Proof of Concept for an "eyePhone" App to Measure Video Head Impulses

Leveraging Technology for Vestibular Assessment and Rehabilitation in the Operational Environment: A Scoping Review

INTRODUCTION

The vestibular system, essential for gaze and postural stability, can be damaged by threats on the battlefield. Technology can aid in vestibular assessment and rehabilitation; however, not all devices are conducive to the delivery of healthcare in an austere setting. This scoping review aimed to examine the literature for technologies that can be utilized for vestibular assessment and rehabilitation in operational environments.

MATERIALS AND METHODS

A comprehensive search of PubMed was performed. Articles were included if they related to central or peripheral vestibular disorders, addressed assessment or rehabilitation, leveraged technology, and were written in English. Articles were excluded if they discussed health conditions other than vestibular disorders, focused on devices or techniques not conducive to the operational environment, or were written in a language other than English.

RESULTS

Our search strategy yielded 32 articles: 8 articles met our inclusion and exclusion criteria whereas the other 24 articles were rejected.

DISCUSSION

There is untapped potential for leveraging technology for vestibular assessment and rehabilitation in the operational environment. Few studies were found in the peer-reviewed literature that described the application of technology to improve the identification of central and/or peripheral vestibular system impairments; triage of acutely injured patients; diagnosis; delivery and monitoring of rehabilitation; and determination of readiness for return to duty.

CONCLUSIONS

This scoping review highlighted technology for vestibular assessment and rehabilitation feasible for use in an austere setting. Such technology may be leveraged for prevention; monitoring exposure to mechanisms of injury; vestibular-ocular motor evaluation; assessment, treatment, and monitoring of rehabilitation progress; and return-to-duty determination after vestibular injury.

FUTURE DIRECTIONS

The future of vestibular assessment and rehabilitation may be shaped by austere manufacturing and 3D printing; artificial intelligence; drug delivery in combination with vestibular implantation; organ-on-chip and organoids; cell and gene therapy; and bioprinting.

Quantifying Induced Nystagmus Using a Smartphone Eye Tracking Application (EyePhone)

BACKGROUND

There are ≈5 million annual dizziness visits to US emergency departments, of which vestibular strokes account for over 250 000. The head impulse, nystagmus, and test of skew eye examination can accurately distinguish vestibular strokes from peripheral dizziness. However, the eye-movement signs are subtle, and lack of familiarity and difficulty with recognition of abnormal eye movements are significant barriers to widespread emergency department use. To break this barrier, we sought to assess the accuracy of EyePhone, our smartphone eye-tracking application, for quantifying nystagmus.

METHODS AND RESULTS

We prospectively enrolled healthy volunteers and recorded the velocity of induced nystagmus using a smartphone eye-tracking application (EyePhone) and then compared the results with video oculography (VOG). Following a calibration protocol, the participants viewed optokinetic stimuli with incremental velocities (2-12 degrees/s) in 4 directions. We extracted slow phase velocities from EyePhone data in each direction and compared them with the corresponding slow phase velocities obtained by the VOG. Furthermore, we calculated the area under the receiver operating characteristic curve for nystagmus detection by EyePhone. We enrolled 10 volunteers (90% men) with an average age of 30.2±6 years. EyePhone-recorded slow phase velocities highly correlated with the VOG recordings (r=0.98 for horizontal and r=0.94 for vertical). The calibration significantly increased the slope of linear regression for horizontal and vertical slow phase velocities. Evaluating the EyePhone's performance using VOG data with a 2 degrees/s threshold showed an area under the receiver operating characteristic curve of 0.87 for horizontal and vertical nystagmus detection.

CONCLUSIONS

We demonstrated that EyePhone could accurately detect and quantify optokinetic nystagmus, similar to the VOG goggles.

Vestibulo-Ocular Reflex Suppression: Clinical Relevance and Assessment in the Digital Age

Background

Visual acuity and image stability are crucial for daily activities, particularly during head motion. The vestibulo-ocular reflex (VOR) and its suppression (VORS) support stable fixation of objects of interest. The VOR drives a reflexive eye movement to counter retinal slip of a stable target during head motion. In contrast, VORS inhibits this countermovement when the target stimulus is in motion. The VORS allows for object fixation when it aligns with the direction of the head's movement, or when an object within or outside the peripheral vision needs to be focused upon.

