Eye Movement Evaluation in Multiple Sclerosis and Parkinson's Disease Using a Standardized Oculomotor and Neuro-Ophthalmic Disorder Assessment (SONDA)

Open Iris - An Open Source Framework for Video-Based Eye-Tracking Research and Development

Eye-tracking is an essential tool in many fields, yet existing solutions are often limited for customized applications due to cost or lack of flexibility. We present OpenIris, an adaptable and user-friendly open-source framework for video-based eye-tracking. OpenIris is developed in C# with modular design that allows further extension and customization through plugins for different hardware systems, tracking, and calibration pipelines. It can be remotely controlled via a network interface from other devices or programs. Eye movements can be recorded online from camera stream or offline post-processing recorded videos. Example plugins have been developed to track eye motion in 3-D, including torsion. Currently implemented binocular pupil tracking pipelines can achieve frame rates of more than 500Hz. With the OpenIris framework, we aim to fill a gap in the research tools available for high-precision and high-speed eye-tracking, especially in environments that require custom solutions that are not currently well-served by commercial eye-trackers.

A novel tablet-based software for the acquisition and analysis of gaze and eye movement parameters: a preliminary validation study in Parkinson's disease

The idea that eye movements can reflect certain aspects of brain function and inform on the presence of neurodegeneration is not a new one. Indeed, a growing body of research has shown that several neurodegenerative disorders, such as Alzheimer's and Parkinson's Disease, present characteristic eye movement anomalies and that specific gaze and eye movement parameters correlate with disease severity. The use of detailed eye movement recordings in research and clinical settings, however, has been limited due to the expensive nature and limited scalability of the required equipment. Here we test a novel technology that can track and measure eye movement parameters using the embedded camera of a mobile tablet. We show that using this technology can replicate several well-known findings regarding oculomotor anomalies in Parkinson's disease (PD), and furthermore show that several parameters significantly correlate with disease severity as assessed with the MDS-UPDRS motor subscale. A logistic regression classifier was able to accurately distinguish PD patients from healthy controls on the basis of six eye movement parameters with a sensitivity of 0.93 and specificity of 0.86. This tablet-based tool has the potential to accelerate eye movement research via affordable and scalable eye-tracking and aid with the identification of disease status and monitoring of disease progression in clinical settings.

Stimulus contrast, pursuit mode, and age strongly influence tracking performance on a continuous visual tracking task

Human observers tend to naturally track moving stimuli. This tendency may be exploited towards an intuitive means of screening visual function as an impairment induced reduction in stimulus visibility will decrease tracking performance. Yet, to be able to detect subtle impairments, stimulus contrast is critical. If too high, the decrease in performance may remain undetected. Therefore, for this approach to become reliable and sensitive, we need a detailed understanding of how age, stimulus contrast, and the type of stimulus movement affect continuous tracking performance. To do so, we evaluated how well twenty younger and twenty older participants tracked a semi-randomly moving stimulus (Goldmann size III, 0.43 degrees of visual angle), presented at five contrast levels (5%-10%-20%-40%-80%). The stimulus could move smoothly only (smooth pursuit mode) or in alternation with displacements (saccadic pursuit mode). Additionally, we assessed static foveal and peripheral contrast thresholds. For all participants, tracking performance improved with increasing contrast in both pursuit modes. To reach threshold performance levels, older participants required about twice as much contrast (20% vs. 10% and 40% vs. 20% in smooth and saccadic modes respectively). Saccadic pursuit detection thresholds correlated significantly with static peripheral contrast thresholds (rho = 0.64). Smooth pursuit detection thresholds were uncorrelated with static foveal contrast thresholds (rho = 0.29). We conclude that continuous visual stimulus tracking is strongly affected by stimulus contrast, pursuit mode, and age. This provides essential insights that can be applied towards new and intuitive approaches of screening visual function.

