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Transactions on Computational Collective Intelligence XVII pp 272–281Cite as

On the Alzheimer’s Disease Diagnosis: Automatic Spontaneous Speech Analysis

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Part of the book series: Lecture Notes in Computer Science ((TCCI,volume 8790))

Abstract

Alzheimer’s disease (AD) is the most prevalent form of progressive degenerative dementia and it has a high socio-economic impact in Western countries therefore is one of the most active research areas today. Its diagnosis is sometimes made by excluding other dementias and definitive confirmation must be done through a post-mortem study of the brain tissue of the patient. The purpose of this paper is to contribute to the improvement of early diagnosis of AD and its degree of severity from an automatic analysis performed by non-invasive intelligent methods. The methods selected in this case are Automatic Spontaneous Speech Analysis (ASSA) and Emotional Temperature (ET) that have the great advantage of being non invasive low cost and without any side effects. The developed system obtains hopeful results for early diagnosis.

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References

  1. Mc Kahn, G., Drachman, D., Folstein, M., Katzman, R., Price, D., Stadlan, E.M.: Clinical diagnosis of Alzheimer’s disease: report of the NINCDS-ADRDA Workgroup on Alzheimer’s disease, 24, pp. 939–944 (1984)

    Google Scholar 

  2. McKhann, G.M., Knopman, D.S., Chertkow, H., Hyman, B.T., Jack Jr., C.R., Kawas, C.H., Klunk, W.E., Koroshetz, W.J., Manly, J.J., Mayeux, R., Mohs, R.C., Morris, J.C., Rossor, M.N., Scheltens, P., Carrillo, M.C., Thies, B., Weintraub, S., Phelps, C.H.: The diagnosis of dementia due to Alzheimer’s disease: Recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease (PDF). Alzheimers Dement. 7(3), 263–269 (2011)

    Article  Google Scholar 

  3. Van de Pole, L.A., et al.: The effects of age and Alzheimer’s disease on hippocampal volumes, a MRI study. Alzheimer’s Dement. 1(1, Supplement 1), 51 (2005)

    Article  Google Scholar 

  4. Morris, J.C.: The Clinical Dementia Rating (CDR): current version and scoring rules. Neurology 43, 2412b–2414b (1993)

    Article  Google Scholar 

  5. American Psychiatric Association: Diagnostic and Statistical Manual of Mental Disorders, 4th edn., Text Revision. American Psychiatric Association, Washington DC (2000)

    Google Scholar 

  6. Cristian, B.: Evaluación y tratamiento de los trastornos del lenguaje, Psicóloga. Gerontóloga. Unidad de Memoria y Alzheimer. Matia Fundazioa, Donostia (2010)

    Google Scholar 

  7. Martinez, F., Garcia, J., Perez, E., Carro, J., Anara, J.M.: Patrones de Prosodia expresiva en pacientes con enfermedad de Alzheimer. Psicothema 24(1), 16–21 (2012)

    Google Scholar 

  8. Shimokawa, A., Yatomi, N., Anamizu, S., Torii, S., Isono, H., Sugai, Y., Kohno, M.: Influence of deteriorating ability of emotional comprehension on interpersonal behaviour in Alzheimer-type dementia. Brain Cogn. 47, 423–433 (2001)

    Article  Google Scholar 

  9. Goodkind, M.S., Gyurak, A., McCarthy, M., Miller, B.L., Levenson, R.W.: Emotion regulation deficits in frontotemporal lobar degeneration and Alzheimer’s disease. Psychol Aging., 25(1):30–37, Mar 2010. PMID, 20230125, PMCID: PMC2841311

    Google Scholar 

  10. Cadieux, N., Greeve, K.: Emotion processing in Alzheimer’s disease. J. Int. Neuropsychol. Soc. 3, 411–419 (1997). The International Neuropsychological Society. DOI: (About DOI) Published online: 2000

    Google Scholar 

  11. Knapp, M.L.: Essentials of Nonverbal Communication. Holt, Rinehart & Winston, New York (1980)

    Google Scholar 

  12. Cowie, E., et al.: Emotion recognition in human-computer interaction. IEEE Signal Process. Mag. 18(1), 32–80 (2001)

    Article  Google Scholar 

  13. Plutchnik, R.: Emotion: A Psychoevolutionary Synthesis’. Harper and Row, New York (1980)

    Google Scholar 

  14. Lopez-de-Ipiña, K., Alonso, J.B., Travieso, C.M., Solé-Casals, J., Egiraun, H., Faundez-Zanuy, M., Ezeiza, A., Barroso, N., Ecay, M., Martinez-Lage, P., Martinez-de-Lizardui, U.: On the selection of non-invasive methods based on speech analysis oriented to Automatic Alzheimer Disease Diagnosis. Sensors 13(5), 6730–6745 (2013)

