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Recommendations for tracking the residual forearm in people with trans-radial limb difference using marker-based motion capture
Get PDFUpper-limb prostheses users report unsatisfactory ‘socket fit’, leading to poor outcomes. Previous attempts to measure socket-residuum coupling as a proxy for upper-limb socket fit were limited by their modelling approach (<6-degrees of freedom (DoF) models) and focused on trans-humeral prosthesis users. Prince described a 6-DoF model to track trans-radial (TR) socket-limb coupling, but this required bespoke measurement equipment and was only demonstrated in one intact-limbed participant. Current International Society of Biomechanics (ISB) recommendations for marker-based forearm tracking include ulna styloid markers, therefore being unsuitable for people with TR limb difference. To identify alternative marker frames, ten intact limb participants performed six different movements, nine times each. Displacement of an ulna marker ‘cloud’ of markers was evaluated, for 18 alternative tracking frames, none of which utilised wrist markers. The optimal frames were a) for a long residuum/full forearm - markers on humeral epicondyles and mid-distal ulna bone (62.5-75% of a typical ulna), and b) for a shorter residuum – markers on humeral epicondyles and distal ulna bone (25-50% of a typical ulna). These frames compared favourably to the ISB frame in the point cloud displacement metric. This study provides novel solutions to tracking the ulna bone of people with TR limb difference
Hamstring Strength and Architectural Properties Are Associated with Running Biomechanics
Get PDFApplied muscular strain and hamstring strain capacity have a joint interaction on hamstring strain injury (HSI) with modifiable risk factors frequently assessed. However, to date there is limited observations on the interaction between these factors. The purpose of the present study was to observe if spatiotemporal characteristics, running kinematics and muscle activation were related to modifiable risk factors of HSI. Twenty-two competitive team sport athletes (24.7 ± 4.3 years, 1.82 ± 0.07 m, 84.9 ± 8.5 kg) participated whereby the Bicep femoris long head (BFLH) fascicle length assessed via ultrasound and isokinetic eccentric hamstring strength was assessed. With running assessment performed at 18 km/h, capturing running kinematics and muscle activation. Multiple linear regressions were used to examine the relationship of running kinematics and muscle activation on the modifiable risk factors of HSI on. The overall model (F2,19) was statistically significant for both relative eccentric hamstring strength (F = 23.58, p < 0.001) and BFLH fascicle length (F = 18.87, p < 0.001) highlighting spatiotemporal characteristics, running kinematics and hamstring activation were found to be significantly related to the modifiable risk factors. There is a complex interrelationship between running mechanics and hamstring muscle properties, with the potential of either cause or consequence association
Exploring staff views about implementing hospital-based exergames to support older adults with frailty: a qualitative study
No full textObjective: To explore the views of staff in hospital rehabilitation wards about factors influencing implementation of Exergames for older adults with mild to moderate frailty.Design: Qualitative descriptive study.Setting: Three rehabilitation and frailty wards across two NHS hospital settings in the North West of England.Participants: A purposive sample of 22 healthcare professionals were recruited to take part in the study.Intervention: Therapy staff were instructed on how to use the Exergames with patients. Trained therapists, and other healthcare professionals, took part in a focus group or semi-structured interview to share perceived constraints to Exergames implementation. The research physiotherapist also reflected on each ward’s response to the intervention, and the Exergames training sessions. Pre-implementation actions in the Quality Implementation Framework informed the topic guide and analysis. Data was analysed using the Framework approach.Results: Three face-to-face focus groups and seven interviews (in-person or online) were conducted, and the research physiotherapist recorded 25 hours of observations. Themes represented factors impacting Exergames use in a hospital environment. These included: competing priorities for staff availability and time; buy-in from key stakeholders; the user-friendly integration of the Exergames system; flexible training sessions; and development of a feasible and effective delivery framework.Conclusions: The dynamic nature of hospital wards, such as changes of staff and ward focus, and complexity of interactions within and between individual, ward and organisational levels, means effective Exergames implementation requires coordinated efforts, and ongoing adaptability
Prediction of Violence Against Women Using Ensemble Learning Models: A Comparative Study of LightGBM, XGBoost, and Others
