The purpose of this project is advance the assessment and treatment of speech motor impairments due to ALS using novel computer-based approaches. Recently developed speech movement tracking technology will be used to record movements of tongue, lips, and jaw in 50 persons with ALS and 50 healthy control participants. The speech movement data will be analyzed using custom machine learning algorithms to address three important translational needs in person with ALS: improved early detection of speech motor involvement, improved progress monitoring of speech motor decline, and improved options for maintaining oral communication. The established interdisciplinary team with expertise in data mining, speech- language pathology, clinical neurology, and spatial statistics are well positioned to conduct this research. If successful, the specific aims have the potential to transform clinical practice for speech-language pathologists, neurologists, and other related health care professionals. The propose research will enhance human health by making an impact on individuals with speech motor impairment due to ALS and potentially to a broad range of other speech motor due to stroke, traumatic brain injury, multiple sclerosis, Parkinson's disease, cerebral palsy, traumatic brain injury, and orofacial or laryngeal cancer.

Public Health Relevance

ALS is one of the most common motor neuron diseases. According to the National Institute of Neurological Disorders and Stroke, approximately 30,000 Americans are living with ALS (NINDS, 2003). Recent evidence suggests ALS incidence is increasing in the general population (Strong & Rosenfeld, 2003), particularly among Gulf War veterans who are nearly twice as likely to develop the disease as veterans not deployed to the Gulf (Haley, 2003). This project is focused on the development and validation of novel machine-learning based tools for improving the assessment and treatment of patients with speech motor impairments due to ALS. If successful, this research may (1) improve early detection and prognostic accuracy, (2) and address the critical need for objective outcome measures for ongoing experimental drug trials, and (3) provide information to develop a novel oral communication device for persons with moderate to severe speech impairment. These developments may ameliorate the socioeconomic burden of speech motor impairments as well as the quality of life for these patients, their families, and the people they closely interact wit.

Agency
National Institute of Health (NIH)
Institute
National Institute on Deafness and Other Communication Disorders (NIDCD)
Type
Research Project (R01)
Project #
5R01DC013547-05
Application #
9390468
Study Section
Motor Function, Speech and Rehabilitation Study Section (MFSR)
Program Officer
Shekim, Lana O
Project Start
2013-12-01
Project End
2018-11-30
Budget Start
2017-12-01
Budget End
2018-11-30
Support Year
5
Fiscal Year
2018
Total Cost
Indirect Cost
Name
Mgh Institute of Health Professions
Department
Type
DUNS #
605122258
City
Boston
State
MA
Country
United States
Zip Code
02129
Cordella, Claire; Dickerson, Bradford C; Quimby, Megan et al. (2017) Slowed articulation rate is a sensitive diagnostic marker for identifying non-fluent primary progressive aphasia. Aphasiology 31:241-260
Shellikeri, S; Karthikeyan, V; Martino, R et al. (2017) The neuropathological signature of bulbar-onset ALS: A systematic review. Neurosci Biobehav Rev 75:378-392
Shokoohi-Yekta, Mohammad; Hu, Bing; Jin, Hongxia et al. (2017) Generalizing DTW to the multi-dimensional case requires an adaptive approach. Data Min Knowl Discov 31:1-31
Allison, Kristen M; Yunusova, Yana; Campbell, Thomas F et al. (2017) The diagnostic utility of patient-report and speech-language pathologists' ratings for detecting the early onset of bulbar symptoms due to ALS. Amyotroph Lateral Scler Frontotemporal Degener 18:358-366
Wang, Jun; Kothalkar, Prasanna V; Kim, Myungjong et al. (2016) Predicting Intelligible Speaking Rate in Individuals with Amyotrophic Lateral Sclerosis from a Small Number of Speech Acoustic and Articulatory Samples. Workshop Speech Lang Process Assist Technol 2016:91-97
Rong, Panying; Yunusova, Yana; Wang, Jun et al. (2016) Predicting Speech Intelligibility Decline in Amyotrophic Lateral Sclerosis Based on the Deterioration of Individual Speech Subsystems. PLoS One 11:e0154971
Yunusova, Yana; Graham, Naida L; Shellikeri, Sanjana et al. (2016) Profiling Speech and Pausing in Amyotrophic Lateral Sclerosis (ALS) and Frontotemporal Dementia (FTD). PLoS One 11:e0147573
Wang, Jun; Samal, Ashok; Rong, Panying et al. (2016) An Optimal Set of Flesh Points on Tongue and Lips for Speech-Movement Classification. J Speech Lang Hear Res 59:15-26
Simione, Meg; Wilson, Erin M; Yunusova, Yana et al. (2016) Validation of Clinical Observations of Mastication in Persons with ALS. Dysphagia 31:367-75
Shellikeri, Sanjana; Green, Jordan R; Kulkarni, Madhura et al. (2016) Speech Movement Measures as Markers of Bulbar Disease in Amyotrophic Lateral Sclerosis. J Speech Lang Hear Res 59:887-899

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