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Soft scissor: A cartilage-inspired, pneumatic artificial muscle for wearable devices
Get PDFAlthough rigid exoskeletons can strengthen human capabilities or provide full assistance to patients with disabilities, their rigidity may constrain natural movement, developing tissue damage in long-term usage. Soft and semi-soft exoskeletons and exosuits exhibit both compliance and comfort, and offer the potential to provide practical and widely-adopted assistance. Soft pneumatic muscles have been explored as a means to drive wearable assist devices for over a decade; however, their softness leads to compromises in terms of power output and the precision by which forces can be applied to the human body. In this article, we introduce a novel soft extending pneumatic actuator, which combines a compliant scissor structure inspired by human cartilage and soft pneumatic muscles. The structure behaves as a compliant skeleton to the force generating pneumatic muscle, guiding its actuation behaviour and maintaining high force transmission through its body. Different designs and dimensions of the actuator and structure were investigated to observe the effect of compliance on key performance parameters. A soft single-module actuator can deliver extending force over 100 N and achieve a maximum strain of 178% when inflated at 50 kPa. A slightly thicker, but still compliant, continuum two-module actuator exhibits twice the extension compared to a single-module actuator with the same design under the same load up to 4 kg, a significant and suitable force for comfortable wearable devices. Last, a wearable prototype of this novel actuator is demonstrated, exhibiting both extension and bending actuation behaviours
Preferences for facial femininity/masculinity across culture and the sexual orientation spectrum
Get PDFJudgments of attractiveness have many important social outcomes, highlighting the need to understand how people form these judgments. One aspect of appearance that impacts perceptions of attractiveness is facial femininity/masculinity (sexual dimorphism). However, extant research has focused primarily on White, Western, heterosexual participants’ preferences for femininity/masculinity in White faces, limiting generalizability. Indeed, recent research indicates that these preferences vary by culture, and other work findsdifferences between gay/lesbian and heterosexual individuals. Aspects of identity such as culture and sexual orientation do not exist in isolation from one another, but rather intersect, leaving a critical gap in understanding. Our research therefore bridged across these hitherto separate areas of inquiry to provide a more comprehensive understanding of facial femininity/masculinity preferences. We tested how White British and East Asian Japanese individuals’ culture and sexual orientation (including, crucially, bisexual individuals) predict their femininity/masculinity preferences for White and East Asian women’s and men’s faces, using two experimental tasks (forced-choice, interactive). Results show that individuals’ culture and sexual orientation consistently interact to predict their preferences for femininity/masculinity in women’s and men’s faces, and we furthermore reveal bisexual individuals’ preferences to differ from those of other sexual orientations. We also find differences between experimental tasks, with greater preferences for femininity emerging in the interactive task, compared to the forced-choice task. Altogether, our findings highlight theimportance of considering intersecting identities, consequences of methods of measurement, and shortcomings of extant explanations for preferences for facial femininity/masculinity
Computational polyphony and diffractive ethnography: An emergent set of methods for futures-centred work in visual anthropology
No full textThis paper proposes an emergent set of methods for Visual Anthropology through which to generate new encounters with and knowledge in possible and uncertain futures. These methods are grounded in ‘computational polyphony’, a mode of practice that the authors have developed to facilitate emergent and relational ways of engaging with fieldwork recordings that are orientated around an appreciation of multi-perspectivity. The paper explains the concepts behind these methods and their alignment with diffractive ethnography.It traces their development through experimental practice enabled by the Polyphonic Documentary project and applies insights gained from this project to a place-based ethnographic study of energy futures. The argument is made that computational polyphony is a valuable tool through which to consider preferred futures in ways that take into account a multiplicity of perspectives across both the human and the more-than-human
Implementation of a hospice community service redesign: Qualitative research identifying lessons learned
