Machine learning powered smart Visual-Spatial Agnosia assistive device

Abstract

"Visual-spatial agnosia is a neurological visual impairment disorder that occurs after brain strokes in elderly people. These patients are unable to recognise objects surrounding them and also they cannot pursue the distance of the object. This creates a huge barrier between the real world and the world they perceive. This study proposes a smart eyewear assistive device that will help patients recognize the object as well as guide the patient toward the object by showing the distance of the object with the help of machine learning algorithms. A stereo vision algorithm is used to estimate the distance along with the Yolov11 algorithm that detects the objects. Physical data has been recorded to analyze the models’ performance with the Yolov11 algorithm with stereo vision algorithm. This study also proposes future works in this area. "

Description

Cataloged from PDF version of final year design project.
Includes bibliographical references (pages 90-92).
This final year design project is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Electrical and Electronic Engineering, 2024.

Keywords

Visual-spatial agnosia, Neurological disorder, Yolov11, Stereo vision algorithm, Object detection

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