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This study was designed to evaluate the effects of a note-taking intervention using the Livescribe 4GB Echo SmartpenTM assistive technology on students’ notes and lecture comprehension, with an emphasis on content, vocabulary skills, and total words written. Students both with and without disabilities, including Specific Learning Disability, in 9th grade English Language Arts classes participated in this study. Students with disabilities may struggle with slower processing speed and poor working memory skills, which reduces the quality of their notes. Students in the experimental group were instructed how to use a note-taking intervention in conjunction with the smartpen assistive technology. This note-taking intervention was designed to assist students with disabilities to focus on taking their notes using the smartpen assistive technology, identify vocabulary words and definitions, amend their notes for errors or missed information, and write a brief summary of the important content. Results from the data analysis found statistical significance with special education students in the experimental group; they recorded more words in their notes, as well as an increase in word count and vocabulary words on the Immediate Free Recall (IFR) assessment. / Special Education

Yes / The development of many tools and technologies for people with visual impairment has become a major priority in the field of assistive technology research. However, many of these technology advancements have limitations in terms of the human aspects of the user experience (e.g., usability, learnability, and time to user adaptation) as well as difficulties in translating research prototypes into production. Also, there was no clear distinction between the assistive aids of adults and children, as well as between “partial impairment” and “total blindness”. As a result of these limitations, the produced aids have not gained much popularity and the intended users are still hesitant to utilise them. This paper presents a comprehensive review of substitutive interventions that aid in adapting to vision loss, centred on laboratory research studies to assess user-system interaction and system validation. Depending on the primary cueing feedback signal offered to the user, these technology aids are categorized as visual, haptics, or auditory-based aids. The context of use, cueing feedback signals, and participation of visually impaired people in the evaluation are all considered while discussing these aids. Based on the findings, a set of recommendations is suggested to assist the scientific community in addressing persisting challenges and restrictions faced by both the totally blind and partially sighted people.

The World Health Organization (WHO) estimates 488 million people worldwide suffer from a visual impairment and of these about 327 million have severe visual impairments. Some individuals with severe visual impairments can navigate and orient independently in well-known surroundings, but even for these people independent navigation and orientation are likely to be a challenge in unfamiliar places. To overcome these challenges, assistive technologies have been developed to support independent wayfinding tasks; however, those with severe visual impairments often experience frustration when they try to use assistive technologies since these technologies lack address the environmental factors that influence their independent wayfinding. This research developed and evaluated the efficacy of a framework called an environmental user interface (EUI). In particular, this research explored whether or not the proposed EUI framework was effective when used with user-centered design (UCD) to design a wayfinding system to capture environmental requirements, thus aiding those with severe visual impairments. Two studies, the first of which consisted of a requirements elicitation and the second usability testing, were conducted. The studies revealed that the EUI framework was indeed more effective than the conventional UCD design method alone in identifying environmental factors, and participants with severe visual impairments preferred to use the prototype designed using UCD and the EUI framework. The proposed EUI framework was found to be an effective way to enhance the design process as it played an important role in eliciting a greater number of environmental factors, and hence produced a device that was preferred by the users with visual impairments. Both prototypes influenced how well the wayfinding tasks were performed by the five participants with severe visual impairments, but the prototype implemented based on the requirements elicited by UCD and the EUI framework was much preferred by the participants. / Ph. D.

Yes / This paper outlines the remit of the UK Engineering and Physical Sciences Research Council KT-EQUAL (Knowledge Transfer for Extending Quality of Life for older and disabled people) programme. Case examples drawing on the range of activities undertaken by KT-EQUAL highlight where assistive technology developments have been facilitated, the value of network activities and an underpinning model of engagement and collaboration. Given an increasing emphasis on the impact of research the model and innovative approaches deployed by KT-EQUAL are even more crucial in future developments which aim to ensure that research can be used to benefit society.