Summary

Deficits of the VORS have been linked to age-related diseases such as balance deficits associated with an increased fall risk. Therefore, the accurate assessment of the VORS is of particular clinical relevance. However, current clinical assessment methods for VORS are mainly qualitative and not sufficiently standardised. Recent advances in digital health technology, such as smartphone-based videooculography, offer a promising alternative for assessing VORS in a more accessible, efficient, and quantitative manner. Moreover, integrating mobile eye-tracking technology with virtual reality environments allows for the implementation of controlled VORS assessments with different visual inputs. These assessment approaches allow the extraction of novel parameters with potential pathomechanistic and clinical relevance.

Key Messages

We argue that researchers and clinicians can obtain a more nuanced understanding of this ocular stabilisation reflex and its associated pathologies by harnessing digital health technology for VORS assessment. Further research is warranted to explore the technologies' full potential and utility in clinical practice.

Self-Recording of Eye Movements in Amyotrophic Lateral Sclerosis Patients Using a Smartphone Eye-Tracking App

Introduction

Amyotrophic lateral sclerosis (ALS) can affect various eye movements, making eye tracking a potential means for disease monitoring. In this study, we evaluated the feasibility of ALS patients self-recording their eye movements using the "EyePhone," a smartphone eye-tracking application.

Methods

We prospectively enrolled ten participants and provided them with an iPhone equipped with the EyePhone app and a PowerPoint presentation with step-by-step recording instructions. The goal was for the participants to record their eye movements (saccades and smooth pursuit) without the help of the study team. Afterward, a trained physician administered the same tests using video-oculography (VOG) goggles and asked the participants to complete a questionnaire regarding their self-recording experience.

Results

All participants successfully completed the self-recording process without assistance from the study team. Questionnaire data indicated that participants viewed self-recording with EyePhone favorably, considering it easy and comfortable. Moreover, 70% indicated that they prefer self-recording to being recorded by VOG goggles.

Conclusion

With proper instruction, ALS patients can effectively use the EyePhone to record their eye movements, potentially even in a home environment. These results demonstrate the potential for smartphone eye-tracking technology as a viable and self-administered tool for monitoring disease progression in ALS, reducing the need for frequent clinic visits.

Smartphone-Assisted Medical Care for Vestibular Dysfunction as a Telehealth Strategy for Digital Therapy Beyond COVID-19: Scoping Review

BACKGROUND

Dizziness and vertigo can be caused by various factors, such as peripheral vestibular and central disorders. Although consultations with specialists are advisable when necessary, patients with severe vertigo symptoms may have limited mobility, which may interfere with hospital visits. The spread of COVID-19 has further limited the number of hospital visits for patients with dizziness; therefore, a method of medical care that enables more accurate treatment under time and geographical constraints is needed. Telemedicine has become widespread, owing to the popularity of smartphone and tablet devices in recent years, and the use of devices and systems has made it possible to provide efficient medical care. However, no previous scoping review has mapped existing studies on telemedicine for vertigo and dizziness, and no recommendations have been made regarding which devices and systems should be used for specific diseases.

OBJECTIVE

The aim of this review was to map and assess previous studies on the use of information communications technology, smartphones, and apps for treating patients with vertigo and discuss the added value of introducing telemedicine to improve the quality of medical care and create an environment that builds security and trust among patients.

METHODS

A scoping review was conducted with the methodological framework of Arksey and O'Malley and in accordance with the of the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analysis extension for Scoping Reviews) guidelines. The PubMed, MEDLINE, and Cochrane Library databases were searched to retrieve previous reports on smartphone-assisted telemedicine treatment for vertigo published between January 2000 and May 2023. Two authors independently assessed eligibility and extracted data.

RESULTS

This review included 20 papers that reported devices or systems for telemedicine for vestibular dysfunction. Among studies that reported the use of a device or app, 2 were related to anamnesis and subjective symptoms, 12 were related to objective examination, 7 were related to remote diagnosis, and 7 were related to treatment and rehabilitation.

