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

Yang, Anbang; Beheshti, Mahya; Hudson, Todd E; Vedanthan, Rajesh; Riewpaiboon, Wachara; Mongkolwat, Pattanasak; Feng, Chen; Rizzo, John-Ross
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.
PMCID:9696753
PMID: 36433501
ISSN: 1424-8220
CID: 5382902

Accuracy of clinical versus oculographic detection of pathological saccadic slowing

Grossman, Scott N; Calix, Rachel; Hudson, Todd; Rizzo, John Ross; Selesnick, Ivan; Frucht, Steven; Galetta, Steven L; Balcer, Laura J; Rucker, Janet C
Saccadic slowing as a component of supranuclear saccadic gaze palsy is an important diagnostic sign in multiple neurologic conditions, including degenerative, inflammatory, genetic, or ischemic lesions affecting brainstem structures responsible for saccadic generation. Little attention has been given to the accuracy with which clinicians correctly identify saccadic slowing. We compared clinician (n = 19) judgements of horizontal and vertical saccade speed on video recordings of saccades (from 9 patients with slow saccades, 3 healthy controls) to objective saccade peak velocity measurements from infrared oculographic recordings. Clinician groups included neurology residents, general neurologists, and fellowship-trained neuro-ophthalmologists. Saccades with normal peak velocities on infrared recordings were correctly identified as normal in 57% (91/171; 171 = 9 videos × 19 clinicians) of clinician decisions; saccades determined to be slow on infrared recordings were correctly identified as slow in 84% (224/266; 266 = 14 videos × 19 clinicians) of clinician decisions. Vertical saccades were correctly identified as slow more often than horizontal saccades (94% versus 74% of decisions). No significant differences were identified between clinician training levels. Reliable differentiation between normal and slow saccades is clinically challenging; clinical performance is most accurate for detection of vertical saccade slowing. Quantitative analysis of saccade peak velocities enhances accurate detection and is likely to be especially useful for detection of mild saccadic slowing.
PMID: 36183516
ISSN: 1878-5883
CID: 5359142

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

Bell, Carter A; Rice, Lionel; Balcer, Marc J; Pearson, Randolph; Penning, Brett; Alexander, Aubrey; Roskelly, Jensyn; Nogle, Sally; Tomczyk, Chris P; Tracey, Allie J; Loftin, Megan C; Pollard-McGrandy, Alyssa M; Zynda, Aaron J; Covassin, Tracey; Park, George; Rizzo, John-Ross; Hudson, Todd; Rucker, Janet C; Galetta, Steven L; Balcer, Laura; Kaufman, David I; Grossman, Scott N
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.
PMID: 36208585
ISSN: 1878-5883
CID: 5351822

Real-Time Loosely Coupled 3DMA GNSS/Doppler Measurements Integration Using a Graph Optimization and Its Performance Assessments in Urban Canyons of New York

Ng, Hoi-Fung; Hsu, Li-Ta; Lee, Max Jwo Lem; Feng, Junchi; Naeimi, Tahereh; Beheshti, Mahya; Rizzo, John-Ross
Smart health applications have received significant attention in recent years. Novel applications hold significant promise to overcome many of the inconveniences faced by persons with disabilities throughout daily living. For people with blindness and low vision (BLV), environmental perception is compromised, creating myriad difficulties. Precise localization is still a gap in the field and is critical to safe navigation. Conventional GNSS positioning cannot provide satisfactory performance in urban canyons. 3D mapping-aided (3DMA) GNSS may serve as an urban GNSS solution, since the availability of 3D city models has widely increased. As a result, this study developed a real-time 3DMA GNSS-positioning system based on state-of-the-art 3DMA GNSS algorithms. Shadow matching was integrated with likelihood-based ranging 3DMA GNSS, generating positioning hypothesis candidates. To increase robustness, the 3DMA GNSS solution was then optimized with Doppler measurements using factor graph optimization (FGO) in a loosely-coupled fashion. This study also evaluated positioning performance using an advanced wearable system's recorded data in New York City. The real-time forward-processed FGO can provide a root-mean-square error (RMSE) of about 21 m. The RMSE drops to 16 m when the data is post-processed with FGO in a combined direction. Overall results show that the proposed loosely-coupled 3DMA FGO algorithm can provide a better and more robust positioning performance for the multi-sensor integration approach used by this wearable for persons with BLV.
PMCID:9460112
PMID: 36080991
ISSN: 1424-8220
CID: 5335992

