healthcare professional. Participants identified four main visualization characteristics for technology to aid in decision‐making; relationships between inputs, trends, graphs and colours, and identified essential features such as ease of use, convenience and connectivity.
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Martin C, Aldea A, Duce D, Harrison R, Alshaigy B, 'The Role of Usability Engineering in the Development of an Intelligent Decision Support System'
Lecture Notes in Computer Science 11326 (2019) pp.142-161
ISSN: 0302-9743 eISSN: 0302-9743 ISBN: 9783030127381AbstractPublished here Open Access on RADARThis paper presents an overview of the usability engineering process for the development of a personalised clinical decision support system for the management of type 1 diabetes. The tool uses artificial intelligence (AI) techniques to provide insulin bolus dose advice and carbohydrate recommendations that adapt to the individual. We describe the role of human factors and user-centred design in the creation of medical systems that must adhere to international standards. We focus specifically on the formative evaluation stage of this process. The preliminary analysis of data shows promising results.
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Hinze R, Martin C, 'Parberry’s Pairwise Sorting Network Revealed'
Journal of Functional Programming 28 (2018)
ISSN: 0956-7968 eISSN: 1469-7653AbstractPublished here Open Access on RADARBatcher’s “merge exchange” sorting network, discussed in a previous pearl (Hinze & Martin, 2016), remains one of the best practical algorithms for oblivious sorting, even almost half a century after its inception. So it is surprising that an algorithm with exactly the same level of performance, devised two decades later by Parberry (1992), has been relatively overlooked. Perhaps a reason for its lack of celebrity is that Parberry’s design is not immediately recognizable, whereas the Batcher method has a familiar ring, as a hardwired implementation of merge sort. Here we hope to rectify this imbalance by unravelling Parberry’s algorithm and uncoupling its close relationship to Batcher’s. Interestingly, Parberry derives his network using the zero-one principle (Knuth, 1998). We abandon this traditional method, in favour of a feature of comparison networks that we consider to be more fundamental: monotonicity. We shall see that this property, used before to demystify Batcher’s merger (Hinze & Martin, 2016), also helps to shed some light on Parberry’s design. To keep the pearl reasonably self-contained we start with a quick recap of the notation and Batcher’s construction.
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Hinze R, Martin C, 'Batcher’s Odd-Even Merging Network Revealed'
Journal of Functional Programming 28 (2018)
ISSN: 0956-7968 eISSN: 1469-7653Published here Open Access on RADAR -
Brown D, Aldea A, Harrison R, Martin C, Bayley I, 'Temporal case-based reasoning for type 1 diabetes mellitus bolus insulin decision support'
Artificial Intelligence in Medicine 85 (April 2018) (2018) pp.28-42
ISSN: 0933-3657 eISSN: 1873-2860AbstractIndividuals with type 1 diabetes have to monitor their blood glucose levels, determine the quantity of insulin required to achieve optimal glycaemic control and administer it themselves subcutaneously, multiple times per day. To help with this process bolus calculators have been developed that suggest the appropriate dose. However these calculators do not automatically adapt to the specific circumstances of an individual and require fine-tuning of parameters, a process that often requires the input of an expert.Published here Open Access on RADAR
To overcome the limitations of the traditional methods this paper proposes the use of an artificial intelligence technique, case-based reasoning, to personalise the bolus calculation. A novel aspect of our approach is the use of temporal sequences to take into account preceding events when recommending the bolus insulin doses rather than looking at events in isolation.