CONCLUSIONS

With the advancement of technology, the use of telemedicine in patients with dizziness may be feasible. In the future, it will be necessary to consider how telemedicine can be used in dizziness treatment and develop an effective treatment system combining in-person medical care and the effective use of devices for the management of severe vertigo and related diseases. The smooth introduction of telemedicine in vertigo treatment is expected to improve the quality of treatment, increase opportunities for patients to receive medical care, and reduce time and travel costs, leading to a sense of security and trust among patients.

Development of a Prototype Video Head Impulse Test System Using an iPhone for Screening of Peripheral Vestibular Dysfunction

Introduction

Head impulse, nystagmus, and test of skew (HINTS) is more accurate for the early diagnosis of occipital fossa stroke than magnetic resonance imaging. However, the head impulse test (HIT) is relatively challenging to perform, as it is subjective. Herein, we developed a prototype video HIT (vHIT) system using an iPhone (Apple, Cupertino, CA, USA) that is compact, easy to operate, and analyzable by our iPhone application.

Methods

The iPhone-vHIT and a vHIT using EyeSeeCam (Interacoustics, Eden Prairie, NM, USA) were performed on a healthy man in his 30s and on a patient with vestibular neuritis who visited the Mejiro University Ear Institute Clinic. For the iPhone-vHIT, eye movements were detected by analyzing high-speed videos captured using an iPhone camera, and head movements were followed using an iPhone gyro sensor. An iPhone fixation brace was used to capture the video without any blurring.

Results

The iPhone-vHIT system obtained vHIT waveforms similar to those of the EyeSeeCam-vHIT system in the healthy man and the patient with vestibular neuritis. The iPhone-vHIT system effectively detected the reduced vestibulo-ocular reflex gain in patients with vestibular neuritis. The iPhone-vHIT system at 120 frames per second was less sensitive to catch-up saccades than the EyeSeeCam.

Conclusion

vHIT systems using a smartphone have been reported but are currently unavailable. At present, the iPhone-vHIT application in this study is the only available smartphone-based vHIT system for screening of peripheral vestibular dysfunction. We believe that the prototype iPhone-vHIT with a high-speed camera will be clinically used to perform the vHIT, even though it only examines the lateral semicircular canal.

Smartphone video nystagmography using convolutional neural networks: ConVNG

Background

Eye movement abnormalities are commonplace in neurological disorders. However, unaided eye movement assessments lack granularity. Although videooculography (VOG) improves diagnostic accuracy, resource intensiveness precludes its broad use. To bridge this care gap, we here validate a framework for smartphone video-based nystagmography capitalizing on recent computer vision advances.

Methods

A convolutional neural network was fine-tuned for pupil tracking using > 550 annotated frames: ConVNG. In a cross-sectional approach, slow-phase velocity of optokinetic nystagmus was calculated in 10 subjects using ConVNG and VOG. Equivalence of accuracy and precision was assessed using the “two one-sample t-test” (TOST) and Bayesian interval-null approaches. ConVNG was systematically compared to OpenFace and MediaPipe as computer vision (CV) benchmarks for gaze estimation.

Results

ConVNG tracking accuracy reached 9–15% of an average pupil diameter. In a fully independent clinical video dataset, ConVNG robustly detected pupil keypoints (median prediction confidence 0.85). SPV measurement accuracy was equivalent to VOG (TOST p < 0.017; Bayes factors (BF) > 24). ConVNG, but not MediaPipe, achieved equivalence to VOG in all SPV calculations. Median precision was 0.30°/s for ConVNG, 0.7°/s for MediaPipe and 0.12°/s for VOG. ConVNG precision was significantly higher than MediaPipe in vertical planes, but both algorithms’ precision was inferior to VOG.

Conclusions

ConVNG enables offline smartphone video nystagmography with an accuracy comparable to VOG and significantly higher precision than MediaPipe, a benchmark computer vision application for gaze estimation. This serves as a blueprint for highly accessible tools with potential to accelerate progress toward precise and personalized Medicine.

aEYE: A deep learning system for video nystagmus detection

Background

Nystagmus identification and interpretation is challenging for non-experts who lack specific training in neuro-ophthalmology or neuro-otology. This challenge is magnified when the task is performed via telemedicine. Deep learning models have not been heavily studied in video-based eye movement detection.