Evidence-Based Medicine Training in US-based Physiatry Residency Programs

Annaswamy, Thiru M; Rizzo, John-Ross; Schnappinger, Amy; Morgenroth, David C; Engkasan, Julia Patrick; Ilieva, Elena; Arnold, W David; Boninger, Mike; Bean, Allison C; Cirstea, Carmen M; Dicianno, Brad E; Fredericson, Michael; Jayabalan, Prakash; Raghavan, Preeti; Sawaki, Lumy; Suri, Pradeep; Suskauer, Stacy J; Wang, Qing Mei; Hosseini, Maryam; Case, Christina; Whyte, John; Paganoni, Sabrina
ABSTRACT/UNASSIGNED:While the physiatric community increasingly embraces Evidence-Based Medicine (EBM), the current state of EBM training for trainees in physiatry is unclear. The purpose of this article is to report the results of the Association of Academic Physiatrists (AAP)'s surveys of physiatry residency programs in the United States (US), to discuss the implications of their findings, and to better delineate the 'baseline' upon which sound and clear recommendations for systematic EBM training can be made. The two AAP surveys of US physiatry residency programs reveal that most survey respondents report that they include EBM training in their programs that covers the five recommended steps of EBM core competencies. However, while most respondents reported using traditional pedagogical methods of training such as journal club, very few reported that their EBM training used a structured and systematic approach. Future work is needed to support and facilitate physiatry residency programs interested in adopting structured EBM training curricula that include recommended EBM core-competencies and the evaluation of their impact.
PMID: 33852491
ISSN: 1537-7385
CID: 4871172

Let's Write a Manuscript - A Primer with Tips & Tricks for Penning an Original Article

Ozcakar, Levent; Rizzo, John-Ross; Franchignoni, Franco; Negrini, Stefano; Frontera, Walter R
A group of international researchers and editors summarize how (promptly and easily) an original manuscript can be written using certain tips and tricks. In other words, the authors guide novice colleagues with minimal experience using simple hints and straightforward advice in scholarly publishing. The main body of an original article is composed of four parts: Introduction, Methods, Results and Discussion (the IMRaD format). We make recommendations about how to write these sections. We also make suggestions regarding the title, abstract, key words, and references. In addition, we underline the importance of carefully reading and following both general recommendations for the conduct, reporting, editing, and publication of scholarly papers. Specific guidelines are reviewed for improving clarity, accuracy and transparency, from protocol registration and ethical approval to submission issues, inclusive of rehabilitation specificities. A thorough review of the mission and instructions of the journals under consideration is critical inclusive of manuscript preparation guidelines such as word limits of main text, limits in number and style of references, tables and figures, format, checklist, and other specific instructions. Finally, each and every sentence should be iteratively revised for grammar, style, and clarity.
PMID: 34297520
ISSN: 1537-7385
CID: 5087842

The MICK (Mobile integrated cognitive kit) app: Digital rapid automatized naming for visual assessment across the spectrum of neurological disorders

