Accuracy and Usability of Smartphone-Based Distance Estimation Approaches for Visual Assistive Technology Development.

Goal: Distance information is highly requested in assistive smartphone Apps by people who are blind or low vision (PBLV). However, current techniques have not been evaluated systematically for accuracy and usability. Methods: We tested five smartphone-based distance-estimation approaches in the image center and periphery at 1-3 meters, including machine learning (CoreML), infrared grid distortion (IR_self), light detection and ranging (LiDAR_back), and augmented reality room-tracking on the front (ARKit_self) and back-facing cameras (ARKit_back). Results: For accuracy in the image center, all approaches had <±2.5 cm average error, except CoreML which had ±5.2-6.2 cm average error at 2-3 meters. In the periphery, all approaches were more inaccurate, with CoreML and IR_self having the highest average errors at ±41 cm and ±32 cm respectively. For usability, CoreML fared favorably with the lowest central processing unit usage, second lowest battery usage, highest field-of-view, and no specialized sensor requirements. Conclusions: We provide key information that helps design reliable smartphone-based visual assistive technologies to enhance the functionality of PBLV.

Evidence-based practice education in physical medicine and rehabilitation residency programs: A Canadian national survey.

OBJECTIVE: The current extent and quality of evidence based practice (EBP) training for physiatrists is unclear at this time. Training of EBP is also available to residents in Canada. The extent, quality and impact of the training was explored. DESIGN: Cohort study Results: about half of the Canadian programs reported a formal EBP curriculum. The most frequently reported method of providing EBP education were resident participation in journal club. CONCLUSIONS: Despite the increasing integration of EBP into residency program education, there remains a critical lack of knowledge and skills for implementation of EBP into clinical practice among Canadian PM&R residency programs.

Wearables for persons with blindness and low vision: form factor matters.

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.

Commute Booster: A Mobile Application for First/Last Mile and Middle Mile Navigation Support for People With Blindness and Low Vision.

OBJECTIVE: People with blindness and low vision face substantial challenges when navigating both indoor and outdoor environments. While various solutions are available to facilitate travel to and from public transit hubs, there is a notable absence of solutions for navigating within transit hubs, often referred to as the "middle mile". Although research pilots have explored the middle mile journey, no solutions exist at scale, leaving a critical gap for commuters with disabilities. In this paper, we proposed a novel mobile application, Commute Booster, that offers full trip planning and real-time guidance inside the station. METHODS AND PROCEDURES: Our system consists of two key components: the general transit feed specification (GTFS) and optical character recognition (OCR). The GTFS dataset generates a comprehensive list of wayfinding signage within subway stations that users will encounter during their intended journey. The OCR functionality enables users to identify relevant navigation signs in their immediate surroundings. By seamlessly integrating these two components, Commute Booster provides real-time feedback to users regarding the presence or absence of relevant navigation signs within the field of view of their phone camera during their journey. RESULTS: As part of our technical validation process, we conducted tests at three subway stations in New York City. The sign detection achieved an impressive overall accuracy rate of 0.97. Additionally, the system exhibited a maximum detection range of 11 meters and supported an oblique angle of approximately 110 degrees for field of view detection. CONCLUSION: The Commute Booster mobile application relies on computer vision technology and does not require additional sensors or infrastructure. It holds tremendous promise in assisting individuals with blindness and low vision during their daily commutes. Clinical and Translational Impact Statement: Commute Booster translates the combination of OCR and GTFS into an assistive tool, which holds great promise for assisting people with blindness and low vision in their daily commute.

Training AI to Recognize Objects of Interest to the Blind and Low Vision Community.

Recent object detection models show promising advances in their architecture and performance, expanding potential applications for the benefit of persons with blindness or low vision (pBLV). However, object detection models are usually trained on generic data rather than datasets that focus on the needs of pBLV. Hence, for applications that locate objects of interest to pBLV, object detection models need to be trained specifically for this purpose. Informed by prior interviews, questionnaires, and Microsoft's ORBIT research, we identified thirty-five objects pertinent to pBLV. We employed this user-centric feedback to gather images of these objects from the Google Open Images V6 dataset. We subsequently trained a YOLOv5x model with this dataset to recognize these objects of interest. We demonstrate that the model can identify objects that previous generic models could not, such as those related to tasks of daily functioning - e.g., coffee mug, knife, fork, and glass. Crucially, we show that careful pruning of a dataset with severe class imbalances leads to a rapid, noticeable improvement in the overall performance of the model by two-fold, as measured using the mean average precision at the intersection over union thresholds from 0.5 to 0.95 (mAP50-95). Specifically, mAP50-95 improved from 0.14 to 0.36 on the seven least prevalent classes in the training dataset. Overall, we show that careful curation of training data can improve training speed and object detection outcomes. We show clear directions on effectively customizing training data to create models that focus on the desires and needs of pBLV.Clinical Relevance- This work demonstrated the benefits of developing assistive AI technology customized to individual users or the wider BLV community.

