Assistive Technology最新文献

This study evaluated the effectiveness of assistive technologies (ATs) through e-books in teaching practices aimed at enhancing language development among hard-of-hearing (HH) students. The study implemented an intervention consisting of four language aspects (phonemic awareness, writing, vocabulary, and reading comprehension) wherein the ATs' impacts on language development were assessed. Eighty HH students were divided into control and treatment groups and evaluated through pre- and post-tests. The results showed that the intervention led to significant changes in all four language aspects in both groups. Interestingly, the effect sizes were moderate in the control group but large in the treatment group, thus showing the efficiency and effectiveness of the developed intervention. These findings constitute useful evidence-based guidelines for implementing ATs to enhance teaching practices in the HH language setting.

As the global aging trend increases, dementia pressures families and society. Mobile apps that provide interventions and independence for people with dementia (PwD) may relieve this pressure. This study reviews mobile app-based interventions designed for use with PwD, focusing on the type, design, and evaluation of mobile apps. This study searched PubMed, Web of Science, SpringerLink, Taylor & Francis, and IEEE Xplore databases for mobile applications designed for people with disabilities and reported the evaluation results. This study aimed to find out what types of mobile apps developed for people with dementia were marketed during the COVID-19 pandemic, to find out what relevant studies have been done to evaluate mobile apps, and whether users have benefited. Twenty papers were eligible, covering four different intervention types and assessment methods. This review found that Serious games can improve the cognitive abilities of PwD and contribute to the mental recovery of patients. Recall therapy and musical mobile apps help PwD slow down memory loss. Personal life mobile apps are effective in assisting PwD to improve independent living.

Based on statistics from the WHO and the International Agency for the Prevention of Blindness, an estimated 43.3 million people have blindness and 295 million have moderate and severe vision impairment globally as of 2020, statistics expected to increase to 61 million and 474 million respectively by 2050, staggering numbers. Blindness and low vision (BLV) stultify many activities of daily living, as sight is beneficial to most functional tasks. Assistive technologies for persons with blindness and low vision (pBLV) consist of a wide range of aids that work in some way to enhance one's functioning and support independence. Although handheld and head-mounted approaches have been primary foci when building new platforms or devices to support function and mobility, this perspective reviews potential shortcomings of these form factors or embodiments and posits that a body-centered approach may overcome many of these limitations.

The Health App Review Tool (HART) is a novel assessment designed to match users with Alzheimer's disease or related dementias (ADRD) and caregivers to mobile applications that support health and wellness. The objectives of this study were to gather stakeholder feedback on the HART and then to implement revisions. Thirteen participants completed in-depth Think Aloud interviews. Participants shared qualitative feedback on each HART item. Participant feedback was analyzed via in-depth video-audio review. Feedback was implemented as actionable HART revisions. On average, the majority of participants rated items as "adequate"; however, qualitative findings indicated the need for improvement in conciseness, clarity, and understandability. Conciseness was addressed by combining related concepts into multi-items, clarity through the addition of specific examples, and understandability through improved verbiage. The HART has been refined from 106 items to 17 items through extensive revisions to the clarity, conciseness, and explanations provided throughout the assessment.

Autistic individuals face difficulties in finding and maintaining employment, and studies have shown that the job interview is often a significant barrier to obtaining employment. Prior computer-based job interview training interventions for autistic individuals have been associated with better interview outcomes. These previous interventions, however, do not leverage the use of multimodal data that could give insight into the emotional underpinnings of autistic individuals' challenges in job interviews. In this article, the authors present the design of a novel multimodal job interview training platform called CIRVR that simulates job interviews through spoken interaction and collects eye gaze, facial expressions, and physiological responses of the participants to understand their stress response and their affective state. Results from a feasibility study with 23 autistic participants who interacted with CIRVR are presented. In addition, qualitative feedback was gathered from stakeholders on visualizations of data on CIRVR's visualization tool called the Dashboard. The data gathered indicate the potential of CIRVR along with the Dashboard to be used in the creation of individualized job interview training of autistic individuals.

A current limitation in the development of robotic gait training interventions is understanding the factors that predict responses to treatment. The purpose of this study was to explore the application of an interpretable machine learning method, Bayesian Additive Regression Trees (BART), to identify factors influencing neuromuscular responses to a resistive ankle exoskeleton in individuals with cerebral palsy (CP). Eight individuals with CP (GMFCS levels I - III, ages 12-18 years) walked with a resistive ankle exoskeleton over seven visits while we measured soleus activation. A BART model was developed using a predictor set of kinematic, device, study, and participant metrics that were hypothesized to influence soleus activation. The model (R² = 0.94) found that kinematics had the largest influence on soleus activation, but the magnitude of exoskeleton resistance, amount of gait training practice with the device, and participant-level parameters also had substantial effects. To optimize neuromuscular engagement during exoskeleton training in individuals with CP, our analysis highlights the importance of monitoring the user's kinematic response, in particular, peak stance phase hip flexion and ankle dorsiflexion. We demonstrate the utility of machine learning techniques for enhancing our understanding of robotic gait training outcomes, seeking to improve the efficacy of future interventions.

This study aimed to investigate clinical stakeholders' acceptance of an immersive wheelchair simulator as a potential powered wheelchair skills training tool. Focus groups, conducted in four rehabilitation centers, were used to obtain a rich understanding of participants' experiences and beliefs. Then, a cross-sectional survey of the simulator acceptability for clinical practice was created. Twenty-three rehabilitation therapists and clinical program directors participated in the focus groups and thirty-three responded to the survey. Participants generally expressed that use of the simulator would be complementary to training in an actual powered wheelchair, and that it could be useful for challenging situations in rehabilitation centers (e.g. anxious clients; when there is uncertainty around their potential to drive a powered wheelchair; tasks that cannot be assessed in a real-life environment). They also provided suggestions to improve the simulator (e.g. more feedback during tasks; possibility of adjusting control settings such as speed and sensitivity; possibility of adding varied control interfaces). Feedback received from key stakeholders clearly indicated that the wheelchair simulator would be complementary to training provided in a real context of use. However, some important limitations must be addressed to improve the simulator and promote its adoption by clinical programs, therapists and clients.

The rise of 3D printing allows unprecedented customization of rehabilitation devices, and with an ever-expanding library of 3D printable (3DP) materials, the spectrum of attenable rehabilitation devices is likewise expanding. The current pilot study explores feasibility of using 3DP elastic materials to create dynamic hand orthoses for stroke survivors. A dynamic orthosis featuring a replaceable finger component was fabricated using 3DP elastic materials. Duplicates of the finger component were printed using different materials ranging from low stiffness (low elastic modulus) to relatively high stiffness (high elastic modulus). Five stroke survivors with predominantly moderate hand impairment were recruited to evaluate usability and impact of orthoses on upper extremity function and biomechanics. No significant differences in usability were found between 3D-printed orthoses and a commercial orthosis. Increases in stiffness of the 3DP material reduced pincer force (p = .0041) and the BBT score (p = .043). In comparison, the commercial orthosis did not reduce pincer force but may reduce BBT score to a degree that is clinically significant (p = .0002). While preliminary, these findings suggest that a dynamic orthosis is a feasible clinical application of 3DP elastic materials, and future study is warranted.