The in silico results described in this paper show that given the initial conditions of the patient, the temporal retrieval algorithm identifies the most suitable case for reuse. Additionally through insulin-on-board adaptation and postprandial revision, the approach is able to learn and improve bolus predictions, reducing the blood glucose risk index by up to 27% after three revisions of a bolus solution. -
Beatriz Lopez, Clare Martin, Pau Herrereo Vinas, 'Special section on artificial intelligence in diabetes [editorial]'
Artificial Intelligence in Medicine 85 (2018) pp.26-27
ISSN: 0933-3657Published here Open Access on RADAR -
Waite MA, Martin CE, Franklin R, Duce D, Harrison R, 'Human factors and data logging processes with the use of advanced technology for adults with type 1 diabetes (T1DM): A systematic integrative review'
Journal of Medical Internet Research 5 (1) (2017)
ISSN: 1439-4456 eISSN: 1438-8871AbstractPublished here Open Access on RADARBackground: People with T1DM are confronted with self-management tasks and for which they need to develop strategies to balance the risks of long-term complications with those of hypoglycemic events. The potential of advanced and evolving technology to address these issues involves consideration of psychological and behavioral constructs alongside evaluation of the usability of devices. Access and uptake of advanced technology is further influenced by economic factors and health care provider capacity to support such interventions. Previous reviews have either focused upon clinical outcomes or descriptively scoped the literature. In addition, some have synthesized studies on adults with those on children and young people where human factors are different. Objective: The objective of this review was to describe the relationship between
human factors and adherence with technology for data logging processes in adults with T1DM and to explore the factors which influence this association. Methods: A systematic search of the literature was undertaken in accordance with the PRISMA guidelines. Quality appraisal of each study was undertaken. Data were abstracted and categorized into the themes that underpinned the human factor constructs that were examined. Results: Eighteen studies were included in the review. Six constructs emerged from the data analysis: The relationship between adherence to data logging and measurable outcomes; Satisfaction with the transition to advanced technology for self-management; Use of advanced technology and time spent on diabetes related activities; Strategies to mediate the complexities of diabetes and the use of advanced technology; Cognition in the wild and, Meanings, views and perspectives from the users of technology. Conclusions: evidence of increased treatment satisfaction was found on transition from traditional to advanced technology use (insulin pump and continuous glucose monitoring (CGM)); the most significant contributing factor was when blood glucose (BG) levels were consistently
evidence that logging of data was positively correlated with increasing age when using an app that provided meaningful feedback (regression coefficient = 55.8 recordings/ year; P = 0.009). Furthermore, there were benefits of CGM for older people in mediating complexities and their fears of hypoglycemia with reported significant differences in well-being (P= .009). Qualitative studies within the review aimed to explore the use and uptake of technology within the context of everyday lives. There were ‘frustrations’ with CGM, continuous subcutaneous insulin infusion (CSII), calibration of devices and alarms. This created implications for “body image” and the way in which “significant others” impacted on the behavior and attitude of the individual towards technology use. There were wide variations in the normal use of and interaction with technology across a continuum of sociocultural contexts, which has implications for the way in which future technologies should be designed. Many of the quantitative studies in the review were limited by small sample sizes. This may make it difficult to generalize findings to other contexts. This is further limited by a sample that was predominantly Caucasian, well-controlled and engaged with their self-care. However, the use of critical appraisal frameworks has highlighted areas where research into human factors and data logging processes of individuals could be improved. This includes engaging people in the design of the technology especially hard-to- reach or marginalized groups.
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Hinze R, Martin C, 'A logical reconstruction of Batcher’s mergers, or, Bitonicity is a red herring'
Journal of Universal Computer Science 23 (1) (2017) pp.21-41
ISSN: 0948-695X eISSN: 0948-6968AbstractAlmost half a century after Batcher wrote his seminal paper on sorting networks, we revisit the key algorithmic design decisions for oblivious merging to rediscover his schemes in a disciplined way. The design space of sorting networks is explored, resulting in a systematic reconstruction of schemes that appear in the literature in various guises.Published here Open Access on RADAR -
Aldea A, Crook N, Duce D, Marshall P, Martin C, Sutton D, 'Reflections on the evolution of the teaching of programming to undergraduates at Oxford Brookes University'
Brookes eJournal of Learning and Teaching 7 (1) (2015)
ISSN: 1744-7747AbstractPublished hereUndergraduate computing courses inevitably include a high degree of regeneration in order to keep abreast of this rapidly changing field. Introductory programming modules in particular need to adapt to changing trends and languages. Until recently, the focus of debate within the Oxford Brookes University curriculum has therefore been on the course content, but since 2012 there has been a major change in the method of delivery through the introduction of a new apprenticeship model. This paper seeks to reflect on this, and other recent changes which have led to improved student engagement and results. The data is limited however, and so the results presented here are not conclusive.
