Smart Eye Research Articles

Validation and optimization of smart eye camera as teleophthalmology device for the reduction of preventable and treatable blindness in Nigeria.

Limited resources and staffing hinders efforts to reduce preventable blindness, especially in low- to middle-income countries. The slit-lamp examination (SLE), which is essential for ophthalmology practices, is often unavailable in primary and secondary eye care facilities due to the high costs and lengthy training required for operation. We conducted a cross-sectional, multicentre study exploring the potential for a smart eye camera (SEC; a tele-ophthalmology handheld device developed by OUI Inc., Japan) to address the limitations of the SLE. Ocular diagnoses, visual acuity assessments and examinations of the eyes were performed independently using both a conventional SLE and a SEC. Four independent assessors (blind to the study) reviewed the images captured by the SEC and the SLE as administered by separate investigators. All analyses were performed using R version 4.2.2 for macOS at a 5% level of statistical significance. The results of the image quality analysis demonstrated that the number of higher-quality images was significantly higher (p < 0.05) for the images captured using the SEC device compared to the SLE machine. Remarkably, up to 96% accuracy of diagnosis was recorded with SEC. Evaluation of diagnostic accuracy rates derived from images obtained from both machines revealed a degree of divergence in assessments among evaluators, yielding a Fleiss's Kappa value of 0.092. The sensitivity analysis for the SEC device revealed a reasonably strong capacity to correctly identify true positive cases, with an average sensitivity score of 90%. The results of this study indicate that SEC can effectively evaluate anterior segment lesions in ophthalmology.

Evaluating the Effect of Image Enhancement on Diagnostic Reliability in Dry Eye Disease Using a Portable Imaging Device.

This study aimed to evaluate the impact of image enhancement techniques on the interobserver reliability of tear break-up time (TBUT), tear meniscus height (TMH), corneal fluorescein staining (CFS) scoring, and conjunctivochalasis detection using the Smart Eye Camera (SEC), a portable device for anterior segment examination. A retrospective analysis was conducted on video recordings captured by the SEC from 46 patients with dry eye disease (DED). Separate sets of images were created for each level of enhancement: unenhanced (G0), mildly enhanced (G3), and strongly enhanced (G7). These sets were not intermixed, ensuring that each enhancement level was assessed independently. Three observers-two DED specialists and one general ophthalmologist-assessed TBUT, TMH, CFS scores, and conjunctivochalasis. Interobserver reliability was evaluated using intraclass correlation coefficients (ICCs) for each image set. Interobserver reliability for CFS scores significantly improved with G3, yielding an ICC of 0.8413. In contrast, G7 improved reliability for TBUT measurements (ICC = 0.7381), but led to a notable decrease in reliability for both CFS scoring (ICC = 0.2259) and conjunctivochalasis detection (ICC = 0.0786). Furthermore, the assessment of TMH demonstrated a progressive decline in accuracy with increasing levels of image enhancement. Image enhancement using the SEC improved the diagnostic consistency of dry eye specialists and general ophthalmologists, especially for TBUT and CFS assessments. However, excessive enhancement may obscure key diagnostic features, indicating the need for careful optimization of image processing techniques depending on the diagnostic focus.

Utilizing Eye-Tracking in Advertising: Preliminary Findings

Eye-tracking research is steadily increasing, with emerging hypotheses about the connection between eye movements and cognitive processes in advertising contexts. This study aimed to utilize eye-tracking technology to explore how consumers perceive advertising appeals, particularly in distinguishing between the promoted product and the accompanying elements within an advertisement. The research sample included 35 students aged 19 to 23 years, comprising 18 women (51%) and 17 men (49%). The eye-tracker used in our study was the Smart Eye AI-X model from iMotions. We hypothesized that respondents would predominantly focus their gaze on the image of the child. The heat map revealed that the most viewed areas were the advertising text, the child’s face, and the car’s registration number section. The factors examined in this study significantly impact data quality, and we argue that our findings are valuable for anyone seeking to capture high-quality data in psychological and neurological research.

P‐44: A Smart Eye Tracking System Based on Linear Array Sensors

Eye tracking as an important human‐machine interface plays avital role in immersive displays such as augmented reality (AR) and virtual reality (VR). Different from near infrared (NIR) camerabased methods, the proposed corneal reflection method based on principle of eyeball co‐vision takes advantage of using eye‐safe 940‐ nm vertical cavity surface emitting laser (VCSEL) and dual‐column linear array sensor (DCLAS) to obtain coordinates of the eyeball's moving positions through detecting its reflected light. The DCLAS not only delivers high sensitivity at eye‐safe NIR wavelength, but also has high spatial resolution for position accuracy and wide dynamic range to suppress ambient light influence. Together with low power consumption, good wearability, low data redundancy and simple computing algorism, a great promise can be made to enable smart eye tracking for AR/VR.