Get PDFViolence against women and the possibility of its occurrence among children is a very serious issue that negatively impacts the physical, psychological, and emotional aspects of the victims and those around them. Various efforts have been made to reduce violence against women and children; however, in reality, such violence still occurs significantly in many countries due to emotions and turmoil within human relationships. It is necessary to propose prediction methods so that violence can be reduced through early observation and intervention against violence experienced by women. machine learning, as one of the Artificial Intelligence algorithms, offers a solution to identify and predict the risk of violence. This study aims to explore the use of several Ensemble Learning models, such as LightGBM, XGBoost, CatBoost, and AutoEnsemble, which are expected to improve prediction accuracy and stability. This study uses a dataset consisting of 348 samples with 5 selected features that represent indicators relevant to the risk of violence against women. The test results show that XGBoost and CatBoost achieved the highest accuracy, approximately 73%, with a precision of 76%, recall of 65%, and F1-Score of 70%. TabNet demonstrated similar performance with an accuracy of 73%, but with a higher recall of 70%. Meanwhile, LightGBM showed slightly lower performance with 68% accuracy and an F1-Score of 64%. AutoEnsemble produced stable results with 73% accuracy, 76% precision, 65% recall, and 70% F1-Score. However, the practical limitation of this study lies in the relatively small dataset size, which may affect the model’s generalization ability when applied to larger or more diverse features. The findings of this study indicate that Ensemble Learning models can provide accurate and effective results in predicting violence against women. It is hoped that this research can contribute to more proactive and accurate efforts to prevent violence against women in the future
Music-induced physiological markers for detecting Alzheimer's disease using machine learning
Get PDFIntroduction: Alzheimer's disease (AD) is characterized by progressive cognitive and emotional decline, highlighting the need for novel, non-invasive biomarkers to aid in early detection, monitoring, and stage-specific interventions. This study investigates music-evoked physiological responses as potential biomarkers of AD and evaluates their translational value using machine learning (ML). Materials and methods: A total of 36 AD patients, spanning different severity levels, listened to emotionally evocative musical excerpts while electrodermal activity and facial electromyography (corrugator and zygomaticus muscles) were recorded. Machine learning models were then trained on these signals to classify the presence and severity of AD and to detect residual emotion-specific physiological responses elicited by music. Results: Physiological reactivity to music declined with disease progression, with positive emotions eliciting more distinct responses than negative ones. The Random Forest classifier distinguished AD patients from healthy controls with 70.5% accuracy, while the Naïve Bayes model predicted severity with 65.6% accuracy, demonstrating that ML models can detect subtle music-evoked physiological differences even in individuals with AD. Discussion: Music-evoked physiological signals reflect the hierarchical disruption of emotion-related neural circuits in AD and hold promise as complementary biomarkers for disease presence and stage. When combined with machine learning (ML), these measures provide a non-invasive, ecologically valid approach to support early detection, monitoring, and the development of stage-specific interventions
Human perception and response to sound from unmanned aircraft systems within ambient acoustic environments
No full textPotential opportunities for unmanned aircraft systems (UAS) to offer societal benefits are accompanied by noise impact risks. Accordingly, it is important to develop greater understanding of perception and response to UAS sound. A laboratory listening experiment was undertaken to address this aim by investigating psychoacoustics of UAS sound exposure. The experiment incorporated contextual auditory and soundscape factors by embedding spatially-rendered UAS sounds within urban acoustic environments. The UAS covered varying aircraft designs, operating modes and numbers of flights. The experiment was focussed on determining noticeability and noise annoyance. The results indicate that annoyance responses were influenced by UAS type, operational mode, sound characteristics, quantities of flights, and the ambient acoustic environments in which UAS events occurred. Annoyance also appeared to have associations with personal attitude towards advanced air mobility technology, and with classification of residence area. Noticeability appeared to be influenced by UAS type, operating mode, loudness and ambient environment
Evaluating Tender Using Sustainable Products Model in Goods Procurement: A case of the electricity distributor in Ghana.