    Article  Google Scholar 

  15. Faúndez Zanuy, M., Sesa-Nogueras, E., Monte-Moreno, E., Garre-Olmo, J., Lopez-de-Ipiña, K., Viñals, F., Luz Puente, M.: Aplicaciones biométricas más allá de la seguridad. In: VI Jornadas de reconocimiento biométrico de personas, Las Palmas de Gran Canaria, pp. 25–43, 26–27 January 2012. ISBN 978-84-695-0695-0

    Google Scholar 

  16. López de Ipiña, K., Alonso, J.B., Solé-Casals, J., Barroso, N., Faundez, M., Ecay, M., Travieso, C., Ezeiza, A., Estanga, A.: Alzheimer disease diagnosis based on automatic spontaneous speech analysis. In: Proceedings of NCTA 2012, Barcelona (2012)

    Google Scholar 

  17. Pao, T.L., Chien, C.S., Yen, J.H., Chen, Y.T., Cheng, Y.M.: Continuous tracking of user emotion in mandarin emotional speech. In: Proceedings, 3th International Conference on International Information Hiding and Multimedia Signal Processing (IIH-MSP’07), pp. 1:47–1:52 (2007)

    Google Scholar 

  18. Petrushin, V.A.: Emotion in speech: recognition and application to call centers. In: Proceedings, Conference on Artificial Neural Networks in Engineering (ANNIE), pp. 7–10 (1999)

    Google Scholar 

  19. Lee, C.M., Narayanan, S.: Emotion recognition using a data-driven fuzzy interference system. In: Proceedings, 8th ECSCT, pp. 157–160 (2003)

    Google Scholar 

  20. Kwon, O.W., Chan, K., Hao, J., Lee, T.W.: Emotion recognition by speech signals. In: 8th European Conference on Speech Communication and Technology, 125–128 (2003)

    Google Scholar 

  21. De Cheveigné, A., Kawahara, H.: YIN, a fundamental frequency estimator for speech and music. J. Acoust. Soc. Am. 111(4), 1917–1930 (2002)

    Article  Google Scholar 

  22. Alonso, J., De León, J., Alonso, I., Ferrer, M.A.: Automatic detection of pathologies in the voice by HOS base parameters. Journal on Applied Signal Processing 4, 275–284 (2001)

    Article  Google Scholar 

  23. WEKA. http://www.cs.waikato.ac.nz/ml/weka/

  24. Picard, R., Cook, D.: Cross-validation of regression models. J. Am. Stat. Assoc. 79(387), 575–583 (1984)

    Article  MATH  MathSciNet  Google Scholar 

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Acknowledgements

This work has been partially supported by SAIOTEK from the Basque Government. Dr. Solé-Casals also acknowledges the partial support of the University of Vic under the research grant R0904 and by the Spanish Ministerio de Ciencia e Innovación TEC2012-38630-C04-03.

Author information

Authors and Affiliations

  1. System Engineering and Automation Department, University of the Basque Country, 20008, Donostia, Spain

    K. Lopez-de-Ipiña

  2. Data and Signal Processing Research Group, University of Vic, Barcelona, Spain

    J. Solé-Casals

  3. Universidad de Las Palmas de Gran Canaria, IDeTIC, Las Palmas, Spain

    J. B. Alonso & C. M. Travieso

  4. Neurology Department CITA-Alzheimer Foundation, Donostia, Spain

    M. Ecay & P. Martinez-Lage

Authors
  1. K. Lopez-de-Ipiña
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  2. J. Solé-Casals
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  3. J. B. Alonso
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  4. C. M. Travieso
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  5. M. Ecay
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  6. P. Martinez-Lage
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Corresponding author

Correspondence to K. Lopez-de-Ipiña .

Editor information

Editors and Affiliations

  1. Institute of Informatics, Wrocław University of Technology, Wrocław, Poland

    Ngoc Thanh Nguyen

  2. Swinburne University of Technology, Melbourne, Australia and Polish Academy of Sciences, Warsaw, Poland

    Ryszard Kowalczyk

  3. Technical University of Lisbon, Lisbon, Portugal

    Ana Fred

  4. Polytechnic Institute of Sétubal, Sétubal, Portugal

    Filipe Joaquim

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Lopez-de-Ipiña, K., Solé-Casals, J., Alonso, J.B., Travieso, C.M., Ecay, M., Martinez-Lage, P. (2014). On the Alzheimer’s Disease Diagnosis: Automatic Spontaneous Speech Analysis. In: Nguyen, N., Kowalczyk, R., Fred, A., Joaquim, F. (eds) Transactions on Computational Collective Intelligence XVII. Lecture Notes in Computer Science(), vol 8790. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-44994-3_14

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  • DOI: https://doi.org/10.1007/978-3-662-44994-3_14

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-44993-6

  • Online ISBN: 978-3-662-44994-3

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