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Austen A, Martin C, 'Reflections on using the Raspberry Pi in schools to make learning programming fun'
Brookes eJournal of Learning and Teaching 7 (1) (2015)
ISSN: 1744-7747 eISSN: 1744-7747AbstractPrimary and secondary schools across the UK are currently faced with the exciting, yet daunting prospect of inspiring a new generation of programmers, following the introduction of the national curriculum for computing in September 2014. The Raspberry Pi is a very low-cost credit card sized computer that was launched in 2012 to promote the study of computer science to school-age pupils, and is therefore ideally suited to supporting this challenge. This article describes some experiences of using the Raspberry Pi to deliver extra-curricular activities in secondary schools.Published hereThe Raspberry Pi (Raspberry Pi Foundation 2014) is a small, cheap, yet powerful computer first released in 2012 by the Raspberry Pi Foundation, a UK registered charity that was founded in 2009 to support the study of basic computer science in schools. The Pi has rapidly gained popularity, partly because of its capability to control external electronic circuits with computer code.
The project described in this article began as an after school club at Wheatley Park secondary school. It was led by volunteers who were inspired by the potential of the Pi and concerned about the deficiencies in the 2013 ICT curriculum. The aims of the club were to make learning computer programming fun for the pupils and to transfer knowledge to the school’s IT staff.
The students undertook activities during the project that involved programming in Python (Python Software 2014), which most of them had not used before. The exercises involved controlling simple sound and lighting systems.
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Martin C, Curtis S, 'Educational pearl: functional fractal image compression'
Journal of Functional Programming 23 (6) (2013) pp.629-657
ISSN: 0956-7968 eISSN: 1469-7653AbstractPublished hereThis paper describes some experiences of using fractal image compression as the subject of an assignment for a functional programming course using Haskell. The students were fascinated by the reproduction of images from their encodings and engaged well with the exercise which involved only elementary functional programming techniques.
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Martin C, Curtis S, 'Fractal Image Compression'
Journal of Functional Programming (2013)
ISSN: 0956-7968 eISSN: 1469-7653AbstractPublished hereThis paper describes some experiences of using fractal image compression as the subject of an assignment for a functional programming course using Haskell. The students were fascinated by the reproduction of images from their encodings and engaged well with the exercise which involved only elementary functional programming techniques.
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Martin C, Curtis S, 'The algebra of multirelations'
Mathematical Structures in Computer Science 23 (3) (2013) pp.635-674
ISSN: 0960-1295AbstractMultirelational semantics are well suited to reasoning about programs involving two kinds of non-determinism. This paper lays the categorical foundations for an algebraic calculus of multirelations.Published here -
Martin C, Bayley I, 'Disciplined, Efficient, Generalised Folds for Nested Datatypes'
Formal Aspects of Computing 16 (2005) pp.19-35
ISSN: 0934-5043 eISSN: 1433-299XAbstractNested (or non-uniform, or non-regular) datatypes have recursive definitions in which the type parameter changes. Their folds are restricted in power due to type constraints. Bird and Paterson introduced generalised folds for extra power, but at the cost of a loss of efficiency: folds may take more than linear time to evaluate. Hinze introduced efficient generalised folds to counter this inefficiency, but did so in a pragmatic way, at the cost of a loss of reasoning power: without categorical or equivalent underpinnings, there are no universal properties for manipulating folds. We combine the efficiency of Hinze's construction with the powerful reasoning tools of Bird and Paterson's.Published here
Book chapters
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Martin C, Flood D, Harrison R, 'A protocol for evaluating mobile applications' in Information systems research and exploring social artifacts: approaches and methodologies, IGI Global (2013)
eISBN: 1.466624914E9AbstractThe number of applications available for mobile phones is growing at a rate which makes it difficult for new application developers to establish the current state of the art before embarking on new product development. This chapter outlines a protocol for capturing a snapshot of the present state of applications in existence for a given field in terms of both usability and functionality. The proposed methodology is versatile in the sense that it can be implemented for any domain across all mobile platforms, which is illustrated here by its application to two dissimilar domains on three platforms. The chapter concludes with a critical evaluation of the process that was undertaken.Published here -