Implementing Remote Patient Monitoring of Physical Activity in Clinical Practice.

PURPOSE: Remote patient monitoring (RPM) is a tool for patients to share data collected outside of office visits. RPM uses technology and the digital transmission of data to inform clinician decision-making in patient care. Using RPM to track routine physical activity is feasible to operationalize, given contemporary consumer-grade devices that can sync to the electronic health record. Objective monitoring through RPM can be more reliable than patient self-reporting for physical activity. DESIGN AND METHODS: This article reports on four pilot studies that highlight the utility and practicality of RPM for physical activity monitoring in outpatient clinical care. Settings include endocrinology, cardiology, neurology, and pulmonology settings. RESULTS: The four pilot use cases discussed demonstrate how RPM is utilized to monitor physical activity, a shift that has broad implications for prediction, prevention, diagnosis, and management of chronic disease and rehabilitation progress. CLINICAL RELEVANCE: If RPM for physical activity is to be expanded, it will be important to consider that certain populations may face challenges when accessing digital health services. CONCLUSION: RPM technology provides an opportunity for clinicians to obtain objective feedback for monitoring progress of patients in rehabilitation settings. Nurses working in rehabilitation settings may need to provide additional patient education and support to improve uptake.

Macro-Fiber Composite-Based Tactors for Haptic Applications.

Haptic technology is a critical component of human-computer interfaces. Traditional haptic actuators are often unable to provide the broad frequency range and latency that is required in many advanced applications. To address this problem, we propose a new type of tactor based on macro-fiber composites (MFCs), composites of piezoelectric fibers. We propose a physics-based model for the actuation of the tactors, calibrated and validated through experiments. As our tactors are intended for haptic applications, we consider the role of skin on their response, an aspect seldom analyzed in the literature. In our experiments, we simulate the presence of the skin with a rubber membrane in contact with the tactor, with varying pre-stretch, mimicking different indentations of the tactor on the skin. The MFC-based tactor can always generate vibration amplitudes higher than skin discrimination thresholds, over the range of frequencies of interest for haptics, with a latency much smaller than traditional actuators. We theoretically investigate the effect of the skin on tactor vibrations, highlighting the individual roles of skin stiffness and damping and their combined effect across a series of pre-stretches. Our tactor shows promise in haptic applications, including assistive technologies and real-time feedback systems for training, safety, and monitoring.

Disparities in breast cancer among patients with disabilities: care gaps, accessibility, and best practices.

Pronounced disparities exist in detecting and treating breast cancer in women with disabilities, leading to cancer detection at advanced stages. This paper provides an overview of disparities for women with disabilities related to breast cancer screening and care, primarily focusing on clinically significant mobility disabilities. Current care gaps include screening barriers related to accessibility and inequitable treatment options, with race and ethnicity, socioeconomic status, geographic location, and disability severity factors mediating the disparities for this population. The reasons for these disparities are myriad and stem from both system-level deficiencies and individual-level clinician bias. Although structural changes are warranted, individual healthcare professionals must also be incorporated into the requisite change. Intersectionality is critical to disparities and inequities and should be central to any discussion of strategies for improving care for people with disabilities, many of whom have intersectional identities. Efforts to reduce screening rate disparities for breast cancer in women with mobility-related disabilities should start with improving accessibility through removing structural barriers, establishing comprehensive accessibility standards, and addressing healthcare professional bias. Future interventional studies are needed to implement and assess the value of programs to improve breast cancer screening rates in women with disabilities. Increasing the representation of women with disabilities in clinical trials may provide another avenue for reducing treatment disparities because these trials often provide breakthrough treatment to women with cancer diagnosed at later stages. Ultimately, attention to the specific needs of patients with disabilities should be improved across the United States to promote inclusive and effective cancer screening and treatment.

Virtual reality as a means to explore assistive technologies for the visually impaired.

