We propose a real-time 3D human pose estimation and motion analysis method termed RePose for rehabilitation training. It is capable of real-time monitoring and evaluation of patients'motion during rehabilitation, providing immediate feedback and guidance to assist patients in executing rehabilitation exercises correctly. Firstly, we introduce a unified pipeline for end-to-end real-time human pose estimation and motion analysis using RGB video input from multiple cameras which can be applied to the field of rehabilitation training. The pipeline can help to monitor and correct patients'actions, thus aiding them in regaining muscle strength and motor functions. Secondly, we propose a fast tracking method for medical rehabilitation scenarios with multiple-person interference, which requires less than 1ms for tracking for a single frame. Additionally, we modify SmoothNet for real-time posture estimation, effectively reducing pose estimation errors and restoring the patient's true motion state, making it visually smoother. Finally, we use Unity platform for real-time monitoring and evaluation of patients' motion during rehabilitation, and to display the muscle stress conditions to assist patients with their rehabilitation training.
Background With prevalence rates of cardiovascular disease (CVD) on the rise across the globe, people with CVD are an emerging vocational rehabilitation (VR) consumer population. Objective This article provides recommendations for working with people who have CVD across the phases of the VR process. Method Following an overview of the etiology, incidence, prevalence, and career development implications of CVD, the authors present direct service and advocacy recommendations for VR professionals. Results The importance of access to quality healthcare, lifestyle and environmental modifications to promote heart and circulatory health, employer consultation, workplace accommodations and universal design, and interface with medical and mental health professionals is emphasized throughout the article. Conclusions Rehabilitation professionals must be prepared to meet the needs of this growing and diverse clientele as people with CVD seek assistance from the VR program in acquiring, maintaining, and advancing in meaningful, satisfying employment.
Janice Rubin, Emily A. Brinck, Laura Gorman
et al.
People with psychiatric disabilities represent a significant percentage of the individuals served by rehabilitation programs. Research has shown that most individuals with psychiatric disabilities are interested in employment but vocational providers may lack the knowledge, skills, and abilities to assist this population (Henry & Lucca, 2004; Medar et al., 2017), and this paper may provide valuable considerations to Vocational Rehabilitation Counselors to increase positive outcomes such as securing and maintaining employment. According to Substance Abuse and Mental Health Service Administration (SAMSHA, 2012) unemployment of people with psychiatric disabilities is around 60-90%, work has always been an integrating force, although many people with psychiatric disabilities are unemployed. This article will provide information which will contribute to a better understanding of psychiatric disabilities and the employment and career counseling strategies that have proven successful.
The present research investigated the lived experiences of mothers of children with mild intellectual disabilities in a central city in Iran. The research method was qualitative and phenomenological type. Eleven families were selected from males with intellectual disabilities who were graduated from secondary vocational centers through purposeful sampling and participated in in-depth semi-structured interviews. The data was analyzed by Colaizzi method. The main themes extracted from the interviews with mothers were: employment and financial independence; physical and mental health; sexual and marriage issues; and life after the death of parents. The results showed the lived experiences of mothers and their concerns regarding employment, marriage, sexual issues, physical and mental health, and the future of their children. The results recommended that the government should take steps to remove life obstacles for adults with intellectual disabilities by modifying the methods of education and rehabilitation of people with intellectual disabilities in the country.
Maria Micaela Fonseca, Nuno Fachada, Micael Sousa
et al.
The field of serious games for health has grown significantly, demonstrating effectiveness in various clinical contexts such as stroke, spinal cord injury, and degenerative neurological diseases. Despite their potential benefits, therapists face barriers to adopting serious games in rehabilitation, including limited training and game literacy, concerns about cost and equipment availability, and a lack of evidence-based research on game effectiveness. Serious games for rehabilitation often involve repetitive exercises, which can be tedious and reduce motivation for continued rehabilitation, treating clients as passive recipients of clinical outcomes rather than players. This study identifies gaps and provides essential insights for advancing serious games in rehabilitation, aiming to enhance their engagement for clients and effectiveness as a therapeutic tool. Addressing these challenges requires a paradigm shift towards developing and co-creating serious games for rehabilitation with therapists, researchers, and stakeholders. Furthermore, future research is crucial to advance the development of serious games, ensuring they adhere to evidence-based principles and engage both clients and therapists. This endeavor will identify gaps in the field, inspire new directions, and support the creation of practical guidelines for serious games research.