Martin C, 'Monadic Maps and Folds for Multirelations in an Allegory' in Unifying theories of programming: Lecture Notes in Computer Science, vol. 5713, Springer Verlag (2010)
ISBN: 97836421145209AbstractThis paper contributes to the unification of semantic models and program development techniques by making a link from multirelations and predicate transformer semantics to algebraic semantics and the derivation of programs by calculation, as used in functional programming and relational program development. Two common ways to characterise iteration, namely the functional programming operators map and fold, are extended to multirelations, using concepts from category theory, power allegories and monads.Published here
Conference papers
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Duce, D. and Martin, C. and Russell, a. and Brown D. and Aldea, A. and Alshaigy, B. and Harrison, R. and Waite, M. and Leal, Y. and Wos, M.and Fernandez-Balsells, M. and Real, J. and Nita, L. and López, B. and Massana, J. and Avari, P. and Herrero, P. and Jugnee, N. and Oliver, N. and Reddy, M., 'Visualizing Usage Data from a Diabetes Management System'
(2020)
ISBN: 9783038681229AbstractPublished here Open Access on RADARThis article explores the role for visualization in interpreting data collected by a customised analytics framework within a healthcare technology project. It draws on the work of the EU-funded PEPPER project, which has created a personalised decision-support system for people with type 1 diabetes. Our approach was an exercise in exploratory visualization, as described by Bergeron's three category taxonomy. The charts revealed different patterns of interaction, including variability in insulin dosing schedule, and potential causes of rejected advice. These insights into user behaviour are of especial value to this field, as they may help clinicians and developers understand some of the obstacles that hinder the uptake of diabetes technology.
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Waite , M. Aldea A. Avari, P , Leal Y, Martin, C. Duce , D, Fernández-Balsells, M. Fernández-
Real J.M. , Herrero , P.,Jugnee , N, Lui, C., 1 , López, B., Massana, J. Russell, A , Reddy, M., Wos , M,
Oliver, N., 'TRUST AND CONTEXTUAL ENGAGEMENT WITH THE PEPPER SYSTEM: THE QUALITATIVE FINDINGS OF A CLINICAL FEASIBILITY STUDY'
(2020)
AbstractOpen Access on RADARBackground and aims. PEPPER (Patient Empowerment through Predictive PERsonalised decision support) is an EU-funded research project which aims to improve self-management of type 1 diabetes (T1D). The system comprises an AI insulin bolus recommender, coupled with a safety system. The aim of the qualitative arm of this clinical feasibility study was to examine the context of participants’ interaction with the PEPPER system and identify incidents where bolus recommendations were trusted and accepted.
Methods. This was a multicentre (UK and Spain) non-randomised open-labelled 6-week pilot study. Thirteen adults with T1D participated in weekly telephone interviews to explore the context of their interactions and responses to PEPPER. Data was thematically analysed through conceptual frameworks for engagement with healthcare digital behaviour change interventions.Results. Participants reported their key interactions as responding to PEPPER bolus recommendations, inputting carbohydrate values, interpreting continuous glucose monitoring (CGM) values through visualization of personal data and dealing with safety alarms. Two themes were associated with trust and engagement with the system; ‘feeling monitored’ and ‘feeling in control’. The incidents where participants trusted PEPPER also enhanced personal expertise of T1D through insights provided by the safety system such as low glucose basal insulin for pump users. Benefits were balanced against technical challenges of the system, which were used to improve the PEPPER application and enhance user experience.
Conclusion. Some participants suggested that even access to PEPPER for a temporary period could positively influence self-management strategies. Contextual interviewing is a valuable tool in mobile application development for diabetes decision support systems.
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Martin C, Aldea A, Duce D, Harrison R, Waite M, 'The Role of Usability Engineering in the Development of an Intelligent Decision Support System'
(2018)
AbstractPublished hereWe describe the role of human factors in the development of a personalised clinical decision support system for type 1 diabetes self-management. The tool uses artificial intelligence (AI) techniques to provide insulin bolus dose advice and carbohydrate recommendations that adapt to the individual.