Visual impairment represents a significant health and economic burden affecting 596 million globally. The incidence of visual impairment is expected to double by 2050 as our population ages. Independent navigation is challenging for persons with visual impairment, as they often rely on non-visual sensory signals to find the optimal route. In this context, electronic travel aids are promising solutions that can be used for obstacle detection and/or route guidance. However, electronic travel aids have limitations such as low uptake and limited training that restrict their widespread use. Here, we present a virtual reality platform for testing, refining, and training with electronic travel aids. We demonstrate the viability on an electronic travel aid developed in-house, consist of a wearable haptic feedback device. We designed an experiment in which participants donned the electronic travel aid and performed a virtual task while experiencing a simulation of three different visual impairments: age-related macular degeneration, diabetic retinopathy, and glaucoma. Our experiments indicate that our electronic travel aid significantly improves the completion time for all the three visual impairments and reduces the number of collisions for diabetic retinopathy and glaucoma. Overall, the combination of virtual reality and electronic travel aid may have a beneficial role on mobility rehabilitation of persons with visual impairment, by allowing early-phase testing of electronic travel aid prototypes in safe, realistic, and controllable settings.

Art therapy as a comprehensive complementary treatment for Parkinson's disease.

Introduction: Parkinson's disease (PD) is the second most prevalent neurodegenerative disease. Complementary and alternative therapies are increasingly utilized to address its complex multisystem symptomatology. Art therapy involves motoric action and visuospatial processing while promoting broad biopsychosocial wellness. The process involves hedonic absorption, which provides an escape from otherwise persistent and cumulative PD symptoms, refreshing internal resources. It involves the expression in nonverbal form of multilayered psychological and somatic phenomena; once these are externalized in a symbolic arts medium, they can be explored, understood, integrated, and reorganized through verbal dialogue, effecting relief and positive change. Methods: 42 participants with mild to moderate PD were treated with 20 sessions of group art therapy. They were assessed before and after therapy with a novel arts-based instrument developed to match the treatment modality for maximum sensitivity. The House-Tree-Person PD Scale (HTP-PDS) assesses motoric and visuospatial processing-core PD symptoms-as well as cognition (thought and logic), affect/mood, motivation, self (including body-image, self-image, and self- efficacy), interpersonal functioning, creativity, and overall level of functioning. It was hypothesized that art therapy will ameliorate core PD symptoms and that this will correlate with improvements in all other variables. Results: HTP-PDS scores across all symptoms and variables improved significantly, though causality among variables was indeterminate. Discussion: Art therapy is a clinically efficacious complementary treatment for PD. Further research is warranted to disentangle causal pathways among the aforementioned variables, and additionally, to isolate and examine the multiple, discrete healing mechanisms believed to operate simultaneously in art therapy.

A Smart Service System for Spatial Intelligence and Onboard Navigation for Individuals with Visual Impairment (VIS4ION Thailand): study protocol of a randomized controlled trial of visually impaired students at the Ratchasuda College, Thailand.

BACKGROUND: Blind/low vision (BLV) severely limits information about our three-dimensional world, leading to poor spatial cognition and impaired navigation. BLV engenders mobility losses, debility, illness, and premature mortality. These mobility losses have been associated with unemployment and severe compromises in quality of life. VI not only eviscerates mobility and safety but also, creates barriers to inclusive higher education. Although true in almost every high-income country, these startling facts are even more severe in low- and middle-income countries, such as Thailand. We aim to use VIS4ION (Visually Impaired Smart Service System for Spatial Intelligence and Onboard Navigation), an advanced wearable technology, to enable real-time access to microservices, providing a potential solution to close this gap and deliver consistent and reliable access to critical spatial information needed for mobility and orientation during navigation. METHODS: We are leveraging 3D reconstruction and semantic segmentation techniques to create a digital twin of the campus that houses Mahidol University's disability college. We will do cross-over randomization, and two groups of randomized VI students will deploy this augmented platform in two phases: a passive phase, during which the wearable will only record location, and an active phase, in which end users receive orientation cueing during location recording. A group will perform the active phase first, then the passive, and the other group will experiment reciprocally. We will assess for acceptability, appropriateness, and feasibility, focusing on experiences with VIS4ION. In addition, we will test another cohort of students for navigational, health, and well-being improvements, comparing weeks 1 to 4. We will also conduct a process evaluation according to the Saunders Framework. Finally, we will extend our computer vision and digital twinning technique to a 12-block spatial grid in Bangkok, providing aid in a more complex environment. DISCUSSION: Although electronic navigation aids seem like an attractive solution, there are several barriers to their use; chief among them is their dependence on either environmental (sensor-based) infrastructure or WiFi/cell "connectivity" infrastructure or both. These barriers limit their widespread adoption, particularly in low-and-middle-income countries. Here we propose a navigation solution that operates independently of both environmental and Wi-Fi/cell infrastructure. We predict the proposed platform supports spatial cognition in BLV populations, augmenting personal freedom and agency, and promoting health and well-being. TRIAL REGISTRATION: ClinicalTrials.gov under the identifier: NCT03174314, Registered 2017.06.02.