Methods

We developed, trained, and validated a deep-learning system (aEYE) to classify video recordings as normal or bearing at least two consecutive beats of nystagmus. The videos were retrospectively collected from a subset of the monocular (right eye) video-oculography (VOG) recording used in the Acute Video-oculography for Vertigo in Emergency Rooms for Rapid Triage (AVERT) clinical trial (#NCT02483429). Our model was derived from a preliminary dataset representing about 10% of the total AVERT videos (n = 435). The videos were trimmed into 10-sec clips sampled at 60 Hz with a resolution of 240 × 320 pixels. We then created 8 variations of the videos by altering the sampling rates (i.e., 30 Hz and 15 Hz) and image resolution (i.e., 60 × 80 pixels and 15 × 20 pixels). The dataset was labeled as "nystagmus" or "no nystagmus" by one expert provider. We then used a filtered image-based motion classification approach to develop aEYE. The model's performance at detecting nystagmus was calculated by using the area under the receiver-operating characteristic curve (AUROC), sensitivity, specificity, and accuracy.

Results

An ensemble between the ResNet-soft voting and the VGG-hard voting models had the best performing metrics. The AUROC, sensitivity, specificity, and accuracy were 0.86, 88.4, 74.2, and 82.7%, respectively. Our validated folds had an average AUROC, sensitivity, specificity, and accuracy of 0.86, 80.3, 80.9, and 80.4%, respectively. Models created from the compressed videos decreased in accuracy as image sampling rate decreased from 60 Hz to 15 Hz. There was only minimal change in the accuracy of nystagmus detection when decreasing image resolution and keeping sampling rate constant.

Conclusion

Deep learning is useful in detecting nystagmus in 60 Hz video recordings as well as videos with lower image resolutions and sampling rates, making it a potentially useful tool to aid future automated eye-movement enabled neurologic diagnosis.

The HINTS examination and STANDING algorithm in acute vestibular syndrome: A systematic review and meta-analysis involving frontline point-of-care emergency physicians

This systematic review aims to evaluate whether point-of-care emergency physicians, without special equipment, can perform the HINTS examination or STANDING algorithm to differentiate between central and non-central vertigo in acute vestibular syndrome with diagnostic accuracy and reliability comparable to more specialized physicians (neuro-ophthalmologists and neuro-otologists). Previous research has concluded that emergency physicians are unable to utilize the HINTS examination with sufficient accuracy, without providing any appropriate education or training. A comprehensive systematic search was performed using MEDLINE, Embase, the Cochrane CENTRAL register of controlled trials, Web of Science Core Collection, Scopus, Google Scholar, the World Health Organization International Clinical Trials Registry Platform, and conference programs and abstracts from six medical organizations. Of the 1,757 results, only 21 were eligible for full-text screening. Two further studies were identified by a manual search of references and an electronic search for any missed studies associated with the authors. Five studies were included in the qualitative synthesis. For the STANDING algorithm, there were two studies of 450 patients who were examined by 11 emergency physicians. Our meta-analysis showed that emergency physicians who had received prior education and training were able to utilize the STANDING algorithm with a sensitivity of 0.96 (95% confidence interval: 0.87–1.00) and a specificity of 0.88 (0.85–0.91). No data was available for the HINTS examination. When emergency physicians are educated and trained, they can use the STANDING algorithm with confidence. There is a lack of evidence regarding the HINTS examination; however, two ongoing studies seek to remedy this deficit.

Eye and Head Movement Recordings Using Smartphones for Telemedicine Applications: Measurements of Accuracy and Precision

Objective

Smartphones have shown promise in the assessment of neuro-ophthalmologic and vestibular disorders. We have shown that the head impulse test results recorded using our application are comparable with measurements from clinical video-oculography (VOG) goggles. The smartphone uses ARKit's capability to acquire eye and head movement positions without the need of performing a calibration as in most eye-tracking devices. Here, we measure the accuracy and precision of the eye and head position recorded using our application.