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D. Brown, C. Martin, D. Duce, A. Aldea, R. Harrison, 'Towards a Formal Model of Type 1 Diabetes for Artificial Intelligence'
(2017)
AbstractArtificial Intelligence (AI) is potentially useful for cost effective diabetes self-management. One research priority for the development of robust and beneficial AI concerns the use of formal verification techniques to model such self-modifying systems. In the context of diabetes, formal methods may also have a role in fostering trust in the technology as well as facilitating dialogue between a multidisciplinary team to determine system requirements in a precise way. In this paper we show how the formal modelling language Event-B can be used to capture safety-critical constraints associated with AI systems for diabetes management.Published here Open Access on RADAR -
Herrero P, Lopez B, Martin C, 'PEPPER: Patient Empowerment Through Predictive Personalised Decision Support'
(2016) pp.8-9
AbstractPEPPER is a newly-launched three-year research project, funded by the EU Horizon 2020 Framework. It will create a portable personalised decision support system to empower individuals on insulin therapy to self-manage their condition. PEPPER employs Case- Based Reasoning to advise about insulin bolus doses, drawing on various sources of physiological, lifestyle, environmental and social data. It also uses a Model-Based Reasoning approach to maximise users’ safety. The system will be integrated with an unobtrusive insulin patch pump and has a patient-centric development approach in order to improve patient self-efficacy and adherence to treatment.Published here Open Access on RADAR -
Alshaigy B, Kamal S, Aldea A, Martin C, Mitchell F, 'PILeT: an Interactive Learning Tool To Teach Python'
(2015) pp.76-79
ISBN: 978-1-4503-3753-3AbstractThis paper describes a planned investigation into how learning styles and pedagogical methodologies can be embedded into an e-learning tool to assist students' learning programming. The objective of the research is to test the hypothesis that combining multiple teaching methods to accommodate dierent learners' preferences will signi�cantly improvePublished herecomprehension of concepts, which in turn increases students' con�dence and as a consequence performance in programming. An interactive learning tool to teach Python programming language to students, called PILeT, has been developed to test the hypothesis. The tool aims to be adaptable to the students' learning style and as such it will teach programming using several techniques (e.g. visual, textual, puzzles) to appeal to each preference. PILeT is suitable for
secondary school students or teachers wishing to undertake CPD (Continuing Professional Development). PILeT will be tested on �rst year undergraduate students at Oxford Brookes University.
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Brown D, Bayley I, Harrison R, Martin C, 'Developing a Mobile Case-based Reasoning Application to Assist Type 1 Diabetes Management'
(2013)
ISBN: 978-1-4673-5800-2AbstractEffective management of diabetes is crucial for patient wellbeing and the prevention of low blood sugar levels (Hypoglycemia) and high blood sugar levels (Hyperglycemia) both of which can be potentially dangerous. Traditionally log books are maintained by patients to record information such as insulin usage and their meals. The ever increasing popularity of smart phones has resulted in various applications being developed to allow patients to log data and help manage their condition. However these applications are often developed simply for the logging of data and only occasionally provide basic calculations to suggest insulin doses following a meal. The goal of this research is to use case-based reasoning techniques to suggest an insulin dosage for the patient as opposed to using a one calculation fits all approach. This is to be achieved by building a knowledge base of the patient's history that is then used to obtain a solution which best fits the current circumstances. The proposed case-based reasoning system is described alongside the development of the system to date and discussion into further research and development. The final implementation will be tested and validated using a diabetic patient simulator to create a knowledge base and observe system behavior and accuracy.Published here -
Brown D, Bayley I, Harrison R, Martin C, 'Formal specification of a mobile diabetes management application using the Rodin platform and Event-B'
(2012) pp.43-44
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Bayley I, Flood D, Harrison R, Martin C, 'Mobitest: A cross-platform tool for testing mobile applications'
(2012)
ISBN: 978-1-61208-230-1AbstractPublished hereTesting is an essential part of the software development lifecycle. However, it can cost a lot of time and money to perform. For mobile applications, this problem is further exacerbated by the need to develop apps in a short time-span and for multiple platforms. This paper proposes MobiTest, a cross-platform automated testing tool for mobile applications, which uses a domain-specific language for mobile interfaces. With it, developers can define a single suite of tests that can then be run for the same application on multiple platforms simultaneously, with considerable savings in time and money.
