A Comprehensive Review of Advancement in Speech-Based Approach for Alzheimer Disease Detection in India

Abstract

Alzheimer’s Disease (AD), accounting for 60%-70% of dementia cases, is poised to afflict India as the second-largest country by mid-century, as indicated by a recent World Health Organization (WHO) study. The socio-economic landscape in India presents unique challenges, with a population that may not be adequately educated on allocating resources for healthcare beyond the age of 60, especially for conditions like Alzheimer's, which currently lacks a definitive cure. Addressing this impending health crisis necessitates innovative, early diagnosis and cost-effective solutions. This comprehensive review paper explores the potential of utilizing speech data analysis for the early detection of Alzheimer’s Disease (AD), offering a pragmatic approach to mitigate the severity of cases. By harnessing speech data, the aim is to diagnose the condition in its early stages, minimizing costs and enabling timely interventions to impede its progression. Early diagnosis is paramount, as it opens doors to effective treatments and preventative measures. The paper systematically reviews various processes involved in developing a mathematical model for the early detection of Alzheimer’s Disease (AD). It delves into key aspects such as data collection methodologies, pre-processing techniques, feature extraction methods, and diverse classifiers. The intention is to provide a thorough understanding of the intricacies involved in creating an accurate and reliable model for early Alzheimer's detection. In light of Alzheimer’s Disease (AD) representing a substantial majority of dementia cases, this review paper serves as a valuable resource for researchers, healthcare professionals, and policymakers. It fosters a deeper comprehension of potential avenues for leveraging speech data specifically in the context of Alzheimer's. As we confront the impending surge in Alzheimer's cases in India, this comprehensive review work contributes to the foundation of knowledge needed to develop scalable and accessible solutions, making a substantial impact on public health.