This dissertation presents a comprehensive exploration and implementation of attention mechanisms and transformers on several healthcare-related and assistive applications. The overarching goal is to demonstrate successful implementation of the state-of-the-art approaches and provide validated models with their superior performance to inform future research and development. In Chapter 1, attention mechanisms are harnessed for the fine-grained classification of white blood cells (WBCs), showcasing their efficacy in medical diagnostics. The proposed multi-attention framework ensures accurate WBC subtype classification by capturing discriminative features from various layers, leading to superior performance compared to other existing approaches used in previous work. More importantly, the attention-based method showed consistently better results than without attention in all three backbone architectures tested (ResNet, XceptionNet and Efficient- Net). Chapter 2 introduces a self-supervised framework leveraging vision transformers for object detection, semantic and custom algorithms for collision prediction in application to assistive technology for visually impaired. In addition, Multimodal sensory feedback system was designed and fabricated to convey environmental information and potential collisions to the user for real-time navigation and grasping assistance. Chapter 3 presents implementation of transformer-based method for operation-relevant human activity recognition (HAR) and demonstrated its performance over other deep learning model, long-short term memory (LSTM). In addition, feature engineering was used (principal component analysis) to extract most discriminatory and representative motion features from the instrumented sensors, indicating that the joint angle features are more important than body segment orientations. Further, identification of a minimal number and placement of wearable sensors for use in real-world data collections and activity recognitions, addressing the critical gap found in the respective field to enhance the practicality and utility of wearable sensors for HAR. The premise and efficacy of attention-based mechanisms and transformers was confirmed through its demonstrated performance in classification accuracy as compared to LSTM. These research outcomes from three distinct applications of attention-based mechanisms and trans- formers and demonstrated performance over existing models and methods support their utility and applicability across various biomedical and human activity research fields. By sharing the custom designed model architectures, implementation methods, and resulting classification performance has direct impact in the related field by allowing direct adoption and implementation of the developed methods.

The current literature reports that oral language development is not a realistic goal for autistic cochlear implant users (ACI). This is curious, due to the general success of cochlear implants and the fact that many autistic individuals develop strong spoken language skills. Therefore, this study aimed to examine clinician and caregiver insights into spoken language development in the ACI population with the aim of elucidating the factors that influence the poor outcomes reported in the literature. We predicted that cochlear implant function would not be the limiting factor in ACI language development, but that device use and sensory atypicalities might have significant impacts. Participants were two speech-language pathologists (SLPs), six audiologists (AuDs), and one dually certified SLP/AuD. Additionally, six mothers and their ACI children participated in the study. All participants, excepting one ACI parent, took a survey and then participated in a 30–60-minute interview about their experience either caring for or working with ACIs and their insights into their language development. We also collected language samples in ACI participants. Quantitative analysis included computing descriptive and inferential statistics, where appropriate, concerning language abilities, sensory processing, anxiety, and survey responses regarding factors associated with cochlear implant (CI) use. We also engaged in qualitative thematic analysis of caregiver and clinician interviews. Quantitative and qualitative results were then integrated to triangulate findings. In important ways, our results are inconsistent with current literature concerning ACIs. For instance, caregiver and clinician statements, as well as quantitative results suggested that it was very possible for ACIs to develop spoken language, when given the right conditions. Qualitative themes that shed light on the factors important to positive language-related outcomes in ACIs included: a) finding (and advocating for) access to care; b) sensory processing difficulties; c) differentiating between autism and hearing loss, and the spectra of both conditions. One specific and novel finding showed that sensory profiles—especially sensory seeking versus sensory averse—may have a significant impact on a child’s oral language development following cochlear implantation and should be considered when counseling families on possible outcomes. These findings provide new insight into and concrete future directions for supporting the ACI population.

The "SmartCane+" thesis abstract outlines an initiative aimed at improving conventional walking canes into more intelligent, helpful devices for senior citizens. The incorporation of microcontrollers, which permits wireless communication and connection functions, is the primary innovation. With the use of MIT App Inventor, a unique mobile application and this technology, the cane can send its position to the user using Bluetooth. Because it can stop the cane from becoming lost, which is a regular problem for senior users, this function is especially beneficial. The SmartCane+ design places a strong focus on accessibility and cost. The idea maintains cheaper prices and simpler technology by choosing not to add complex hardware, which makes it easier for consumers to embrace and operate without feeling overwhelmed by complexity. By striking a mix between cutting-edge technology and intuitive operation, the design hopes to keep the cane a help rather than a burden. The results of the project indicate that the SmartCane+ effectively improves the safety and independence of senior users by ensuring the cane remains within a reachable distance and providing timely alerts. Testing showed reliable performance in various environments, although closed spaces introduced more variability. Future work will focus on enhancing the system’s accuracy, optimizing power consumption, and expanding compatibility with other mobile platforms.