Get PDFSustainability challenges confronting developing countries are numerous and substantial and appear to be exacerbating overtime. Sustainable Public Procurement could be of significant strategic importance to developing countries such as Ghana who spend substantial proportions of their Gross Domestic Product in public procurement. In the tapestry of Ghana's development, the electricity distribution organisation emerges as a vital thread, interweaving economic progress and societal welfare. This case study research will assess the level of knowledge and appreciation by internal and external stakeholders in sustainable product procurement to identify relevant qualitative factors to achieve Best Value for Money procurement. The aim for this study is to investigate how sustainability factors are not considered as key factors of importance when procuring goods and include it within the Ghanaian electricity distribution organisation. Main objectives are therefore:1. To find Sustainable Product key factors for tender evaluation in the electricity distribution organisation in Ghana.2. To find a Model that will use factors obtained in objective 1 to evaluate tenders for goods procurement.3. To test the aforementioned model on goods procurement tenders process for the electricity distribution organisation in Ghana.The premise for choice of approach to this research was influenced by the search for alternatives to tackle industry problem through practical and hands-on solution.The research philosophy in this qualitative study shaped the researcher's approach to understand and interpret social phenomena, influenced the choice of methods and data analysis techniques, and acknowledged the role of the researcher in the research process. It explained how the researcher gained meaningful insights into the complexities of human experiences and behaviour in the research process and discussed the specific research strategy employed, detailing the qualitative methods and techniques used to gather and analyse data.From the identification of sustainability drivers to the exploration of barriers hindering seamless integration, the literature review aimed to unravel the multifaceted dimensional mix that defined sustainability within the public procurement processes and importance of infusing sustainability into tender evaluations.The inductive approach to data collection was elaborated. A pilot study in the form of qualitative interviews was discussed. The use of Computer Assisted Qualitative Data Analysis Software e.g., NVivo 12 & 14, in analysing data from the pilot to the main study was discussed along with how rigor was ensured. A reflective learning cycle approach, which was subjected to the ‘Gibbs’ reflective cycle, was used to navigate professional development in the 5-year doctoral journey to alter the underlying, governing variables and assumptions in the procurement strategy
Linear and Multidirectional Speed Testing (On-Field and Off-Field) Protocols in Senior and Elite Female Football.
Get PDFBeato, M, Datson, N, Clemente, FM, Harper, DJ, Fílter, A, Emmonds, S, Dos' Santos, T, and Jones, PA. Linear and multidirectional speed testing (on-field and off-field) protocols in senior and elite female football. J Strength Cond Res 39(1): e70-e84, 2025-Female football has had a considerable rise in popularity with millions of fans after matches during the recent Women's World Cup. Despite this, the football scientific literature is still biased toward male footballers; therefore, this review aims to present the most recent literature and best practices for assessing linear and multidirectional speed and underpinning physical qualities, and to offer practical recommendations based on the most recent evidence and authors' expertise for practitioners working with female football players. This review categorizes tests as on-field and off-field, highlighting common protocols, their advantages, and the existing limitations. Among the most common on-field tests, we found the change of direction speed, horizontal deceleration, linear sprinting, and curved sprinting; although the suggested off-field tests are multi-joint isometric, single-joint isometric, isokinetic dynamometry, Nordic hamstring, and vertical jumps. These tests are valuable tools for assessing players' physical abilities, serving as a benchmark for tracking physical changes throughout the season, and aiding practitioners in individualizing and optimizing training protocols. This review highlights that strength (eccentric, isometric, concentric, and reactive) and rapid force production are crucial for generating braking and propulsive forces, which underpin linear and multidirectional motion. In conclusion, the evidence and practical suggestions reported in this review will improve the practitioners' knowledge of which tests and the consequent training protocols can be used in senior and elite female football players. But practitioners need to be aware about the scarcity of comprehensive studies on female soccer that hinders a complete understanding of the reliability of all assessment protocols used. [Abstract copyright: Copyright © 2024 National Strength and Conditioning Association.