Valeria Cesaroni, Eleonora Pasqua, Piercosma Bisconti
et al.
AI-based technologies have significant potential to enhance inclusive education and clinical-rehabilitative contexts for children with Special Educational Needs and Disabilities. AI can enhance learning experiences, empower students, and support both teachers and rehabilitators. However, their usage presents challenges that require a systemic-ecological vision, ethical considerations, and participatory research. Therefore, research and technological development must be rooted in a strong ethical-theoretical framework. The Capability Approach - a theoretical model of disability, human vulnerability, and inclusion - offers a more relevant perspective on functionality, effectiveness, and technological adequacy in inclusive learning environments. In this paper, we propose a participatory research strategy with different stakeholders through a case study on the ARTIS Project, which develops an AI-enriched interface to support children with text comprehension difficulties. Our research strategy integrates ethical, educational, clinical, and technological expertise in designing and implementing AI-based technologies for children's learning environments through focus groups and collaborative design sessions. We believe that this holistic approach to AI adoption in education can help bridge the gap between technological innovation and ethical responsibility.
Large language models (LLMs) are increasingly under scrutiny for perpetuating identity-based discrimination in high-stakes domains such as hiring, particularly against people with disabilities (PwD). However, existing research remains largely Western-centric, overlooking how intersecting forms of marginalization--such as gender and caste--shape experiences of PwD in the Global South. We conduct a comprehensive audit of six LLMs across 2,820 hiring scenarios spanning diverse disability, gender, nationality, and caste profiles. To capture subtle intersectional harms and biases, we introduce ABLEIST (Ableism, Inspiration, Superhumanization, and Tokenism), a set of five ableism-specific and three intersectional harm metrics grounded in disability studies literature. Our results reveal significant increases in ABLEIST harms towards disabled candidates--harms that many state-of-the-art models failed to detect. These harms were further amplified by sharp increases in intersectional harms (e.g., Tokenism) for gender and caste-marginalized disabled candidates, highlighting critical blind spots in current safety tools and the need for intersectional safety evaluations of frontier models in high-stakes domains like hiring.
Traditionally, the impact of minimum wages on employment has been studied, and it is generally believed to have a negative effect. Yet, some recent studies have shown that the impact of minimum wages on employment can sometimes be positive. In addition, certain recent proposals set a higher minimum wage than the wage earned by some high-productivity workers. However, the impact of minimum wages on employment has been primarily studied on low-skilled workers, whereas there is limited research on high-skilled workers. To address this gap and examine the effects of minimum wages on high-productivity workers' employment, I construct a macroeconomic model incorporating productivity fluctuations, incomplete markets, directed search, and on-the-job search and compare the steady-state distributions between the baseline model and the model with a minimum wage. As a result, binding minimum wages increase the unemployment rate of both low and high-productivity workers.
Neave O'Clery, Juan Chaparro, Andres Gomez-Lievano
et al.
What drives formal employment creation in developing cities? We find that larger cities, home to an abundant set of complex industries, employ a larger share of their working age population in formal jobs. We propose a hypothesis to explain this pattern, arguing that it is the organised nature of formal firms, whereby workers with complementary skills are coordinated in teams, that enables larger cities to create more formal employment. From this perspective, the growth of formal employment is dependent on the ability of a city to build on existing skills to enter new complex industries. To test our hypothesis, we construct a variable which captures the skill-proximity of cities' current industrial base to new complex industries, termed 'complexity potential'. Our main result is that complexity potential is robustly associated with subsequent growth of the formal employment rate in Colombian cities.
Augmented Reality (AR) technologies hold immense potential for revolutionizing the way individuals with disabilities interact with the world. AR systems can provide real-time assistance and support by overlaying digital information over the physical environment based on the requirements of the use, hence addressing different types of disabilities. Through an in-depth analysis of four case studies, this paper aims to provide a comprehensive overview of the current-state-of-the-art in AR assistive technologies for individuals with disabilities, highlighting their potential to assist and transform their lives. The findings show the significance that AR has made to bridge the accessibility gap, while also discussing the challenges faced and ethical considerations associated with the implementation across the various cases. This is done through theory analysis, practical examples, and future projections that will motivate and seek to inspire further innovation in this very relevant area of exploration.
