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)

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

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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 replicated the model with minor changes. Technology : signal processing of sound event resulted in quantification of cough that was based on hit and trial method.

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Future work proposed during last semester

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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Outline of our Project

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Work Plan

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1. Frequency spectrum analysis

Fig : Pseudo Code used for frequency spectrum analysis

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Frequency spectrum analysis..

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2. Power Spectral Analysis

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Zero Crossing Rate Analysis..

Fig: Algorithm used for calculation of ZCR

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3. Zero Crossing Rate Analysis

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4. Sample entropy Analysis

Fig : Algorithm used for calculation of sample entropy

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Sample entropy Analysis..

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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.

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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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References•  

• Korpás J, Sadlonová J, Vrabec M. Analysis of the cough sound: an overview. Pulm Pharmacol 1996;9:261–268• Fontana GA, Widdicombe J. What is cough and what should be measured?.Pulm Pharmacol Ther 2007;20:307–312• Decalmer S, Webster D, Kelsall A, McGuinness K, Woodcock A, Smith J. Chronic cough: how do cough reflex sensitivity

and subjective assessments correlate with objective cough counts during ambulatory monitoring?.Thorax 2007;62:329–334

• .Smith J, Owen E, Earis J, Woodcock A. Effect of codeine on objective measurement of cough in chronic obstructive pulmonary disease. J Allergy Clin Immunol 2006;117:831–835

• .Smith J, Owen E, Earis J, Woodcock A. Cough in COPD: correlation of objective monitoring with cough challenge and subjective assessments.Chest 2006;130:379–385.

• .Smith JA, Owen EC, Jones AM, Dodd ME, Webb AK, Woodcock A. Objective measurement of cough during 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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Thank You