Page 780 - Emerging Trends and Innovations in Web-Based Applications and Technologies

International Journal of Trend in Scientific Research and Development (IJTSRD) @ www.ijtsrd.com eISSN: 2456-6470
 Loss of Peripheral Vision The prevalence of cataracts and associated risk factors in
 Dark or Empty Spots in Vision rural and urban India was extensively studied in 2019. This
research shed light on how socioeconomic conditions and
This proposed device targets to achieve numerous
environmental factors contribute to the progression of
critical objectives:
cataracts. The results emphasized the need for tailored
1. Design a diagnostic system requiring minimal user
approaches to disease detection that consider diverse
interaction or specialized training.
demographic characteristics (2019).
2. Develop a completely non-invasive diagnostic tool that In terms of technical implementation, Amit Yadav's work on
avoids capturing retinal images.
OpenCV-based eye tracking presented a practical framework
3. Ensure high precision in detecting abnormal eye for real-time pupil and eye movement tracking. The study
movement and pupil behavior indicative of specific detailed the step-by-step use of OpenCV to process and
conditions. analyze eye movements, demonstrating its potential for
detecting abnormalities linked to ocular diseases (Yadav,
4. Offer an affordable solution tailored for low-resource
2024).
settings, especially in rural and underserved regions.
The study by Mezer et al. (2015) investigated the impact of
5. Enhance quality of life by enabling early intervention cataracts on eye movement perimetry. The findings showed
and preserving vision.
that cataracts significantly influence eye movement patterns,
By meeting these objectives, your system can bridge the gap suggesting that analyzing such behaviors could serve as an
between advanced medical diagnostics and accessibility, effective diagnostic measure. This research forms the basis
particularly in regions with limited healthcare infrastructure. for incorporating eye movement behavior into our system’s
II. RELATED WORK algorithms.
The use of advanced algorithms for detecting eye diseases McDonald et al. (2020) reviewed eye movement
has shown promise in the field of medical diagnostics. abnormalities in glaucoma patients, presenting a
Numerous studies have explored eye tracking and related comprehensive analysis of how glaucoma disrupts normal
methodologies for predicting and managing eye disorders eye-tracking patterns. The study reinforced the diagnostic
such as cataracts, glaucoma, and diabetic retinopathy. Below, potential of eye-tracking systems for glaucoma detection,
we review relevant literature and research in this domain. providing strong justification for integrating these patterns
into automated systems.
A study focusing on the risk of cataracts and glaucoma
among older adults with diabetes in India analyzed data from The reviewed literature underscores the growing recognition
the LASI Wave-1. The findings revealed a significant of eye tracking as a vital tool for early diagnosis and
correlation between diabetes and the prevalence of these management of ocular diseases. Our proposed system builds
ocular diseases, particularly in older populations. The study upon these advancements, leveraging real-time eye tracking
highlighted the critical need for early detection and to detect abnormalities in eye movement and pupil size. By
management strategies, especially in resource-constrained addressing the limitations in existing methods and focusing
settings where such diseases are prevalent (LASI Wave-1, on scalability, we aim to provide a low-cost, non-invasive
2023). diagnostic solution tailored to the healthcare challenges in
India.
Another significant contribution is the Chennai Urban Rural
Epidemiology Study (CURES Eye Study), which examined the III. PROPOSED WORK
prevalence of diabetic retinopathy in urban India. The study To facilitate early detection of eye disorders such as
underscored the increasing burden of this condition in urban cataracts, glaucoma, and diabetic retinopathy, the proposed
populations, emphasizing the importance of timely and cost- system will conduct a series of non-invasive tests. This
effective diagnostic solutions. The findings from this comprehensive assessment will utilize advanced eye tracking
research support the integration of non-invasive technology to gather data on various visual functions. The
technologies to address the growing demand for diabetic framework for this system is illustrated in Fig. 1, showcasing
retinopathy detection (CURES Eye Study, 2010). the integration of machine learning techniques to analyze the
collected data.

Fig. 1. The flow of proposed work

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