1. Identification of Cough and Speech
Submitted by :
Saurabh Singh( 10-1-6-022)
Abhijay Kumar (10-1-6-018)
Madhu Shalini (10-1-6-019)
2. How we started
1. We learned about the present day technologies
a) Band Pass Filter :
Technology:
(i) Acquire signal (using unidirectional microphone)
(ii) Processing signal for cough detection (pass signal through band pass
filter 30Hz-100Hz.
(iii) Output result ( using display device )
Advantage – Design was easy to implement
Disadvantage – was not able to eliminate noise; unidirectional microphone
had short range.
b) Hull Automatic Cough counter :
Technology:
(i) Acquired signal sent to artificial neural network
detection of cough events
3. How we started ….
(ii) Signal processing of sound event was used to identify
characteristics of both cough and non cough events.
(iii) Probabilistic neural network was finally used to classify cough and
non cough sound events
Advantage – Sensitivity of 80% was achieved
Disadvantage – was not very accurate.
2. We progressed the model with minor changes.
Technology : signal processing of sound event resulted in
quantification of cough that was based on hit and trial method.
3
13. Limitations of our Project
• Was not able to analyze the spectrogram of sound signal, since it
required the deep understanding of Image Processing techniques.
• There might still exist many unexplored characteristics that can
define a relation between cough and speech
• Was not able to do the hardware implementation of our research.13
14. Conclusion
• We believe that our research will play an important
role in developing a full-fledged Electronic Cough
monitoring system.
• Ours is a very small but sincere effort towards
exploring the possibility of sound based wearable
techniques for long duration respiratory disorder
monitoring.
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15. Future work proposed
1. Identify more characteristics of cough and speech to differentiate
between the two using signal processing.
2. Use of machine learning to separate cough and speech from each
other.
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16. References•
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• Fontana GA, Widdicombe J. What is cough and what should be measured?.Pulm Pharmacol Ther 2007;20:307–
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sensitivity and subjective assessments correlate with objective cough counts during ambulatory
monitoring?.Thorax 2007;62:329–334
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pulmonary exacerbations in adults with cystic fibrosis. Thorax 2006;61:425–429.
• .Musaab Hassan, Asiel Satti, Azza Hussien , Tarteel Tag El-Din:Electronic Cough Monitoring:
• A.Kelsall ,S.Decalmer ,D.Webster ,N.Brown ,A. Woodcock and J.Smith. How to quantify coughing: correlations
with quality of life in chronic cough. February 20,2008, doi:10.1183/09031936.00101307
• Thomas Drugman, Jerome Urbain, Nathalie Bauwens, Ricardo Chessini, Carlos Valderrama, Patrick Lebecque,
and Thierry Dutoit. Objective Study of Sensor Relevance for Automatic cough Detection. IEEE Journal of
biomedical and health Information, Vol.17, No.3, MAY 2013
• Samantha J Barry, Adrie D Dane, Alyn H Morice and Anthony D Walmsley:The automatic recognition and
counting of cough:10.1186/1745-9974-2-8:2006
• en.wikipedia.org
• http://www.physionet.org/physiotools/sampen/
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