Christian Lourido, Zaid Waghoo, Hassam Khan Wazir
et al.
Many neurological conditions, e.g., a stroke, can cause patients to experience upper limb (UL) motor impairments that hinder their daily activities. For such patients, while rehabilitation therapy is key for regaining autonomy and restoring mobility, its long-term nature entails ongoing time commitment and it is often not sufficiently engaging. Virtual reality (VR) can transform rehabilitation therapy into engaging game-like tasks that can be tailored to patient-specific activities, set goals, and provide rehabilitation assessment. Yet, most VR systems lack built-in methods to track progress over time and alter rehabilitation programs accordingly. We propose using arm kinematic modeling and capability maps to allow a VR system to understand a user's physical capability and limitation. Next, we suggest two use cases for the VR system to utilize the user's capability map for tailoring rehabilitation programs. Finally, for one use case, it is shown that the VR system can emphasize and assess the use of specific UL joints.
The objective of this investigation was to assess the structural validity of the Arabic Quick Disabilities of the Arm, Shoulder and Hand (QuickDASH) in individuals suffering from upper extremity musculoskeletal disorders, utilizing both exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). A group of participants with upper extremity musculoskeletal disorders attending physical therapy clinics were recruited. Upon their initial visit to physical therapy, participants were requested to complete the Arabic versions of the QuickDASH, as well as the Numeric Pain Rating Scale. In order to determine the number of factors, parallel analysis was employed in the EFA, while maximum likelihood was utilized for extraction. The fit of the model identified using EFA was subsequently examined using CFA, incorporating multiple fit indices. The outcomes of the EFA indicated the existence of a one-factor structure, accounting for a considerable 50.22% of the total variance. It was observed that all of the QuickDASH items displayed loadings on the single factor, with values ranging from 0.35 to 0.77. However, the multiple fit indices obtained from the CFA did not provide sufficient support for the fit of the initially proposed unidimensional structure. The data showed good fit to the unidimensional model after adding error covariance: chi-square = 100.52 [degrees of freedom (df) = 40, P < 0.001], chi-square/df = 2.51, Tucker–Lewis index = 0.94, comparative fit index = 0.95, root mean square error of approximation = 0.077 [90% confidence interval (CI) = 0.058-0.096], and standardized root mean residual = 0.048. Ultimately, the findings from the EFA provided evidence supporting the unidimensionality of the Arabic QuickDASH, while the CFA supported the unidimensionality of the QuickDASH after addressing the issue of local dependency between some scale items.
Vocational rehabilitation. Employment of people with disabilities
Objective: To determine the effectiveness of ten therapeutic exercises on the patients of Oro-pharyngeal Dysphagia (OD) clinically diagnosed with one structural disorder (Head and neck cancer; HNC) and two neurological disorders (Traumatic Brain Injury; TBI and Cerebral Vascular Accidents; CVA).
Methodology: The Quasi experimental study (pretest-posttest design) was conducted, gathering a sample of 75 patients with mild to moderate Oro-pharyngeal Dysphagia (OD) severity through purposive sampling technique from Govt. and private hospitals without no age and geneder limits. The patients with neurological diseases, nasogastric (NG) tube and tracheostomy were excluded. Two screening test (a) Glassgow Coma Scale (GCS) and (b) The Repetitive Saliva Swallowing Test (RSST) were used to investigate patient’s consciousness and voluntarily swallow, respectively. To quantify the effectiveness of therapeutic manual, The Eating Assessment Tool (EAT-10) was employed as baseline (pre-test and post-test). Therapeutic protocol was received by the patients twice a week for six weeks in the clinical setting and post test was administered on patients’ follow-ups and some through online calls.
