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Children in Cambodia provide key design priorities for below-knee prostheses: independence, functionality, comfort and cosmetic appearance
No full textIntroduction: Children with disabilities in low-resource environments (LREs) face major barriers to education, participation, and well-being. Assistive technologies like prostheses can help, but current solutions often fail to meet child-specific needs, particularly in LREs. This study engages paediatric prosthetic users in Cambodia to identify their unique user needs.
Methods: This study used a novel interactive interview with card games and functional mobility assessment. While the card games and mobility assessment provided quantitative data, the interview responses were analysed using thematic analysis.
Results: Six themes emerged from the analysis, demonstrating children remarkable understanding of both benefits and limitations of prostheses. They appreciated the independence and cosmetic appearance, but pointed to limited mobility, heavy components, and discomfort as major issues. These priorities were echoed in the card games, where anatomically realistic prostheses were the most preferred style, and culturally important activities such as walking fast, sitting cross-legged and kneeling were ranked highest.
Discussion: Children clearly expressed what it is important for them and identified key areas for improvement in current prosthetics to improve their social inclusion. Future prosthetic research and development must adopt a user-centred, culturally sensitive approach that actively involves children, ensuring prosthetic solutions meet their physical, emotional, and social needs
Futures – scenarios, options and agency – preliminary results
No full textA wide range of methodologies are available for predicting the future such as foresight. Such approaches have been widely deployed by organisations and governments to explore potential developments for purposes of planning, resilience, mitigation and adaptation. The differing methods employ a range of qualitative, quantitative and mixed methodology research tools. The future is subject to dynamic intervention as embodied in innovation and the phrase that ‘if you wish to know the future, design it’. The advent of widespread use of artificial intelligence, robotics, neurotechnology and continuous advance in each of the domains is impacting many if not all aspects of society. This review uses diverse methodologies to explore developments within a defined time horizon, a generation taken as approximately 25 years, focussed on 2050, across a range of domains and topics subject to multi, cross, inter and transdisciplinary practice. Although all domains are considered along with major influences on society, a focus is given to eight domains, medicine, robotics, photonics, materials, AI, space, physics and behavioural science, in particular, as representative examples of changes expected. Major societal and behavioural drivers identified in this presentation of preliminary data from the study include well-being, authenticity and sustainability, the steady influence of established philosophy and religion, emerging social media influences, thinking and developments arising from transcending our planetary boundaries, and the impact of disciplinary boundary morphing approaches on innovation in both established and emerging domains
Hybrid robotic and electrical stimulation-based neurorehabilitation after stroke
No full textStroke is a leading cause of adult disability, with over 70% of survivors experiencing upper-limb impairments. While rehabilitation can reduce these deficits, its intensity and availability often remain insufficient, motivating the development of technology-assisted approaches.
Rehabilitation robots enable task-specific motor training, while functional electrical stimulation (FES) supports movement by eliciting muscle contraction and providing sensory feedback. However, FES is limited by rapid muscle fatigue and can be uncomfortable over time. Hybrid systems combining robotics and FES may address these limitations by allowing consistent kinematic guidance from the robot while preserving the neurophysiological engagement provided by FES. This could enable rehabilitation training to be effective and tolerable across a range of impairment levels.
This thesis investigated the effects of hybrid robot-FES assistance and training on motor behaviour, physiological responses, and user experience in unimpaired individuals and stroke survivors, with a focus on clinical applicability. To this end, a simple and portable one-degree-of-freedom robot-FES system was developed to assist wrist flexion/extension, with both systems acting on the same joint. A series of experiments explored how robotic, FES, and hybrid assistance affect performance, effort, fatigue and user experience. Moreover, the effect of a three-week hybrid robot-FES rehabilitation training on functional and physiological recovery after stroke was evaluated.
