NDLI: Portable neurological disease assessment using temporal analysis of speech

Content Provider	ACM Digital Library
Author	Yadav, Nikhil Poellabauer, Christian McQuillan, Shane Daudet, Louis Collins, Tomás Flynn, Patrick
Abstract	This paper discusses and evaluates the extraction and analysis of temporal acoustic features from speech using mobile devices to detect patterns which could be indicative of neurodegenarative diseases. Timing information in speech can play a critical role in future portable applications that help detect the presence of speech disorders, which are often indicators of a more serious underlying neurological condition. Speech data collected from a series of mobile administered speech tests at 47 high schools and colleges in the the Mid-western United States are analyzed for the specific case of mild traumatic brain injuries (mTBI). In this paper, we focus on both the system and test design used to collect and extract temporal metrics from the speech data, as well as the statistical analysis of this data to find patterns that are indicative of a concussion. Preliminary results suggest a correlation between certain temporal features and the likelihood of a concussion.
Starting Page	77
Ending Page	85
Page Count	9
File Format	PDF
ISBN	9781450338530
DOI	10.1145/2808719.2808727
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2015-09-09
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Speech analysis Concussions Voice pathology Portable diagnostics
Content Type	Text
Resource Type	Article

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Portable neurological disease assessment using temporal analysis of speech