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Methods
Towards Anti-Stuttering – Understand the Relation between Stuttering and Anxiety Using Emerging Engineering Methods
Sarah Shamsi ([email protected])MS Student in Embedded Electrical & Computer Systems, School of Engineering
Advisor: Dr. Xiaorong Zhang ([email protected])Assistant Professor, School of Engineering
Bibliography
Background
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Preliminary Results
ECG
EMG
ACTUATOR
ECG
EMG
Analyze ECG & EMG signal to detect anxiety and stuttering
moment
Alert Signal
SYNC Microphone & ECG
Stuttering
LA-RA
LL-RA
Mic mV
Samples
ECG mV
150
70
Stutters: 1% of the World’s Population
•Stuttering - a speech disorder, causes still not clear
• Role of Stress, Anxiety & Nervousness unknown.•Autonomic Nervous System(ANS) controls stress & anxiety by activating & deactivating sympathetic & parasympathetic nervous system
•Limitation in current research: 1) Experiments only performed in controllable environments; 2) Existing data analysis methods are relatively simpleResearch Goals• Apply advanced engineering technologies to the stuttering research
• Use emerging wearable technologies and advanced signal processing methods to address the limitations above
• Understand the relations between stuttering, emotion, and physiological changes
• Propose new anti-stuttering assistive method
Methods
ECG• Detects changes in SNS & PNS
• Heart Rate (BPM), Mean R-R interval, RMSSD, SDNN, pNN50, LF, HF, LF/HF parameters can be used.
Brain
FreezeNew speech
Anticipatory Fear
Stuttering
Sensors
ECG
EMG
GSR
ALERT
Preliminary Results
Prior Stuttering During Stuttering
Normal Abnormal
Abnormal ECG pattern in stuttering gives us opportunity to determine
several other parameters in ECG apart from Heart Rate to determine the
changes in the ANS.
Future Work Collect additional data from more subjects and using more sensors such as EMG, GSR
Find unique data features that distinguishes stuttering and non-stuttering and monitors stress level
The ECG, EMG & GSR patterns will be utilized in anti-stuttering assistive device design as the key signs to identify stuttering-related anxiety in real-time.
Integrated with other audio/tactile feedback or biofeedback techniques, the ultimate goal of the assistive device is to eliminate patients’ negative emotional reactions, reduce severity of stuttering, and thus improve the quality of life of people who stutter.
References
CCLSMini Grant
2015
Funded By:
Peters HF, Hulstijn W: Stuttering and anxiety: The difference between stutterers and nonstutterers in verbal apprehension and physiologic arousal during the anticipation of speech and non-speech tasks. Journal of Fluency Disorders 1984, 9:67-84.Alm PA: Stuttering, emotions, and heart rate during anticipatory anxiety: a critical review. Journal of Fluency Disorders 2004, 29:123-133.
Use wearable devices to collect practical data in the subjects’ daily life.
Collect preliminary data from one stuttering subject and three non-stuttering subjects
Develop advanced signal processing, information fusion, and pattern recognition methods to analyze data
No. of samplesNo. of samples No. of samples
No. of samples No. of samples No. of samples
No. of samplesNo. of samplesNo. of samples
HR(bpm)HR (bpm)
ECG (mV) ECG (mV) ECG (mV)
Mic data (mV) Mic data (mV) Mic data (mV)
120
HR (bpm)
EXPERIMENT 1Reading a book
For a listener at home
EXPERIMENT 2Before a public Presentation
EXPERIMENT 3During Presentation in
front of 6 people
90120