Overall, the findings indicate that the hybrid system can effectively assist movement while remaining comfortable in unimpaired and stroke individuals, with limited fatigue increase. A three-week intervention of daily hybrid training, in addition to usual care, produced clinically meaningful improvements in impairment, function, and movement quality, alongside high patient engagement and satisfaction. Together, these results support the clinical relevance of such hybrid robot-FES rehabilitation as a safe and effective complement to conventional physiotherapy.
This thesis advances our understanding of hybrid robot-FES assistance and training, informing the development and implementation of clinically viable and efficient neurorehabilitation technologies.Open Acces
Evaluate the current evidence of using ethologically relevant pain-related behaviours in rodent persistent pain research and determine how they are influenced by experimental confounding factors
No full textDeveloping effective analgesics for chronic pain is crucial due to the limitations of current drugs, yet many promising candidates fail in clinical translation. Researchers are exploring complex ethologically relevant behaviours as non-evoked, persistent pain-related outcome measures to enhance translational success. However, their reliability across different disease models is unclear and they can be influenced by factors beyond pain. For this PhD, three systematic reviews and meta-analyses were conducted to evaluate the utility of burrowing, thigmotaxis, and rat grimace scale (RGS) score as pain-related outcome measures.
Systematic searches on multiple databases yielded retrieved studies, which were then screened against the pre-defined eligibility criteria. Included studies had their study design characteristics and experimental data extracted according to the pre-defined protocol. Effect sizes were calculated via random-effects meta-analysis. Additional analyses assessed sources of heterogeneity, risk of bias, publication bias, and correlations between ethological behaviours and stimulus-evoked limb withdrawal response.
The meta-analyses suggested that burrowing, thigmotaxis, and RGS score serve as adequate outcome measures for persistent pain, showing negative impacts from injuries and disease models associated with persistent pain, which were attenuated by analgesic drug treatments. However, their full validity requires confirmation with more data. Recommendations were made regarding specific drugs as positive controls in certain rodent disease models. Sources of heterogeneity were inconclusive due to limited data availability. Considerations included the use of sex-balanced animals and genetically diverse strains. Poor reporting of methodological quality measures hindered internal validity assessment, resulting in unclear risk of bias for most studies. Positive correlations were found between stimulus-evoked limb withdrawal and both burrowing and thigmotaxis. Limitations were also discussed.
The empirical evidence acquired aids in refining study designs, elevating experimental methodological quality, promoting reporting transparency in preclinical studies, and advancing the application of the 3Rs (Replacement, Reduction, Refinement) principle in animal pain research.Open Acces
Impacts of rising food prices on nutritional outcomes and mortality of children in low- and middle-income countries: a systematic review
No full textBackground
Estimates indicate that 45% of mortality among children under five years old is linked to nutrition. Increased food prices can reduce access to nutritious foods, increasing nutritional and health risks for children, particularly in Low- and Middle-Income Countries (LMICs). We synthesised evidence on the relationship of rising food costs with nutritional outcomes and mortality in children in LMICs.
Methods
EMBASE, MEDLINE, Global Health, EconLit, Web of Science, and six grey literature sources were searched in September 2023. Searches included key phrases such as “food price shocks" and “child malnutrition". We included any longitudinal study design, with any measure of food price increase and any measure of child malnutrition or mortality as outcomes. Results were analysed narratively with risk of bias assessed using the Newcastle Ottawa Scale. PROSPERO registration CRD42023469198.
Results
A total of 18 studies were included, covering 104 LMICs. There were 16 repeated cross-sectional or panel studies, one longitudinal cohort study and one quasi-experimental study. Five of these studies were multi-country. 16/18 studies reported a range of adverse nutritional outcomes associated with higher food costs, including mortality (five studies), stunting and low height for age (six studies), and wasting and low weight for height (five studies). Low birth weight, admissions to feeding centres, reduced consumption of rice, fruit, vegetables, and animal protein, and reduced haemoglobin concentrations were also associated with higher food prices in one study each. Subgroup analyses were limited although two studies identified larger impacts on children in urban areas, and two studies identified larger impacts where children were exposed to higher food prices at younger ages.