Results: Using SPSS version 26, Shapiro-Wilk test demonstrated normality in the data distribution showing kurtosis (+10, -10) and skewness (+3, -3) values falling within their ranges. Consequently, parametric tests: One-way between-subject ANOVA was employed to compare the statistical significant mean difference between the groups (HNC, TBI, CVA) on EAT-10 score measuring the effect of therapeutic exercises manual for OD. Paired sample t-test was run to investigate the mean difference of EAT-10 scores within subjects before and after the implication of therapeutic exercises manual. One-way between-subject ANOVA identified a significant mean difference of EAT-10 score between three groups F (2, 72) = 17.64, p< .05, with large effect size (η2= .970). Paired sample t-test results indicated a significant mean difference (t= 80.884, df= 74, p< .005, one-tailed) with large effect size (d = .82) within the subjects before and after the intervention.
Conclusion: So, findings addressed a large improvement in Oro-Pharyngeal Dysphagia after the implementation of therapeutic exercises manual.
Vocational rehabilitation. Employment of people with disabilities, Therapeutics. Psychotherapy
Mohammed Alshehri, Sunil Kumar Sharma, Priya Gupta
et al.
Visual impairment poses significant challenges to individuals in their daily lives, limiting their access to information encoded in the visual domain. This paper presents a novel approach to empower the visually impaired by developing a system capable of translating handwritten digits into spoken language. The proposed system leverages a combination of advanced deep learning (DL) architecture, Hopfield Recurrent Neural Network-Grasshopper Optimization Algorithm (HRNN-GOA), and traditional image-processing techniques such as Haralick features. The system employs HRNN-GOA as the core model for handwritten digit recognition. HRNN-GOA exhibits superior sequential learning capabilities, capturing intricate patterns in the handwritten digits. Additionally, Haralick features are extracted from the input images, providing complementary texture-based information. The fusion of DL and traditional features aims to enhance the robustness and accuracy of the recognition process. The experimental results demonstrate the effectiveness of the proposed approach in accurately recognising handwritten digits. The HRNN-GOA model achieves state-of-the-art performance in digit classification tasks, while the incorporation of Haralick features further refines the recognition process, especially in cases with complex textures or variations in writing styles. The simulation results are compared against state-of-the-art strategies in terms of many metrics, including accuracy, precision, recall, specificity, area under the curve, F1-score, and false-positive rate. The proposed system has the potential to significantly improve the independence and quality of life for individuals with visual impairments by providing seamless access to numerical information in a spoken format. Future endeavours could explore the extension of this framework to recognise and translate more complex handwritten symbols or characters. Additionally, user experience studies and real-world deployment assessments will be crucial for refining the system and ensuring its practical utility in diverse scenarios.
Vocational rehabilitation. Employment of people with disabilities
Background: Emotion- and problem-focused coping strategies are frequently employed by caregivers of autistic children to increase their general well-being and resilience to the stress of raising the child. Although these strategies cannot directly address the situation, it is useful for handling stressful situations that cannot change.
Objectives: The study seeks to explore and understand the emotion- and problem-focused strategies that caregivers use to cope with the challenges of raising a child with autism.
Method: This was a qualitative, exploratory and descriptive research study. Twenty-eight caregivers were purposive-convenient sampled from the public special schools where their autism spectrum disorder (ASD) children are schooling. Semi-structured interviews were used to gather data, which were then transcribed and subjected to thematic analysis.
Results: Positive emotion-focused strategies include positive reappraisal, reframing and acceptance. Negative emotion-focused strategies include denial, emotional release, cognitive distortion, self-isolation, overprotection, negative self-talk, punishment and religion. Problem-focused coping strategies include active and adaptive coping, peer group, professional support and social support.
Conclusion: The coping methods that have been identified can be integrated into intervention programmes and serve as a guide for specialised institutions that offer more extensive knowledge and assistance to families who are caring for children with ASD.
Contribution: The study contributes to understanding the emotion- and problem-focused strategies adopted by rural caregivers in managing their emotions, interpretation of the situation and adjusting to the demands of raising an autistic child.