Methodological Issues Relevant to Blinding in Physical Medicine and Rehabilitation Research.

ABSTRACT: Blinding in research is important, and the field of physical medicine and rehabilitation poses special consideration owing to the patient populations and treatment methodologies used. Historically, blinding has been increasingly relevant to conducting good-quality research. The main reason to blind is to reduce bias. There are several strategies to blinding. At times, when blinding is not possible, alternatives to blinding include sham control and description of study and control groups. Illustrative examples of blinding used in physical medicine and rehabilitation research are described in this article, along with how to assess success and fidelity of blinding.

The BLV App Arcade: a new curated repository and evaluation rubric for mobile applications supporting blindness and low vision.

PURPOSE: Visual impairment-related disabilities have become increasingly pervasive. Current reports estimate a total of 36 million persons with blindness and 217 million persons with moderate to severe visual impairment worldwide. Assistive technologies (AT), including text-to-speech software, navigational/spatial guides, and object recognition tools have the capacity to improve the lives of people with blindness and low vision. However, access to such AT is constrained by high costs and implementation barriers. More recently, expansive growth in mobile computing has enabled many technologies to be translated into mobile applications. As a result, a marketplace of accessibility apps has become available, yet no framework exists to facilitate navigation of this voluminous space. MATERIALS AND METHODS: We developed the BLV (Blind and Low Vision) App Arcade: a fun, engaging, and searchable curated repository of app AT broken down into 11 categories spanning a wide variety of themes from entertainment to navigation. Additionally, a standardized evaluation metric was formalized to assess each app in five key dimensions: reputability, privacy, data sharing, effectiveness, and ease of use/accessibility. In this paper, we describe the methodological approaches, considerations, and metrics used to find, store and score mobile applications. CONCLUSION: The development of a comprehensive and standardized database of apps with a scoring rubric has the potential to increase access to reputable tools for the visually impaired community, especially for those in low- and middle-income demographics, who may have access to mobile devices but otherwise have limited access to more expensive technologies or services.

A wide array of assistive mobile applications now serve as low cost, convenient, and effective alternatives to standard tools in the rehabilitation domain.Given an extensive (and growing) marketplace of assistive apps, we highlight the importance of developing standardized evaluation frameworks that serve to assess the merit, functionality, and accessibility of tools in respective rehabilitation fields.To provide an introduction to a novel resource accessible to the public to exhibit verified and reliable assistive apps for the visually impaired community, especially for those in low- and middle-income demographics who may not have access to common technologies and services.

Enhanced cognitive interference during visuomotor tasks may cause eye-hand dyscoordination.

In complex visuomotor tasks, such as cooking, people make many saccades to continuously search for items before and during reaching movements. These tasks require cognitive resources, such as short-term memory and task-switching. Cognitive load may impact limb motor performance by increasing demands on mental processes, but mechanisms remain unclear. The Trail-Making Tests, in which participants sequentially search for and make reaching movements to 25 targets, consist of a simple numeric variant (Trails-A) and a cognitively challenging variant that requires alphanumeric switching (Trails-B). We have previously shown that stroke survivors and age-matched controls make many more saccades in Trails-B, and those increases in saccades are associated with decreases in speed and smoothness of reaching movements. However, it remains unclear how patients with neurological injuries, e.g., stroke, manage progressive increases in cognitive load during visuomotor tasks, such as the Trail-Making Tests. As Trails-B trial progresses, switching between numbers and letters leads to progressive increases in cognitive load. Here, we show that stroke survivors with damage to frontoparietal areas and age-matched controls made more saccades and had longer fixations as they progressed through the 25 alphanumeric targets in Trails-B. Furthermore, when stroke survivors made saccades during reaching movements in Trails-B, their movement speed slowed down significantly. Thus, damage to frontoparietal areas serving cognitive motor functions may cause interference between oculomotor, visual, and limb motor functions, which could lead to significant disruptions in activities of daily living. These findings augment our understanding of the mechanisms that underpin cognitive-motor interference during complex visuomotor tasks.