Get PDFBackground: The need to improve equity of access to palliative care is well recognized; however, much less is known about how new models of hospice community services can be successfully introduced. Aim: We aimed to capture learning from the implementation experiences of hospice stakeholders during the first 12 months of a hospice community services redesign. Design: Qualitative research using individual semi-structured interviews (n = 38) and follow-up focus groups (n = 8). Methods: Participants were clinical and non-clinical staff, hospice leaders, volunteers, and external stakeholders. Interviews were analysed with framework analysis using Normalisation Process Theory. Focus groups were used to confirm and prioritise recommendations. Results: Implementation is more likely to be successful where hospice personnel are enabled to work together in understanding and adapting to new ways of working. Participants gave examples of being supported to plan activities, to form networks of participation, to pilot new ways of working, and to appraise and improve their work. Receiving feedback on progress is beneficial. Implementation strategies that are tailored to each context could be effective if they engage with hospice stakeholders to ensure that strategic aims are well-understood and that the necessary resources are available. Positive experiences of implementation are more likely where stakeholders understand the changes and can participate in planning. Where necessary, changes to human resources and technology support systems would ideally be adopted prior to making changes to patient-facing services. Conclusion: This study contributes knowledge from a charitable provider of specialist palliative care during the implementation of a hospice community service redesign. We identified opportunities for future improvement, particularly regarding communication, planning, prioritisation, and feedback. Investment of time and reflection during implementation can support the ambition of hospices to become integrated within a place-based system, to improve access to palliative care within the communities they serve. We report key implementation recommendations for organisations considering service redesign
Comparing approaches to teaching patients how to use an app-based home spirometer: A randomised controlled trial
Get PDFBackground Bluetooth enabled, app-based home spirometry has been validated for use in the diagnosis and monitoring of respiratory disease. Remote teaching (virtual or self-directed) offers the opportunity to deliver diagnostics safely and at scale. The most appropriate method of teaching home spirometry to patients is unknown.Objective: The aim of this pragmatic study undertaken during the COVID-19 pandemic was to determine whether virtual or self-directed teaching were valid methods of deploying home spirometry to patients referred for outpatient lung physiology testing.Methods: REACH-SPIRO was a single centre, unblinded, randomised controlled trial of adults referred for spirometry. Participants were randomised (1:1:1) to be taught to use a bluetooth, app-based spirometer either face to face (A), virtually (live video conferencing) (B), or self-directed (C). Forced vital capacity (FVC) and Forced expiratory volume in 1 second (FEV1) were recorded. Home spirometry readings (Spirobank Smart Spirometer) were compared to each teaching method and hospital measurements (VyaireMedical) using Bland-Altman and two-way ANOVA. Patients feedback questionnaires on acceptability and adherence were collected.Results: At total of 106 participants were randomised. Bland-Altman analysis between hospital and home FEV1 measurements in group A showed a mean difference 0.108L (95%CI: 0.040, 0.177), LoA -0.331L to 0.548L, Group B 0.152L (95%CI:0.076, 0.228), LoA -0.358L to 0.661L and Group C 0.153L (95%CI:0.077, 0.229), LoA -0.358L to 0.661L. FVC measurements in Group A showed a mean difference 0.123L (95%CI: 0.015, 0.231), LoA -0.402L to 0.648L, Group B 0.249L (95%CI: 0.143, 0.355), LoA -0.297L to 0.795L and Group C 0.340 (95%CI: 0.154, 0.525), LoA -0.556L to 1.235L. The difference in means between randomised arms does not differ in FEV1 measurements (F(2, 76) = 0.894, MSE=1.348, p=0.413) and FVC (F(2,78) = 0.177, MSE=2.082, p=0.838). Patient feedback indicated a preference for virtual or face-to-face instruction over self-directed learning due to difficulties using the app or frustration over lack of feedback.Conclusions: There was no meaningful difference in spirometry results between patients taught to use a home spirometer remotely (virtual or self-directed) or face-to-face. Spirometry values were statistically significantly lower at home than in hospital in all groups. Patients feedback indicated a preference for virtual or face to face support rather than self-directed methods. This study supports the use of virtual or self-directed teaching of home spirometry for the monitoring of respiratory disease. In doing so, we can improve access to spirometry in hard-to-reach and vulnerable populations.Trial Registration: ISRCTN:18299685Key Words: Home spirometry; disease monitoring; medical educatio
Buzzing about bees: Exploring action-based storytelling as a tool for children’s environmental engagement and agency