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Sutton D, Aldea A, Martin C, 'An ontology of diabetes self management'
(2011) pp.83-86
ISBN: 9781450309547AbstractPublished hereThis work is part of a planned larger project to develop an intelligent mobile personalised guidance service for the management of diabetes by harnessing the power of the new generation of smart phones. Existing mobile applications enable diabetic patients to record blood glucose readings, carbohydrates consumed, insulin dosage, physical activity undertaken, and other activities and observations. Our aim is to develop a lightweight ontology that captures the kinds of information recorded by such applications, and which would facilitate interoperation. In order to establish a list of terms that must be captured by the ontology, we have undertaken a systematic review of applications (limited, for the moment to the iOS platform). We use this list to establish suitable classes and properties for the ontology, and then investigate how it can be mapped on to existing standards such as HL7 RIM and OpenEHR.
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Martin C, Flood D, Sutton D, Aldea A, Harrison R, Waite M, 'A Systematic Evaluation of Mobile Applications for Diabetes Management'
6949 (2011) pp.466-469
ISBN: 978-3-642-23767-6 eISBN: 978-3-642-23768-3AbstractThis short paper contains a summary of work that is currently in progress towards the development of an intelligent, personalised tool for diabetes management. A preliminary part of the development process has consisted of a systematic evaluation of existing applications for mobile phones.Published here -
Flood D, Harrison R, Martin CE, McDaid K, 'A systematic evaluation of mobile spreadsheet apps'
(2011)
AbstractThe power and flexibility of spreadsheets have made them an essential part of modern business. The increasingly mobile nature of business has created a need to access spreadsheets while on the move. Mobile devices such as the Apple iPhone and Blackberry have enabled users to do this but the small nature of these devices has caused a number of issues for mobile spreadsheet users. This paper presents a systematic evaluation of mobile spreadsheet apps available on the iOS platform which not only includes an examination of the range of available features and functions but also examines the usability of these applications. This work also recommends some ways in which the usability of mobile spreadsheet apps can be improved. -
Garcia E, Martin C, Garcia A, Harrison R, Flood D, 'Systematic analysis of mobile diabetes management applications on different platforms'
(2011) pp.379-396
ISBN: 9783642253638AbstractPublished hereThere are a number of mobile applications available to help patients suffering from Type 1 diabetes to manage their condition, but the quality of these applications varies greatly. This paper details the findings from a systematic analysis of these applications on three mobile platforms (Android, iOS, and Blackberry) that was conducted to establish the state of the art in mobile applications for diabetes management. The findings from this analysis will help to inform the future development of more effective mobile applications to help patients suffering from Type 1 diabetes who wish to manage their condition with a mobile application.
Other publications
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Kamal S, Novo De Azevedo L, Harrison L, Dalton G, Martin C, Turner L, 'Identifying enterprise and employability opportunities in academic programmes via infographic timeline', (2023)
Published here Open Access on RADAR -
, 'Proceedings of the First Joint Workshop on AI in Health', (2018)
Published here -
Lopez, B; Herrero, P, 'Proceedings of the 2nd International Workshop on Arti�cial Intelligence for Diabetes held in conjunction with the 16th Conference on Arti�cial Intelligence in Medicine (AIME) Vienna, Austria 24th June 2017', (2017)
Open Access on RADAR -
Brown D, Duce D, Franklin R, Harrison R, Martin C, Waite M, 'SWiFT Seeing the Wood From the Trees: helping people make sense of their health data', (2015)
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C.Martin, A. Aldea, D. Brown, D. Duce, J.M. Fernández-Real, P. Gay,P. Georgiou, R. Harrison, P. Herrero, B. Innocenti, B. L{\'o}pez, Y.Leal, L. Nita, P. Pesl, R. Petite, M. Reddy, J. Shapley, F. Torrent-Fontbona, M. Waite, M. Wos and N. Oliver, 'Personalised Clinical Decision Support For Diabetes Management Using Real-time Data',
Published here
Further details
Other experience
I worked as a computer consultant for Tessella Support Services for two years before starting my D. Phil, and I worked as a Senior Lecturer at the University of Buckingham before joining Oxford Brookes University.