Smart Eye : Empowering the Visually Impaired with Assistive Technology

According to the World Health Organization, an estimated 39 million people worldwide are visually impaired, underscoring the critical need for innovative solutions to assist blind individuals in navigating their environment independently. In response, this study introduces an intelligent and multipurpose bright blind stick leveraging Internet of Things (IoT) technology. The stick integrates components such as Arduino UNO, ultrasonic sensor, servo motor, Bluetooth module, GPS, and GSM modules to detect obstacles in real-time and provide audio feedback alerts to the user. Additionally, the technology enables remote monitoring by caregivers through GPS tracking and allows users to send location-based alert messages in emergencies. Through extensive research and comparative analysis of existing systems, including traditional white canes and other electronic aids, our solution has been designed to overcome common limitations such as high cost, limited functionality, and lack of portability. The intelligent multipurpose bright blind stick offers a cost-effective, portable, and intelligent tool aimed at significantly enhancing the independence and safety of blind individuals, fostering inclusivity and autonomy in their daily lives. This paper will provide insights into the design, implementation, and user testing of the solution, highlighting its effectiveness in real-world scenarios and its potential to make a meaningful impact on the lives of blind individuals worldwide. Index Terms - Arduino UNO, Servo Motor , Ultrasonic Sensor Bluetooth Module, GPS Module, GSM Module, Multi-functional Blind Stick and Internet of Things.

Feasibility of Tear Meniscus Height Measurements Obtained with a Smartphone-Attachable Portable Device and Agreement of the Results with Standard Slit Lamp Examination

Purpose: We aimed to evaluate the feasibility of using a novel device, the Smart Eye Camera (SEC), for assessing tear meniscus height (TMH) after fluorescein staining and the agreement of the results with measurements obtained using standard slit lamp examination. Methods: TMH was assessed using both SEC and conventional slit lamp examination. The images were analyzed using the software ImageJ 1.53t (National Institutes of Health, Bethesda, MD, USA). A common measurement unit scale was established based on a paper strip, which was used as a calibration marker to convert pixels into metric scale. A color threshold was applied using uniform parameters for brightness, saturation, and hue. The images were then binarized to black and white to enhance the representation of the tear menisci. A 2 mm area around the upper and lower meniscus in the central eye lid zone was selected and magnified 3200 times to facilitate manual measurement. The values obtained using SEC were compared with those obtained with a slit lamp. Results: The upper and lower TMH values measured using the SEC were not statistically different from those obtained with a slit lamp (0.209 ± 0.073 mm vs. 0.235 ± 0.085, p = 0.073, and 0.297 ± 0.168 vs. 0.260 ± 0.173, p = 0.275, respectively). The results of Bland–Altman analysis demonstrated strong agreement between the two instruments, with a mean bias of −0.016 mm (agreement limits: −0.117 to 0.145 mm) for upper TMH and 0.031 mm (agreement limits: −0.306 to 0.368 mm) for lower TMH. Conclusions: The SEC demonstrated sufficient validity and reliability for assessing TMH in healthy eyes in a clinical setting, demonstrating concordance with the conventional slit lamp examination.

Transforming lives of Sensory Impaired Individuals through Extended Reality (XR)

Sensory Impaired individuals are people with limitations or disabilities related to their sensory perception, which includes their abilities to hear, see or process sensory information. They may have visual impairments, hearing impairments, or a combination of both. Emerging technologies have the potential to revolutionise our approach to assistive devices. This paper explores the impact of Extended Reality (XR) in ameliorating the lives of sensory-impaired individuals with the help of a smart eye wear—RaveSens, by addressing challenges related to communication, accessibility, education, navigation, and social inclusion. This is attempted through intensive design methodologies—Multi-Modal Interaction (MMI), and User-Centred Design (UCD) approach to engineering design. The sensory impaired individuals, parents, care-providers, doctors, and rehabilitation centres, are the stakeholders involved in the process of validation and design. The design includes features like haptic feedback, visual augmentation for deaf, bone conduction feedback, navigation assistance through gesture and voice control with regulatory compliance. Extended Reality (XR) assistive technology stands as an impactful catalyst in enhancing sensory-impaired individual lives and ensuring that, they can engage fully in this fast-paced digital world. This helps empower them and foster inclusivity.