Vocational rehabilitation. Employment of people with disabilities, Communities. Classes. Races
Background: Developing a good working alliance with clients with a severe mental illness (SMI) is a core competency of the employment specialist (ES). The ES's assessment of the working alliance was found to be related to the client's acquisition of a job in the regular market but we have little information on the processes and factors involved. Objective: To understand the development of the work alliance as assessed by the ES and its relationship to the client's acquisition of employment. Factors that may facilitate or hinder the development and evolution of the alliance were also explored. Methods: Cluster analysis was used to define alliance development patterns, while frequency analyses were used to identify differences between the patterns in terms of whether the clients with SMI obtained (or not) employment. Interviews with ESs explored factors that may have explained the different patterns. Results: Three patterns of working alliance were found and the one most often linked to client employment was the very high and stable pattern. The factors that might explain the different patterns are complex and interrelated. Conclusion: The results can be considered in the ES's initial and ongoing training on the working alliance and the implementation of quality supported employment programmes.
The physical and economic damages of hurricanes can acutely affect employment and the well-being of employees. However, a comprehensive understanding of these impacts remains elusive as many studies focused on narrow subsets of regions or hurricanes. Here we present an open-source dataset that serves interdisciplinary research on hurricane impacts on US employment. Compared to past domain-specific efforts, this dataset has greater spatial-temporal granularity and variable coverage. To demonstrate potential applications of this dataset, we focus on the short-term employment disruptions related to hurricanes during 1990-2020. The observed county-level employment changes in the initial month are small on average, though large employment losses (>30%) can occur after extreme storms. The overall small changes partly result from compensation among different employment sectors, which may obscure large, concentrated employment losses after hurricanes. Additional econometric analyses concur on the post-storm employment losses in hospitality and leisure but disagree on employment changes in the other industries. The dataset also enables data-driven analyses that highlight vulnerabilities such as pronounced employment losses related to Puerto Rico and rainy hurricanes. Furthermore, predictive modeling of short-term employment changes shows promising performance for service-providing industries and high-impact storms. In the examined cases, the nonlinear Random Forests model greatly outperforms the multiple linear regression model. The nonlinear model also suggests that more severe hurricane hazards projected by physical models may cause more extreme losses in US service-providing employment. Finally, we share our dataset and analytical code to facilitate the study and modeling of hurricane impacts in a changing climate.
Isidora Tourni, Georgios Grigorakis, Isidoros Marougkas
et al.
The advances of Generative AI models with interactive capabilities over the past few years offer unique opportunities for socioeconomic mobility. Their potential for scalability, accessibility, affordability, personalizing and convenience sets a first-class opportunity for poverty-stricken countries to adapt and modernize their educational order. As a result, this position paper makes the case for an educational policy framework that would succeed in this transformation by prioritizing vocational and technical training over academic education in sub-Saharan African countries. We highlight substantial applications of Large Language Models, tailor-made to their respective cultural background(s) and needs, that would reinforce their systemic decolonization. Lastly, we provide specific historical examples of diverse states successfully implementing such policies in the elementary steps of their socioeconomic transformation, in order to corroborate our proposal to sub-Saharan African countries to follow their lead.
Don-Roberts Emenonye, Anik Sarker, Alan T. Asbeck
et al.
This paper is the first to introduce the idea of using reconfigurable intelligent surfaces (RISs) as passive devices that measure the position and orientation of certain human body parts over time. In this paper, we investigate the possibility of utilizing the available geometric information provided by on-body RISs that reflect signals from an off-body transmitter to an off-body receiver for stroke rehabilitation. More specifically, we investigate the possibility of using on-body RISs to estimate the location information over time of upper limbs that may have been impaired due to stroke. This location information can help medical professionals to estimate the possibly time varying pose and obtain progress on the rehabilitation of the upper limbs. Our analysis is focused on two scenarios: i) after assessment exercises for stroke rehabilitation when the upper limbs are resting at predefined points in the rehabilitation center, and ii) during the assessment exercises. In the first scenario, we explore the possibility of upper limb orientation estimation by deriving the Fisher information matrix (FIM) under near-field and far-field propagation conditions. It is noteworthy that the FIM quantifies how accurately we can estimate location information from a signal, and any subsequent algorithm is bounded by a function of the FIM. Coming to our propagation assumptions, the difference between the near-field and far-field regimes lies in the curvature of the wavefront. In the near-field, a receiver experiences a spherical wavefront, whereas in the far-field, the wavefront is approximately linear. The threshold to be within the near-field can be on the order of $10 \text{ m}.$