University of Florida Research Foundation, Incorporated

Michigan State University

John Clyde Rosenbek

Rahul Shrivastav

Supraja Anand

Mark D Skowronski

James D Harnsberger

Detection of neurological diseases such as Parkinson's disease can be accomplished through analyzing a subject's speech for acoustic measures based on human factor cepstral coefficients (HFCC). Upon receiving a speech sample from a subject, a signal analysis can be performed that includes identifying articulation range and articulation rate using HFCC and delta coefficients. A likelihood of Parkinson's disease, for example, can be determined based upon the identified articulation range and articulation rate of the speech.

Screening for neurological disease using speech articulation characteristics

Systems and methods of screening for neurological and other diseases utilizing a subject's speech behavior are provided. According to one embodiment, a system is provided that includes an identification device used to determine a health state of a subject by receiving, as input to an interface of the device, one or more speech samples from the subject. The speech samples can be provided to the device by an intentional action of a user or passively due to the device being in the signal path of the subject's speech. The samples are communicated to a processor that identifies the acoustic measures of the samples and compares the acoustic measures of the samples with baseline acoustic measures stored in a memory of the device. The results of this determination can be communicated back to the subject or provided to a third party.

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Gainesville, FL, United States of America

John Clyde Rosenbek