Smart Eye for Visually Impaired People

Abstract: This paper presents a novel mobile application tailored to enhance the daily experiences of individuals with visual impairments. Leveraging cutting-edge real-time object detection and Optical Character Recognition (OCR) techniques, the app, constructed using the TensorFlow algorithm and the comprehensive Common Objects in Context (COCO) dataset, aims to empower users by providing invaluable assistance through their mobile devices. The application utilizes the device's camera to seamlessly identify objects in real-time via the object detection algorithm, while simultaneously extracting and vocalizing text from captured images through OCR technology. A crucial aspect of the app lies in its commitment to user-friendliness, ensuring a straightforward interface tailored specifically for the needs of visually impaired individuals. The efficacy of the system was rigorously evaluated, focusing on both accuracy and real-time performance. Results conclusively demonstrate the app's effectiveness and efficiency in offering essential support to visually impaired users, marking a significant stride toward fostering independence and ease in their daily lives. Remarkably, this mobile application stands out for its affordability and accessibility, providing a practical and inclusive solution for individuals with visual impairments. By delivering audio feedback about identified objects and recognized text, this innovative app contributes to a more accessible and autonomous lifestyle for its users, contributing positively to the broader landscape of assistive technology for the visually impaired.

Interobserver Reliability of Tear Break-Up Time Examination Using "Smart Eye Camera" in Indonesian Remote Area.

Dry eye disease (DED) is a multifactorial disease of tears and ocular surface that results in symptoms of discomfort, visual disturbance, and tear film instability leading to decrease of vision, productivity and quality of life, and blindness. DED diagnosis remains difficult and underdiagnosed regarding inconsistency between subjective symptoms and clinical findings. Tear break-up time (TBUT) is an objective indicator of tear film stability in diagnostic DED. A novel smartphone attachment, namely SEC (smart eye camera), could mimic conventional slit lamp to assess TBUT and beneficial in facilitating DED diagnosis. Reliability between a non and an ophthalmologist in TBUT assessment and DED diagnosis is observed in this study. To determine interobserver reliability of TBUT measurement for diagnosing DED using SEC. This a cross-sectional analytic study involving 99 participants (198 eyes) aged 40 years who visited Pratama Gema Santi Hospital, Nusa Penida, from September 2nd to 4th, 2022, with consecutive sampling technique. Fluoresceined eyes were filmed using the SEC device and apps, continued by masked ophthalmologist and resident assessing TBUT based on the video. The primary outcome is interobserver reliability for TBUT measurement and DED diagnosis. The mean age of participants was 55.22±9.78 years, 48.5% male and 51.5% female. The reliability of interobserver in assessing DED based on TBUT test is 0.78 (95% CI=0.31-1.26, P-value=0.001), and interobserver reliability in diagnosing DED based on OSDI and TBUT showed good agreement (weighted kappa=0.71). Good interobserver reliability underscores that non-ophthalmologists can diagnose DED based on TBUT video using SEC. SEC video has good interobserver reliability to assess TBUT for DED diagnosis. SEC can be used as one of the methods in assessing DED in limited health care facilities. The high reliability of interobserver assessment indicates that DED diagnosis using video taken with SEC may be useful for telemedicine evaluation in remote areas.

A WORKFLOW FOR VALIDATION AND EVALUATION OF A DYNAMIC VISUALIZATION PLATFORM FOR UNDERGROUND ANTIQUITIES

Abstract. Smart Eye is a research project focused on developing and operating, in real-time, an innovative system, that allows the visualization of invisible, known, covered by the ground or by constructions, monuments and finds in an archaeological site, using an Augmented Reality (AR) environment. The visitors of an archaeological site will be able to observe the covered antiquities (3D models and descriptive information) on the screen of their mobile device (smart phone and/or tablet). The system integrates mobile positioning and pose estimation technologies, AR algorithms, Geographic Information Systems (GIS) and spatial databases. The AR application is implemented by IT scientists and is subsequently evaluated in the field to identify both technical problems (e.g. are files uploaded at high speed?) and problems identified by the average user of the AR application (e.g. would it be better if the button to display the 3D model of the archaeological excavation was larger on the screen or of a different color?). The paper will present, on one hand, the validation and evaluation protocols according to the relevant literature, and on the other, the exact evaluation methodology of the Smart Eye system. In addition, the problems identified and the way they were solved during the 1st evaluation of the application will be presented, as well as the problems identified during the 2nd evaluation.