Discussion
Rising food prices present a risk to child health and nutrition in LMICs. Policies should prioritise increasing household income alongside structural reforms to mitigate the nutritional impacts of elevated food prices on young children and pregnant women
Incentive mechanism design for carbon-aware electric vehicle charging coordination problem
No full textIn this letter, we study the problem of coordinating the charging pattern of strategic electric vehicle (EV) users by taking carbon intensity into consideration. We implement an incentive mechanism to address the misalignment between individual cost minimisation and system-wide carbon reduction. This mechanism leverages a modified VCG framework tailored to distributed computation, enabling the system to elicit flexible participation from EV users without compromising environmental goals. While the framework supports various optimisation algorithms, we specifically select a cutting plane-based distributed algorithm due to its computational efficiency
Gerontological effects on arousal frequency, autonomic balance, and slow-wave sleep during pressure adjustments of CPAP in OSA patients
No full textObjective: Continuous positive airway pressure (CPAP) therapy is recognized as first-line treatment for obstructive sleep apnea (OSA), but tolerance to pressure adjustments may differ with age. In this study, we examined age-related differences in physiological and neurophysiological responses following CPAP pressure adjustment.
Methods: In this retrospective study, we analyzed baseline polysomnography (PSG) and CPAP titration data from 40 individuals, including 20 younger (< 65 years) and 20 older adults (≥ 65 years) matched at the group level. Time-specific analyses were conducted using 10-min windows following pressure adjustments. Group comparisons across predefined pressure categories of CPAP (4– 5, 6– 7, and ≥ 8 cmH2O) and age groups were performed using one-way analysis of variance (ANOVA) or Kruskal–Wallis tests, as appropriate, with post-hoc analyses. Single and multiple linear regression analyses were conducted to assess associations between CPAP pressure categories and physiological responses, using the 4– 5 cmH2O group as the reference and adjusting for prior pressure change history and sleep-stage distribution.
Results: Both age groups demonstrated improvements in sleep architecture and sleep disorder indices during CPAP titration. Among older individuals, analyses of 10-min periods following pressure adjustments showed a higher arousal frequency, increased elevated standard deviation (SD) of normal-to-normal (NN) intervals (SDNN) and low-frequency (LF)/high-frequency (HF) ratios, and reduced slow-wave peak-to-peak amplitudes and slopes compared to younger counterparts. Regression analyses further indicated associations between pressure categories, HRV features, and slow-wave characteristics in the elderly group.
Conclusion: These findings highlight potential age-related differences in short-term responses to pressure adjustments for CPAP. Future prospective studies are needed to validate and enhance the generalizability and robustness of these findings
Can the UK meet the World Health Organization PM2.5 interim target of 10 μg m−3 by 2030? Part II: associated health and economic benefits
No full textAir pollution has extensive, adverse impacts on human health throughout the life course. This study estimated the health and economic benefits that policy at country and city level can have on the UK achieving the PM2.5 (particles with an aerodynamic diameter < 2.5 μm) WHO interim target of 10 μg m−3. Here we quantify and monetise the health benefits using lifetable analysis from the air pollution concentrations created using sophisticated chemical transport models. Modelling predictions in 2030 were made by combining European Union and UK government’s emissions forecasts, with the Climate Change Committee’s Net Zero (NZ) Electric vehicle (EV) forecasts, and in London with the addition of local policies. UK health and monetary benefits of air pollution reductions up to 2030 were substantial with the UK population gaining 11.5 (8.7–12.8) million life years, equivalent to an improvement in average life expectancy of 2 months and monetised air pollution benefits of £218 to £300 billion (summed to 2134). The conclusions from this study contributes to the evidence base on health benefits to advocate for action and are therefore highly relevant to policy makers. From an economic perspective, this study shows that air-pollution-reduction policies costing up to £2.4 (1.8–2.7) billion per year would be justified. Furthermore, the issues addressed here, such as the co-benefit of NZ policy on EV combined with international, national and local policies toward meeting WHO targets, offer a global public health opportunity of major significance for this century and could be applicable to other international cities
Novel unsupervised techniques for mixed-type data
No full textMixed-type data sets, that is, data sets consisting of continuous and categorical variables, are prevalent across multiple sectors, such as healthcare, finance, and social sciences. While many supervised methods account for this heterogeneity in the data, unsupervised techniques that rely on a Euclidean intuition are not directly applicable to non-continuous features. This underscores the need for unsupervised learning techniques which can handle categorical, as well as mixed-type data in a flexible manner. This thesis presents novel methodological developments in two fundamental tasks in unsupervised learning; cluster analysis and outlier detection.
