Cognitive Behavior and Human Computer Interaction Based on Machine Learning Algorithms

15Application of Artificial Intelligence and Computer Vision to Identify Edible Bird’s Nest

Weng Kin Lai^1*, Mei Yuan Koay¹, Selina Xin Ci Loh², Xiu Kai Lim¹ and Kam Meng Goh¹

¹Department of Electrical & Electronics Engineering, Faculty of Engineering & Technology, Tunku Abdul Rahman University College, Setapak, Kuala Lumpur, Malaysia

²Department of Mechanical Engineering, Faculty of Engineering & Technology, Tunku Abdul Rahman University College, Setapak, Kuala Lumpur, Malaysia

*Corresponding author: [e-mail]

Abstract

Cognitive disability is a common feature associated with a variety of neurological disorders which have increasingly been recognised as major causes of death and disability worldwide. Feigin and Theo in their 2019 study had shown that globally, neurological disorders were the leading cause of disability-adjusted life-years (DALY) and the second leading cause of deaths [1]. There is now evidence that demonstrated neuroinflammation plays an important role in the development of cognitive impairment [2]. However, current available therapies are relatively ineffective in treating or preventing such neurological disorders, thus representing an important, unfulfilled medical need. Hence, developing potential treatment is one of the major areas of research interest.

Edible bird’s nests (EBNs) are nests formed from the saliva of swiftlets commonly found in South East Asia. They contain sialic acid which is believed to improve brain function. A recent study by ...