Where drivers are looking at during takeover: Implications for safe takeovers during conditionally automated driving

Objective Safety has become one of the primary concerns of level 3 automated driving, especially during the takeover process. Since most studies have focused on impacts of various factors on takeover performance of drivers, there seems to be a gap between the causes of crashes and the desired means to mitigate their occurrence and consequences. Hence, the main objective of this study is to extract from crash data during takeovers drivers’ patterns of gaze behaviors and maneuvers and then utilize them to extract some guidance on human-machine-interface design to enhance safety and acceptability of automated driving. Methods A study involving 27 subjects was conducted on a high-fidelity driving simulator with a Steward motion platform of six degrees of freedom. Each subject participated in 6 takeover scenarios with a lead time of 5 s and different duration of monitoring (DoM), with their maneuvers recorded by the system and eye gazes recorded by the Smart Eye Pro and Smart Recorder. Crash data collected during the takeover process were then utilized for the analysis. Results From 132 valid takeovers collected from 23 out of the 27 participants, 15 crashes were recorded. Based on which, five typical patterns of unsafe behaviors were recognized that may have caused the crashes, denoted as Type I to Type V, respectively. Besides, it appears that even if drivers were given more time to observe the surroundings, i.e., longer DoM, the number of crashes has not decreased as anticipated. Therefore, what is more important seems to be drivers’ gaze behaviors and maneuvers shortly after TOR. Conclusions For takeovers to be safe, good cooperations between drivers’ gaze behaviors and maneuvers are essential. Overall, it seems that in emergent situations that require takeovers, some drivers have difficulty in allocating attentions reasonably, which appears to have less to do with the time left for drivers to observe the surroundings. While designing HMIs, we may as well consider providing enough information to guide drivers according to drivers’ states and maneuvers at the time to improve safety of takeovers in emergent situations, and more importantly, to provide the information timely and effectively.

A study establishing sensitivity and accuracy of smartphone photography in ophthalmologic community outreach programs: Review of a smart eye camera.

Diseases affecting the cornea are a major cause of corneal blindness globally. The pressing issue we are facing today is the lack of diagnostic devices in rural areas to diagnose these conditions. The aim of the study is to establish sensitivity and accuracy of smartphone photography using a smart eye camera (SEC) in ophthalmologic community outreach programs. In this pilot study, a prospective non-randomized comparative analysis of inter-observer variability of anterior segment imaging recorded using an SEC was performed. Consecutive 100 patients with corneal pathologies, who visited the cornea specialty outpatient clinic, were enrolled. They were examined with a conventional non-portable slit lamp by a cornea consultant, and the diagnoses were recorded. This was compared with the diagnoses made by two other consultants based on SEC videos of the anterior segment of the same 100 patients. The accuracy of SEC was accessed using sensitivity, specificity, PPV, and NPV. Kappa statistics was used to find the agreement between two consultants by using STATA 17.0 (Texas, USA). There was agreement between the two consultants to diagnosing by using SEC. Above 90% agreements were found in all the diagnoses, which were statistically significant (P-value < 0.001). More than 90% sensitivity and a negative predictive value were found. SEC can be used successfully in the community outreach programs like field visits, eye camps, teleophthalmology, and community centers, where either a clinical setup is lacking or ophthalmologists are not available.

Artificial intelligence to estimate the tear film breakup time and diagnose dry eye disease

The use of artificial intelligence (AI) in the diagnosis of dry eye disease (DED) remains limited due to the lack of standardized image formats and analysis models. To overcome these issues, we used the Smart Eye Camera (SEC), a video-recordable slit-lamp device, and collected videos of the anterior segment of the eye. This study aimed to evaluate the accuracy of the AI algorithm in estimating the tear film breakup time and apply this model for the diagnosis of DED according to the Asia Dry Eye Society (ADES) DED diagnostic criteria. Using the retrospectively corrected DED videos of 158 eyes from 79 patients, 22,172 frames were annotated by the DED specialist to label whether or not the frame had breakup. The AI algorithm was developed using the training dataset and machine learning. The DED criteria of the ADES was used to determine the diagnostic performance. The accuracy of tear film breakup time estimation was 0.789 (95% confidence interval (CI) 0.769–0.809), and the area under the receiver operating characteristic curve of this AI model was 0.877 (95% CI 0.861–0.893). The sensitivity and specificity of this AI model for the diagnosis of DED was 0.778 (95% CI 0.572–0.912) and 0.857 (95% CI 0.564–0.866), respectively. We successfully developed a novel AI-based diagnostic model for DED. Our diagnostic model has the potential to enable ophthalmology examination outside hospitals and clinics.

