학술논문
Speech-Based Dementia Classification for FTLD Diagnosis Support
Document Type
Conference
Author
Source
2021 IEEE 3rd Global Conference on Life Sciences and Technologies (LifeTech) Life Sciences and Technologies (LifeTech), 2021 IEEE 3rd Global Conference on. :344-346 Mar, 2021
Subject
Language
Abstract
This paper proposes a screening system to automatically detect a Frontotemporal Lobar Degeneration (FTLD) and support a diagnosis of a general practitioner. Dementia results from a variety of diseases that primarily or secondarily affect the brain. It is important to diagnose an underlying disease correctly. We have been investigating FTLD, which is one of diseases. We took into account the specific symptoms, used speech features to classify FTLD, Alzheimer's disease (AD) and healthy control (HC). We confirmed that our method can classify three groups with accuracy of 0.84 and macro F-measure of 0.79. We also showed the effectiveness of linguistic features in FTLD detection.