Measuring saccades in patients with Niemann-Pick type C: A comparison between video-oculography and a novel eye tracking test based on continuous psychophysics

Introduction

Vertical supranuclear gaze palsy is a key feature of Niemann-Pick type C (NP-C) and is commonly quantified using video-oculography (VOG). VOG requires sitting still for long times and performing specific tasks, thus it can be challenging or impossible for patients severely affected by movement disorders or cognitive impairment. To overcome this limitation, we measure saccades of NP-C patients using a fast eye tracking test based on continuous psychophysics and compare it to VOG.

Methods

Saccades of six NP-C patients and six age-matched controls were assessed using VOG and Standardized Oculomotor and Neuro-ophthalmic Disorders Assessment (SONDA). In SONDA, participants continuously track a semi-randomly moving dot on a computer screen while their gaze is being tracked. For both assessments, saccades were quantified using four conventional measures: amplitude, gain, latency, and peak velocity. Furthermore, SONDA's continuous measures were quantified with several novel spatio-temporal properties.

Results

In the NP-C patients, both methods revealed reduced amplitude, gain, peak velocity, and increased latency of vertical saccades compared to horizontal saccades and compared to healthy controls. Effect sizes obtained with SONDA were overall larger than those for VOG. SONDA's spatio-temporal properties showed similar trends.

Conclusion

SONDA reveals a deterioration of vertical saccades in NP-C patients that is consistent with VOG. SONDA's measures based on continuous psychophysics are consistent with traditional saccadic parameters and can potentially provide complementary information. SONDA shows larger effect sizes than VOG, suggesting that it provides robust and clinically relevant outcomes with a more intuitive task and shorter testing time.

Abnormalities of the oculomotor function in type 1 diabetes and diabetic neuropathy

AIMS

Abnormalities in the oculomotor system may represent an early sign of diabetic neuropathy and are currently poorly studied. We designed an eye-tracking-based test to evaluate oculomotor function in patients with type 1 diabetes.

METHODS

We used the SRLab-Tobii TX300 Eye tracker®, an eye-tracking device, coupled with software that we developed to test abnormalities in the oculomotor system. The software consists of a series of eye-tracking tasks divided into 4 classes of parameters (Resistance, Wideness, Pursuit and Velocity) to evaluate both smooth and saccadic movement in different directions. We analyzed the oculomotor system in 34 healthy volunteers and in 34 patients with long-standing type 1 diabetes.

RESULTS

Among the 474 parameters analyzed with the eye-tracking-based system, 11% were significantly altered in patients with type 1 diabetes (p < 0.05), with a higher proportion of abnormalities observed in the Wideness (24%) and Resistance (10%) parameters. Patients with type 1 diabetes without diabetic neuropathy showed more frequently anomalous measurements in the Resistance class (p = 0.02). The classes of Velocity and Pursuit were less frequently altered in patients with type 1 diabetes as compared to healthy subjects, with anomalous measurements mainly observed in patients with diabetic neuropathy.

CONCLUSIONS

Abnormalities in oculomotor system function can be detected in patients with type 1 diabetes using a novel eye-tracking-based test. A larger cohort study may further determine thresholds of normality and validate whether eye-tracking can be used to non-invasively characterize early signs of diabetic neuropathy.

TRIAL

NCT04608890.

Digital Biomarkers in Multiple Sclerosis

For incurable diseases, such as multiple sclerosis (MS), the prevention of progression and the preservation of quality of life play a crucial role over the entire therapy period. In MS, patients tend to become ill at a younger age and are so variable in terms of their disease course that there is no standard therapy. Therefore, it is necessary to enable a therapy that is as personalized as possible and to respond promptly to any changes, whether with noticeable symptoms or symptomless. Here, measurable parameters of biological processes can be used, which provide good information with regard to prognostic and diagnostic aspects, disease activity and response to therapy, so-called biomarkers Increasing digitalization and the availability of easy-to-use devices and technology also enable healthcare professionals to use a new class of digital biomarkers-digital health technologies-to explain, influence and/or predict health-related outcomes. The technology and devices from which these digital biomarkers stem are quite broad, and range from wearables that collect patients' activity during digitalized functional tests (e.g., the Multiple Sclerosis Performance Test, dual-tasking performance and speech) to digitalized diagnostic procedures (e.g., optical coherence tomography) and software-supported magnetic resonance imaging evaluation. These technologies offer a timesaving way to collect valuable data on a regular basis over a long period of time, not only once or twice a year during patients' routine visit at the clinic. Therefore, they lead to real-life data acquisition, closer patient monitoring and thus a patient dataset useful for precision medicine. Despite the great benefit of such increasing digitalization, for now, the path to implementing digital biomarkers is widely unknown or inconsistent. Challenges around validation, infrastructure, evidence generation, consistent data collection and analysis still persist. In this narrative review, we explore existing and future opportunities to capture clinical digital biomarkers in the care of people with MS, which may lead to a digital twin of the patient. To do this, we searched published papers for existing opportunities to capture clinical digital biomarkers for different functional systems in the context of MS, and also gathered perspectives on digital biomarkers under development or already existing as a research approach.