Methods

We enrolled healthy volunteers and asked them to direct their eyes, their heads, or both to targets on a wall at known eccentricities while recording their head and eye movements with our smartphone application. We measured the accuracy as the error between the eye or head movement measurement and the location of each target and the precision as the standard deviation of the eye or head position for each of the target positions.

Results

The accuracy of head recordings (15% error) was overall better than the accuracy of eye recordings (23% error). We also found that the accuracy for horizontal eye movements (17% error) was better than for vertical (27% error). Precision was also better for head movement (0.8 degrees) recordings than eye movement recordings (1.3 degrees) and variability tended to increase with eccentricity.

Conclusion

Our results provide basic metrics evaluating the utility of smartphone applications in the quantitative assessment of head and eye movements. While the new method may not replace the more accurate dedicated VOG devices, they provide a more accessible quantitative option. It may be advisable to include a calibration recording together with any planned clinical test to improve the accuracy.

Identification of Stroke and TIA in Patients With Acute Dizziness, Vertigo or Imbalance in Emergency Departments of Primary Care Hospitals: Early Experiences With a Network-Based Telemedical Approach

Background

Acute dizziness, vertigo, and imbalance are frequent and difficult to interpret symptoms in the emergency department (ED). Primary care hospitals often lack the expertise to identify stroke or TIA as underlying causes. A telemedical approach based on telestroke networks may offer adequate diagnostics and treatment.

Aim

The aim of this study is to evaluate the accuracy of a novel ED algorithm in differentiating between peripheral and central vestibular causes.

Methods

Within the Telemedical Project for Integrative Stroke Care (TEMPiS), a telemedical application including a videooculography (VOG) system was introduced in 2018 in 19 primary care spoke hospitals. An ED triage algorithm was established for all patients with acute dizziness, vertigo, or imbalance of unknown cause (ADVIUC) as a leading complaint. In three predefined months, all ADVIUC cases were prospectively registered and discharge letters analyzed. Accuracy of the ED triage algorithm in differentiation between central and peripheral vestibular cases was analyzed by comparison of ED diagnoses to final discharge diagnoses. The rate of missed strokes was calculated in relation to all cases with a suitable brain imaging. Acceptance of teleconsultants and physicians in spoke hospitals was assessed by surveys.

Results

A total number of 388 ADVIUC cases were collected, with a median of 12 cases per months and hospital (IQR 8–14.5). The most frequent hospital discharge diagnoses are vestibular neuritis (22%), stroke/TIA (18%), benign paroxysmal positioning vertigo (18%), and dizziness due to internal medicine causes (15%). Detection of a central vestibular cause by the ED triage algorithm has a high sensitivity (98.6%), albeit poor specificity (45.9%). One stroke out of 32 verified by brain scan was missed (3.1%). User satisfaction, helpfulness of the project, improvement of care, personal competence, and satisfaction about handling of the VOG systems were rated consistently positive.

Discussion

The concept shows good acceptance for a telemedical and network-based approach to manage ADVIUC cases in the ED of primary care hospitals. Identification of stroke cases is accurate, while specificity needs further improvement. The concept could be a major step toward a broadly available state of the art diagnostics and therapy for patients with ADVIUC in primary care hospitals.

Feasibility of Telemedical HINTS (Head Impulse-Nystagmus-Test of Skew) Evaluation in Patients With Acute Dizziness or Vertigo in the Emergency Department of Primary Care Hospitals

Background

Acute dizziness, vertigo and imbalance are common symptoms in emergency departments. Stroke needs to be distinguished from vestibular diseases. A battery of three clinical bedside tests (HINTS: Head Impulse Test, Nystagmus, Test of Skew) has been shown to detect stroke as underlying cause with high reliability, but implementation is challenging in primary care hospitals. Aim of this study is to prove the feasibility of a telemedical HINTS examination via a remotely controlled videooculography (VOG) system.