Clear Aligners and Smart Eye Tracking Technology as a New Communication Strategy between Ethical and Legal Issues.

Smart eye-tracking technology (SEET) that determines visual attention using smartphones can be used to determine the aesthetic perception of different types of clear aligners. Its value as a communication and comprehension tool, in addition to the ethical and legal concerns which it entails, can be assessed. One hundred subjects (50 F, 50 M; age range 15-70) were equally distributed in non-orthodontic (A) and orthodontic (B) groups. A smartphone-based SEET app assessed their knowledge of and opinions on aligners. Subjects evaluated images of smiles not wearing aligners, with/without attachments and with straight/scalloped gingival margins, as a guided calibration step which formed the image control group. Subsequently, the subjects rated the same smiles, this time wearing aligners (experimental images group). Questionnaire data and average values for each group of patients, and images relating to fixation times and overall star scores, were analyzed using these tests: chi-square, t-test, Mann-Whitney U, Spearman's rho, and Wilcoxon (p < 0.05). One-way ANOVA and related post-hoc tests were also applied. Orthodontic patients were found to be better informed than non-orthodontic patients. Aesthetic perception could be swayed by several factors. Attachments scored lower in aesthetic evaluation. Lips distracted attention from attachments and improved evaluations. Attachment-free aligners were better rated overall. A more thorough understanding as to the opinions, expectations and aesthetic perception of aligners can improve communication with patients. Mobile SEET is remarkably promising, although it does require a careful medicolegal risk-benefit assessments for responsible and professional use.

Physiological and Behavioral Changes of Passive Fatigue on Drivers during On-Road Driving

Driver fatigue can be further categorized into passive fatigue and active fatigue based on the task-induced fatigue perspective, with its categorization necessary from a theoretical basis and practical needs. Passive fatigue is caused by mental underload and inactive task engagement, which is considered more hazardous. To facilitate the construction of the driver monitoring system (DMS), the current study aims to investigate the physiological and behavioral changes of passive fatigue. A total of thirty-six participants completed a 90 min driving task on a monotonous highway, during which subjective fatigue level, eye tracking indicators, and driving dynamics were recorded using the Stanford Sleepiness Scale, Smart Eye Pro, and CAN Bus system. Results showed that drivers reported higher levels of fatigue as driving duration increased. An increase in pupil diameters and gaze dispersions were observed during the task. Drivers gradually reduced the control of the vehicle, in which faster speed and lower speed compliance were witnessed. In addition, a compensatory process was found as passive fatigue increased. Drivers tended to lower their standards to maintain the lateral position but recovered their lateral control when they lost control of the car speed. The current study emphasizes the importance of investigating active and passive fatigue of drivers independently, and the unique physiological and behavioral changes accompanied by passive fatigue should be considered in designing driver monitoring systems.

Offline Calibration for Infant Gaze and Head Tracking across a Wide Horizontal Visual Field.

Most well-established eye-tracking research paradigms adopt remote systems, which typically feature regular flat screens of limited width. Limitations of current eye-tracking methods over a wide area include calibration, the significant loss of data due to head movements, and the reduction of data quality over the course of an experimental session. Here, we introduced a novel method of tracking gaze and head movements that combines the possibility of investigating a wide field of view and an offline calibration procedure to enhance the accuracy of measurements. A 4-camera Smart Eye Pro system was adapted for infant research to detect gaze movements across 126° of the horizontal meridian. To accurately track this visual area, an online system calibration was combined with a new offline gaze calibration procedure. Results revealed that the proposed system successfully tracked infants' head and gaze beyond the average screen size. The implementation of an offline calibration procedure improved the validity and spatial accuracy of measures by correcting a systematic top-right error (1.38° mean horizontal error and 1.46° mean vertical error). This approach could be critical for deriving accurate physiological measures from the eye and represents a substantial methodological advance for tracking looking behaviour across both central and peripheral regions. The offline calibration is particularly useful for work with developing populations, such as infants, and for people who may have difficulties in following instructions.