Eye-Movement-Based Assessment of the Perceptual Consequences of Glaucomatous and Neuro-Ophthalmological Visual Field Defects

Purpose

Assessing the presence of visual field defects (VFD) through procedures such as perimetry is an essential aspect of the management and diagnosis of ocular disorders. However, even the latest perimetric methods have shortcomings-a high cognitive demand and requiring prolonged stable fixation and feedback through a button response. Consequently, an approach using eye movements (EM)-as a natural response-has been proposed as an alternate way to evaluate the presence of VFD. This approach has given good results for computer-simulated VFD. However, its use in patients is not well documented yet. Here we use this new approach to quantify the spatiotemporal properties (STP) of EM of various patients suffering from glaucoma and neuro-ophthalmological VFD and controls.

Methods

In total, 15 glaucoma patients, 37 patients with a neuro-ophthalmological disorder, and 21 controls performed a visual tracking task while their EM were being recorded. Subsequently, the STP of EM were quantified using a cross-correlogram analysis. Decision trees were used to identify the relevant STP and classify the populations.

Results

We achieved a classification accuracy of 94.5% (TPR/sensitivity = 96%, TNR/specificity = 90%) between patients and controls. Individually, the algorithm achieved an accuracy of 86.3% (TPR for neuro-ophthalmology [97%], glaucoma [60%], and controls [86%]). The STP of EM were highly similar across two different control cohorts.

Conclusions

In an ocular tracking task, patients with VFD due to different underlying pathology make EM with distinctive STP. These properties are interpretable based on different clinical characteristics of patients and can be used for patient classification.

Translational Relevance

Our EM-based screening tool may complement existing perimetric techniques in clinical practice.

Computational Methods for Continuous Eye-Tracking Perimetry Based on Spatio-Temporal Integration and a Deep Recurrent Neural Network

The measurement of retinal sensitivity at different visual field locations-perimetry-is a fundamental procedure in ophthalmology. The most common technique for this scope, the Standard Automated Perimetry, suffers from several issues that make it less suitable to test specific clinical populations: it can be tedious, it requires motor manual feedback, and requires from the patient high levels of compliance. Previous studies attempted to create user-friendlier alternatives to Standard Automated Perimetry by employing eye movements reaction times as a substitute for manual responses while keeping the fixed-grid stimuli presentation typical of Standard Automated Perimetry. This approach, however, does not take advantage of the high spatial and temporal resolution enabled by the use of eye-tracking. In this study, we introduce a novel eye-tracking method to perform high-resolution perimetry. This method is based on the continuous gaze-tracking of a stimulus moving along a pseudo-random walk interleaved with saccadic jumps. We then propose two computational methods to obtain visual field maps from the continuous gaze-tracking data: the first is based on the spatio-temporal integration of ocular positional deviations using the threshold free cluster enhancement (TFCE) algorithm; the second is based on using simulated visual field defects to train a deep recurrent neural network (RNN). These two methods have complementary qualities: the TFCE is neurophysiologically plausible and its output significantly correlates with Standard Automated Perimetry performed with the Humphrey Field Analyzer, while the RNN accuracy significantly outperformed the TFCE in reconstructing the simulated scotomas but did not translate as well to the clinical data from glaucoma patients. While both of these methods require further optimization, they show the potential for a more patient-friendly alternative to Standard Automated Perimetry.