The Utopia of Disability Inclusion in the Rehabilitation Sciences: An Insider's Perspective.

The inclusion of people with disabilities has historically been, and continues to be, challenging work. In the health professions, the practice of inclusion should promote and advance the dissemination of efforts to decrease the impact of societal and physical barriers on the lives of people with disability, as well as promote innovative approaches to effectively foster an inclusive society. In addition to a focus on concepts such as the intact abilities of people with disabilities and the facilitation of community participation, an important shift in inclusion-related research requires listening to the lived experience of individuals with disabilities. Listening to their lived experiences and including the valuable insights gleaned from their insider's perspective can enrich efforts to evaluate clinical and educational programs, define population needs, and set research agendas and rehabilitation goals. Building on seminal work from Tamara Dembo, Beatrice Wright, and Margaret Brown, this communication from the Disability Representation Task Force at the American Congress of Rehabilitation Medicine also explores how healthcare providers living with a disability can make a significant contribution to rehabilitation treatment by analyzing how their own experience applies to clinical practice.

UNav: An Infrastructure-Independent Vision-Based Navigation System for People with Blindness and Low Vision.

Vision-based localization approaches now underpin newly emerging navigation pipelines for myriad use cases, from robotics to assistive technologies. Compared to sensor-based solutions, vision-based localization does not require pre-installed sensor infrastructure, which is costly, time-consuming, and/or often infeasible at scale. Herein, we propose a novel vision-based localization pipeline for a specific use case: navigation support for end users with blindness and low vision. Given a query image taken by an end user on a mobile application, the pipeline leverages a visual place recognition (VPR) algorithm to find similar images in a reference image database of the target space. The geolocations of these similar images are utilized in a downstream task that employs a weighted-average method to estimate the end user's location. Another downstream task utilizes the perspective-n-point (PnP) algorithm to estimate the end user's direction by exploiting the 2D-3D point correspondences between the query image and the 3D environment, as extracted from matched images in the database. Additionally, this system implements Dijkstra's algorithm to calculate a shortest path based on a navigable map that includes the trip origin and destination. The topometric map used for localization and navigation is built using a customized graphical user interface that projects a 3D reconstructed sparse map, built from a sequence of images, to the corresponding a priori 2D floor plan. Sequential images used for map construction can be collected in a pre-mapping step or scavenged through public databases/citizen science. The end-to-end system can be installed on any internet-accessible device with a camera that hosts a custom mobile application. For evaluation purposes, mapping and localization were tested in a complex hospital environment. The evaluation results demonstrate that our system can achieve localization with an average error of less than 1 m without knowledge of the camera's intrinsic parameters, such as focal length.

MICK (Mobile Integrated Cognitive Kit) app: Feasibility of an accessible tablet-based rapid picture and number naming task for concussion assessment in a division 1 college football cohort.

Although visual symptoms are common following concussion, quantitative measures of visual function are missing from concussion evaluation protocols on the athletic sideline. For the past half century, rapid automatized naming (RAN) tasks have demonstrated promise as quantitative neuro-visual assessment tools in the setting of head trauma and other disorders but have been previously limited in accessibility and scalability. The Mobile Interactive Cognitive Kit (MICK) App is a digital RAN test that can be downloaded on most mobile devices and can therefore provide a quantitative measure of visual function anywhere, including the athletic sideline. This investigation examined the feasibility of MICK App administration in a cohort of Division 1 college football players. Participants (n = 82) from a National Collegiate Athletic Association (NCAA) Division 1 football team underwent baseline testing on the MICK app. Total completion times of RAN tests on the MICK app were recorded; magnitudes of best time scores and between-trial learning effects were determined by paired t-test. Consistent with most timed performance measures, there were significant learning effects between the two baseline trials for both RAN tasks on the MICK app: Mobile Universal Lexicon Evaluation System (MULES) (p < 0.001, paired t-test, mean improvement 13.3 s) and the Staggered Uneven Number (SUN) (p < 0.001, mean improvement 3.3 s). This study demonstrated that the MICK App can be feasibly administered in the setting of pre-season baseline testing in a Division I environment. These data provide a foundation for post-injury sideline testing that will include comparison to baseline in the setting of concussion.