To Cultivate Scientific Literacy by Learning, Thinking, Practicing and Understanding, To Utilize the “Smart Eye” Expertise by Integrating of Knowledge and Action: Ideological and Political Construction of Analytical Chemistry Experiment Course

To Cultivate Scientific Literacy by Learning, Thinking, Practicing and Understanding, To Utilize the “Smart Eye” Expertise by Integrating of Knowledge and Action: Ideological and Political Construction of Analytical Chemistry Experiment Course

Smart Eye: An Application for In Situ Accessibility to “Invisible” Heritage Sites

The Smart Eye Application is an augmented reality app for mobile devices that enables the in-situ 3D visualization of underground and inaccessible to the public archaeological sites and monuments. Accessibility to excavated archaeological sites and monuments is often hindered for reasons of preservation or urban development. Portable finds are transferred and, in some cases, exhibited in local museums, but the non-portable remains of ancient structures become eventually effaced from the landscape and the collective memory of local communities. The Smart Eye app provides an “x-ray” type view of excavation sites that have been backfilled and are now invisible. While common practice in heritage sites’ digital dissemination to the general public uses 2D or 3D reconstructions in augmented or virtual reality environments, the Smart Eye app presents archaeological remains in the shape and form they were found in by archaeologists supplemented with augmented reality markers that provide simplified textual and visual information aimed toward a non-scholarly public. The aim is to re-instate these heritage sites into the interactive relationship that people have with their landscape and their history. The present paper discusses the chaîne-opératoire of developing the app, from the acquisition of primary documentation data of the excavation sites to the methodology used for the production of the 3D models of the archaeological sites and the development of the app itself and the technical equipment used. Finally, we discuss the results of the preliminary evaluation of the application and future steps to improve it before final testing by the local communities where the archaeological sites are located.

‘Cockney Aristotle’: Hazlitt’s Second Nature

In the early nineteenth century, to insult someone as a ‘Cockney’ (before the term had accrued more cheerful, salt-of-the-earth associations of the Dickensian Sam Weller type) was to cast aspersions not only on their origins, but on their very state of mind. ‘Nature must conspire with accident to make a true Cockney’, Blackwood’s declared in 1823. ‘It is the littleness of soul, the mechanism and mannerism of mind and body contracted from a certain Londonish character, common to all the objects with which they are conversant, that make Cockneys of a description of persons reared in London.’1 This was one of numerous attacks on the Cockney milieu contained in the pages of the conservative Edinburgh magazine, and none were more targeted than the members of what its writers labelled the Cockney School, with particular ridicule directed towards William Hazlitt, the ‘Cockney Aristotle’ or, as he came to be known, ‘pimpled Hazlitt’.2 Mocking his popular lecture series, Blackwood’s commented that ‘Mr Hazlitt cannot look round him at the Surrey, without resting his smart eye on the idiot admiring grin of several dozens of aspiring apprentices and critical clerks.’3 By the time John Gibson Lockhart published ‘Hazlitt Cross-Questioned’ against the ‘ex-painter, theatrical critic, review, essay, and lecture manufacturer [of] London’, the embattled target was ready in the response, penning an unpublished ‘Reply to Z’ in 1818 – in which he protested that ‘I am not pimpled, but remarkably pale and sallow’ – and threatening to sue Blackwood’s for libel in 1823.4

Eye-SCOR: A Supply Chain Operations Reference-Based Framework for Smart Eye Status Monitoring Using System Dynamics Modeling

This work is a unique integration of three different areas, including smart eye status monitoring, supply chain operations reference (SCOR), and system dynamics, to explore the dynamics of the supply chain network of smart eye/vision monitoring systems. Chronic eye diseases such as glaucoma affect millions of individuals worldwide and, if left untreated, can lead to irreversible vision loss. Nearly half of the affected population is unaware of the condition and can be informed with frequent, accessible eye/vision tests. Tonometry is the conventional clinical method used in healthcare settings to determine the intraocular pressure (IOP) level for evaluating the risk of glaucoma. There are currently very few (under development) non-contact and non-invasive methods using smartphones to determine the risk of IOP and/or the existence of other eye-related diseases conveniently at home. With the overall goal of improving health, well-being, and sustainability, this paper proposes Eye-SCOR: a supply chain operations reference (SCOR)-based framework to evaluate the effectiveness of smartphone-based eye status monitoring apps. The proposed framework is designed using system dynamics modeling as a subset of a new causal model. The model includes interaction/activities between the main players and enablers in the supply chain network, namely suppliers/service providers, smartphone app/device factors, customers, and healthcare professionals, as well as cash and information flow. The model has been tested under various scenarios and settings. Simulation results reveal the dynamics of the model and show that improving the eye status monitoring device/app factors directly increases the efficiency/Eye-SCOR level. The proposed framework serves as an important step towards understanding and improving the overall performance of the supply chain network of smart eye/vision monitoring systems.