Methods

The existing video system of our telestroke network TEMPiS (Telemedic Project for Integrative Stroke Care) was expanded through a VOG system. This feature enables the remote teleneurologist to assess a telemedical HINTS examination based on inspection of eye movements and quantitative video head impulse test (vHIT) evaluation. ED doctors in 11 spoke hospitals were trained in performing vHIT, nystagmus detection and alternating cover test. Patients with first time acute dizziness, vertigo or imbalance, whether ongoing or resolved, presented to the teleneurologist were included in the analysis, as long as no focal neurological deficit according to the standard teleneurological examination or obvious internal medicine cause was present and a fully trained team was available. Primary outcome was defined as the feasibility of the telemedical HINTS examination.

Results

From 01.06.2019 to 31.03.2020, 81 consecutive patients were included. In 72 (88.9%) cases the telemedical HINTS examination was performed. The complete telemedical HINTS examination was feasible in 46 cases (63.9%), nystagmus detection in all cases (100%) and alternating covert test in 70 cases (97.2%). The vHIT was recorded and interpretable in 47 cases (65.3%). Results of the examination with the VOG system yielded clear results in 21 cases (45.7%) with 14 central and 7 peripheral lesions. The main reason for incomplete examination was the insufficient generation of head impulses.

Conclusion

In our analysis the telemedical HINTS examination within a telestroke network was feasible in two thirds of the patients. This offers the opportunity to improve specific diagnostics and therapy for patients with acute dizziness and vertigo even in primary care hospitals. Improved training for spoke hospital staff is needed to further increase the feasibility of vHIT.

Vestibular function testing in the 21st century: video head impulse test, vestibular evoked myogenic potential, video nystagmography; which tests will provide answers?

PURPOSE OF REVIEW

To most neurologists, assessing the patient with vertigo is an unpleasant and worrisome task. A structured history and focused examination can be complemented by carefully selected laboratory tests, to reach an early and accurate diagnosis. We provide evidence-based recommendations for vestibular test selection.

RECENT FINDINGS

The video head impulse test (vHIT), cervical and ocular vestibular evoked myogenic potential (VEMP) and home-video nystagmography are four modern, noninvasive methods of assessing vestibular function, which are equally applicable in the hospital and office-practice. Collectively, they enable assessment of all five vestibular end-organs. The prevalence and patterns of test abnormalities are distinct for each vestibular disorder. We summarize typical abnormalities encountered in four common vestibular syndromes.

SUMMARY

In the context of acute vestibular syndrome, an abnormal vHIT with low gain and large amplitude refixation saccades and an asymmetric oVEMP separates innocuous vestibular neuritis from stroke. In episodic spontaneous vertigo, high-velocity ictal nystagmus and asymmetric cVEMP help separate Ménière's disease from vestibular migraine. In chronic imbalance, all three tests help detect unilateral or bilateral vestibular loss as the root cause. Recurrent positional vertigo requires no laboratory test and can be diagnosed and treated at the bedside, guided by video nystagmography.

New Frontiers in Managing the Dizzy Patient

Despite progress in vestibular research in the last 20 years, much remains poorly understood about vestibular pathophysiology and its management. A shared language is a critical first step in understanding vestibular disorders and is under development. Telehealth will continue for patients with dizziness, and ambulatory monitoring of nystagmus will become a diagnostic tool. In the next 2 decades, it is anticipated that vestibular perceptual threshold testing will become common in tertiary centers, imaging with improved spatial resolution will yield better understanding of vestibular pathophysiology, and that vestibular implants will become a part of clinical practice.

Pitfalls in the Diagnosis of Posterior Circulation Stroke in the Emergency Setting

Posterior circulation stroke (PCS), caused by infarction within the vertebrobasilar arterial system, is a potentially life-threatening condition and accounts for about 20–25% of all ischemic strokes. Diagnosing PCS can be challenging due to the vast area of brain tissue supplied by the posterior circulation and, as a consequence, the wide range of—frequently non-specific—symptoms. Commonly used prehospital stroke scales and triage systems do not adequately represent signs and symptoms of PCS, which may also escape detection by cerebral imaging. All these factors may contribute to causing delay in recognition and diagnosis of PCS in the emergency context. This narrative review approaches the issue of diagnostic error in PCS from different perspectives, including anatomical and demographic considerations as well as pitfalls and problems associated with various stages of prehospital and emergency department assessment. Strategies and approaches to improve speed and accuracy of recognition and early management of PCS are outlined.