Socio-Spatial Framework to Improve Air Quality in Transit-Oriented Development
No full textThis research focuses on air quality management in Transit-Oriented Development (TOD) neighbourhoods, addressing the complex interplay between urban design, community behaviour, and regulatory policies. TODs, while promoting sustainable urban development, can inadvertently exacerbate air quality issues due to high-density urban structure and increased localised activities that feature this kind of development.The study aimed to develop a socio-spatial framework for managing air quality in TODs, focusing on Urban Heat Island (UHI) effects and air pollution. This conceptual framework identifies key pillars influencing TOD's air quality, analyses their interconnections, and proposes strategies to enhance their performance.TOD neighbourhoods in Manchester City, UK, were utilised as case studies to test and validate the framework: Manchester Piccadilly and East Didsbury. A mixed-methods approach was employed, integrating geospatial analysis of urban configurations, UHI intensity, and air pollution in both areas. A quantitative analysis of residents' commuting habits through questionnaires, combined with qualitative insights from the focus group with experts and stakeholders, complemented the geospatial analysis.The research identified five key pillars affecting air quality in TODs: planning and design, traffic patterns, policy and regulation, socio-political engagement, and community behaviour. The study found that urban structure significantly influenced UHI intensity, while traffic patterns, particularly non-exhaust emissions, were major contributors to air pollution. Community behaviour and policy gaps were found to indirectly impact air quality by influencing travel choices and traffic conditions.The findings highlight the need for a holistic approach to TOD planning that considers physical urban characteristics besides social and political factors. This study provides a nuanced understanding of air quality management in TODs, emphasising the importance of integrated strategies encompassing urban design, traffic management, policy, and community engagement and behaviour. The developed framework provides a comprehensive tool for stakeholders to address air quality challenges in TODs
Using Wearable Soft Sensors for Gesture Recognition
Get PDFThe increasing prevalence of hand impairments due to conditions such as arthritis, Cerebral Palsy, Parkinson’s Disease, and stroke presents significant challenges in everyday activities, such as tying shoes or getting dressed. In the UK, long-term musculoskeletal conditions are on the rise, highlighting the urgent need for effective rehabilitation methods. Despite physical therapy's potential to help regain motor skills, there is no consensus on optimal methods for promoting neuroplasticity. Robotic and wearable technologies have emerged as viable solutions, with soft robotics offering distinct advantages due to their flexibility, adaptability, and portability. However, limited evidence supports the superiority of conventional robotic devices over traditional therapies.This PhD research investigates the development of a soft tactile sensor aimed at improving rehabilitation outcomes for individuals with upper limb impairments, focusing on muscle activity during hand movements in healthy, Parkinson’s, and stroke patients. The motivation for this study lies in the growing demand for accessible rehabilitation solutions that address the UK’s healthcare challenges, particularly for stroke survivors, where upper limb rehabilitation is under-resourced. The primary aim of this research is to design and validate a novel fabric-based tactile sensor using Eeon-Tex conductive stretchable elastic fibre, capable of accurately detecting muscle activity. The methodology includes the fabrication of the sensor, an investigation into the nonlinear hysteresis phenomenon, and validation against a commercial surface electromyography (sEMG) sensor. A key focus is on developing reliable alternatives to traditional sEMG systems, making rehabilitation more accessible.Key findings demonstrate that the soft tactile sensor is effective in capturing distinct muscle activity patterns across various patients, particularly during tasks involving gripping and manipulating objects. Statistical analysis showed high signal similarity between the tactile sensor and sEMG, confirming the sensor’s reliability and potential for clinical application. Additionally, strategies were developed to mitigate the effects of nonlinear hysteresis on the sensor’s performance.In conclusion, this research contributes to the field of rehabilitation technology by providing a cost-effective, reliable alternative to conventional muscle monitoring systems. The significance of this work lies in its potential to improve the quality of life for individuals with mobility impairments, particularly in an ageing population, while addressing the resource challenges faced by healthcare systems such as the National Health Service (NHS)
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