Park, George; Balcer, Marc J; Hasanaj, Lisena; Joseph, Binu; Kenney, Rachel; Hudson, Todd; Rizzo, John-Ross; Rucker, Janet C; Galetta, Steven L; Balcer, Laura J; Grossman, Scott N
OBJECTIVE:Rapid automatized naming (RAN) tasks have been utilized for decades to evaluate neurological conditions. Time scores for the Mobile Universal Lexicon Evaluation System (MULES, rapid picture naming) and Staggered Uneven Number (SUN, rapid number naming) are prolonged (worse) with concussion, mild cognitive impairment, multiple sclerosis and Parkinson's disease. The purpose of this investigation was to compare paper/pencil versions of MULES and SUN with a new digitized format, the MICK app. METHODS:Participants (healthy office-based volunteers, professional women's hockey players), completed two trials of the MULES and SUN tests on both platforms (tablet, paper/pencil). The order of presentation of the testing platforms was randomized. Between-platform variability was calculated using the two-way random-effects intraclass correlation coefficient (ICC). RESULTS:Among 59 participants (median age 32, range 22-83), no significant differences were observed for comparisons of mean best scores for the paper/pencil versus MICK app platforms, counterbalanced for order of administration (P = 0.45 for MULES, P = 0.50 for SUN, linear regression). ICCs for agreement between the MICK and paper/pencil tests were 0.92 (95% CI 0.86, 0.95) for MULES and 0.94 (95% CI 0.89, 0.96) for SUN, representing excellent levels of agreement. Inter-platform differences did not vary systematically across the range of average best time score for either test. CONCLUSION/CONCLUSIONS:The MICK app for digital administration of MULES and SUN demonstrates excellent agreement of time scores with paper/pencil testing. The computerized app allows for greater accessibility and scalability in neurological diseases, inclusive of remote monitoring. Sideline testing for sports-related concussion may also benefit from this technology.
PMID: 35038658
ISSN: 1878-5883
CID: 5131412

Learning to use electronic travel AIDS for visually impaired in virtual reality

Chapter by: Ricci, Fabiana Sofia; Boldini, Alain; Rizzo, John Ross; Porfiri, Maurizio
in: Proceedings of SPIE - The International Society for Optical Engineering by
[S.l.] : SPIE, 2022
pp. ?-?
ISBN: 9781510649651
CID: 5315132

A virtual reality platform to simulate orientation and mobility training for the visually impaired

Ricci, Fabiana Sofia; Boldini, Alain; Beheshti, Mahya; Rizzo, John Ross; Porfiri, Maurizio
Blindness and low vision are an urgent, steadily increasing public health concern. One of the most dramatic consequences of the debilitating conditions that cause visual impairment (VI) is the loss of mobility. Immobility is a grave impediment to quality of life. Orientation and mobility (O&M) training is a profession specific to VI that teaches safe, efficient, and effective travel skills to persons of all ages and in all types of environments. However, the lack of standardized best practices for objective assessment of performance and the exposure of trainees to harm during training are key hurdles for O&M education success. To partially mitigate these drawbacks, we propose a virtual reality platform that can support O&M trainers in the evaluation and refinement of O&M practice, help O&M trainees learn new O&M techniques in a completely safe, yet realistic, environment, and raise awareness for VI in the general public. The proposed platform is tested with a proof-of-concept experiment that evaluates the clinical utility of a custom VI simulation, the immersivity of the virtual reality experience"”a crucial attribute for training and educational purposes"”and participants"™ disability awareness and gained knowledge about the challenges faced by persons with VI in their daily life. The first concept is tested by assessing participants"™ performance in virtual reality-based wayfinding tasks while the second and third are tested through a series of dedicated questionnaires.
SCOPUS:85138042624
ISSN: 1359-4338
CID: 5330872

Deep Augmentation for Electrode Shift Compensation in Transient High-density sEMG: Towards Application in Neurorobotics

Chapter by: Sun, Tianyun; Libby, Jacqueline; Rizzo, John Ross; Atashzar, S. Farokh
in: IEEE International Conference on Intelligent Robots and Systems by
[S.l.] : Institute of Electrical and Electronics Engineers Inc., 2022
pp. 6148-6153
ISBN: 9781665479271
CID: 5408842