The first part of the thesis explores existing non-model-based algorithms for clustering mixed-type data. It identifies the main strengths and weaknesses of specific methods and provides a taxonomy of eight state-of-the-art algorithms. Moreover, the most influential data set characteristics to the clustering performance are investigated, thus motivating the development of a novel clustering framework. The proposed framework leverages ideas from information theory, highlighting the versatility of this approach in integrating different variable types to the clustering problem.
In the second part of the thesis, the focus is on defining and detecting outliers in discrete and mixed-attribute domains. A definition of outlyingness for unordered categorical data is provided and a framework for outlier quantification is devised. The presented framework reflects on the considerations implied by the given definition and employs concepts from association rule mining to assign scores of anomalous behaviour to observations. The case of mixed-type data is also explored by extending ideas from the robust statistics literature for the case of mixed continuous-ordinal data. This provides a statistically principled approach to the problem of outlier identification. The extension to nominal data and the challenges associated with the latter are thoroughly discussed. Overall, this thesis introduces novel techniques for unsupervised learning problems in the presence of categorical and mixed-type data
Phase-space approaches to decoherence and classicality in quantum theory
No full textThis thesis presents a comprehensive study of phase-space measurements, decoherence, and the emergence of classicality in quantum systems.
Motivated by limitations of position-based localisation in standard decoherence models, we develop a phase-space decoherence formalism using coherent-state positive operator-valued measures (POVMs).
These generalised measurements, constructed from overcomplete sets of coherent states, provide a natural and physically motivated framework for modelling coarse-grained quantum observations.
We develop an iterative measurement scheme for phase-space decoherence in systems with Heisenberg-Weyl, , , and symmetries.
In each case, repeated weak measurements gradually suppress quantum interference, driving the system toward a maximally mixed state.
A universal structure is shown to emerge: a single iteration maps the Wigner function to the Husimi -function, removing negativity, while full decoherence maps the singular Glauber-Sudarshan -function to the -function, eliminating all singularities.
This establishes a group-independent mechanism by which phase-space measurements induce classicality.
We compare this model to Lindblad-type dynamics, which describe open quantum systems via completely positive, trace-preserving semigroups.
For Heisenberg-Weyl and tomographic systems, the measurement channel coincides exactly with isotropic Lindblad evolution.
In and cases, the correspondence is only partial, with exact agreement in asymptotic regimes.
A universal decoherence timescale, , emerges beyond which quasi-probability distributions become strictly positive.
We then construct a stochastic unravelling based on Brownian motion on phase space, offering a geometric alternative to standard stochastic Schr\"odinger equations.
This reveals that decoherence occurs without GKSL-type dynamics in noncompact systems.
Such unravellings preserve the intrinsic phase-space symmetry and provide a natural setting for studying semiclassical limits and quantum-to-classical transitions.
Finally, we extend the framework to relativistic quantum systems by defining a covariant coherent-state POVM on the future tube and constructing a Bargmann transform to the forward light cone.
Preliminary results on relativistic phase-space decoherence are presented, along with possible directions for future research.Open Acces