No full textThis article considers innovative research in neuroscience and psychology showing that we need to transform environmental storytelling, moving away from stories focused on awareness raising, to ones which develop people’s capacity for action. We investigate how this knowledge might be applied in an environmental education context, developing a model for action-based storytelling in the classroom and examining how this supports children’s engagement in and sense of agency over environmental issues. To examine how children experience action-based storytelling approaches, we ran nine workshops in primary schools. The workshop design brings developments in psychology and neuroscience into conversation with educational theory, intersecting storytelling experiences with active and experiential learning activities. Following the workshops, children completed surveys and participated in group discussions. Findings show that, having participated in the workshops, children expressed enthusiasm for further environmental learning, and reported increased levels of agency and intentions to engage with pro-environmental actions. We also provide insight regarding issues of interest to children, aiming to assist practitioners and researchers developing learning strategies. We advocate that environmental education needs to centre stories which support children to engage with relevant actions. Linked to this, we outline a model for action-based storytelling which might be adapted by educators
Defining the recommended gray zone in MGMT promoter methylation pyrosequencing reporting: A robust translatable method to implement new EANO guidelines
Get PDFBackgroundThe DNA repair protein O6-methylguanine-DNA methyltransferase (MGMT) may cause resistance of tumour cells to alkylating agents, and is a predictive biomarker in high-grade gliomas treated with temozolomide. Recent EANO guidelines recommend internal validation of MGMT methylation cut-offs and reporting of gray zone values. This study aimed to develop a method to derive a gray zone from pyrosequencing MGMT methylation data.MethodsWe developed a method to find the optimal gray zone using pyrosequencing MGMT methylation values (CpG sites 72-83) from 308 glioblastoma cases with overall survival data. Each integer below the methylated threshold defined a new possible gray zone and categorisation which was used as a variable in a multivariate Cox proportional hazards regression model. The optimal gray zone was selected as the option that had a statistically different survival function from the methylated and unmethylated groups, with the largest log likelihood ratio test statistic. We applied the method to a validation cohort of 115 glioblastoma cases.ResultsOur method successfully identified a gray zone in our development cohort. The following categorisation gave 3 distinct survival functions: methylated >=12% (n=152 cases), gray zone 5-12% (n=43), unmethylated <5% (n=113). This categorisation was better at predicting survival than the existing categorisation (methylated >=12%, unmethylated <12%). Validating our method showed a sufficient sample size and time to follow up is recommended to apply our method.ConclusionsWe have developed a translatable method to identify the optimal MGMT gray zone from pyrosequencing data in line with recent EANO guidelines, to enhance clinical decision-making
Explainable AI in medical imaging: An interpretable and collaborative federated learning model for brain tumor classification
Get PDFIntroduction: A brain tumor is a collection of abnormal cells in the brain that can become life-threatening due to its ability to spread. Therefore, a prompt and meticulous classification of the brain tumor is an essential element in healthcare care. Magnetic Resonance Imaging (MRI) is the central resource for producing high-quality images of soft tissue and is considered the principal technology for diagnosing brain tumors. Recently, computer vision techniques such as deep learning (DL) have played an important role in the classification of brain tumors, most of which use traditional centralized classification models, which face significant challenges due to the insufficient availability of diverse and representative datasets and exacerbate the difficulties in obtaining a transparent model. This study proposes a collaborative federated learning model (CFLM) with explainable artificial intelligence (XAI) to mitigate existing problems using state-of-the-art methods. Methods: The proposed method addresses four class classification problems to identify glioma, meningioma, no tumor, and pituitary tumors. We have integrated GoogLeNet with a federated learning (FL) framework to facilitate collaborative learning on multiple devices to maintain the privacy of sensitive information locally. Moreover, this study also focuses on the interpretability to make the model transparent using Gradient-weighted class activation mapping (Grad-CAM) and saliency map visualizations. Results: In total, 10 clients were selected for the proposed model with 50 communication rounds, each with decentralized local datasets for training. The proposed approach achieves 94% classification accuracy. Moreover, we incorporate Grad-CAM with heat maps and saliency maps to offer interpretability and meaningful graphical interpretations for healthcare specialists. Conclusion: This study outlines an efficient and interpretable model for brain tumor classification by introducing an integrated technique using FL with GoogLeNet architecture. The proposed framework has great potential to improve brain tumor classification to make them more reliable and transparent for clinical use