Abstract
As the age of the human population increases worldwide, depression in elderly patients has become a problem in medical care. In this study, we analyzed voice-emotion component data, attribute data, and Beck Depression Inventory (BDI) scores by multivariate analysis, particularly in the elderly, and proposed evaluation indicators for estimating the state of depression of elderly patients. We divided the data into two groups according to BDI scores: a state of depression and the absence of this state. The labels distinguishing the two groups were dependent variables, while the voice-emotion component and attribute information were set as independent variables, and we performed logistic regression analysis on the data. We obtained a prediction model with significantly sufficient fitness. In the receiver operating characteristic curve for the proposed depression evaluation indicator, a sorting performance with an area under the curve of approximately 0.93 was obtained.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Acharya, U.R., Sudarshan, V.K., Adeli, H., Santhosh, J., Koh, J.E., Puthankatti, S.D., Adeli, A.: A novel depression diagnosis index using nonlinear features in EEG signals. Eur. Neurol. 2015 74(1–2), 79–83 (2015)
Agresti, A.: Categorical Data Analysis 3rd Edition, 3rd edn. Wiley-Interscience, Hoboken (2012)
Diagnostic and statistical manual of mental disorders IV. American Psychiatric Association (1994)
Beck, A.T., Ward, C.H., Mendelson, M., Mock, J., Erbaugh, J.: An inventory for measureing depression. Arch. Gen. Psychiatry 4(6), 561–571 (1961)
Beck, A.T., Steer, R.A., Brown, G.K.: Manual for the beck depression inventory-II. Psychological Corporation, San Antonio (1996)
Beekman, A.T., Copeland, J.R., Prince, M.J.: Review of community prevalence of depression in later life. Br. J. Psychiatry 174(4), 307–311 (1999)
Carney, C.E., Ulmer, C., Edinger, J.D., Krystal, A.D., Knauss, F.: Assessing depression symptoms in those with insomnia: an examination of the beck depression inventory second edition (BDI-II). J. Psychiatr. Res. 43(5), 576–582 (2009)
Delgado-Rodriguez, M., Llorca, J.: Bias. J. Epidemiol. Community Health 58(8), 635–641 (2004)
Fisher, R.A.: On the interpretation of \(\chi ^2\) from contingency tables, and the calculation of P. J. Roy. Stat. Soc. 85(1), 87–94 (1922)
Garcia, R.G., Valenza, G., Tomaz, C.A., Barbieri, R.: Instantaneous bispectral analysis of heartbeat dynamics for the assessment of major depression. In: Computing in Cardiology 2015, Nice, pp. 781–784 (2015)
Goldberg, D.P.: Manual of the General Health Questionnaire. NFER Publishing, Windsor (1978)
Hagiwara, N., Omiya, Y., Shinohara, S., Nakamura, M., Yasunaga, H., Higuchi, M., Mitsuyoshi, S., Tokuno, S.: Validity of the mind monitoring system as a mental health indicator. In: Proceedings of IEEE 16th International Conference on BioInformatics and BioEngineering, Taichung (2016)
Hagiwara, N., Omiya, Y., Shinohara, S., Nakamura, M., Higuchi, M., Mitsuyoshi, S., Yasunaga, H., Tokuno, S.: Validity of mind monitoring system as a mental health indicator using voice. Adv. Sci. Technol. Eng. Syst. J. 2(3), 338–344 (2017)
Higuchi, M., Shinohara, S., Nakamura, M., Omiya, Y., Hagiwara, N., Mitsuyoshi, S., Tokuno, S.: Study on depression evaluation indicator in the elderly using sensibility technology. In: Proceedings of the 3rd International Conference on Information and Communication Technologies for Ageing Well and e-Health, Porto, pp. 70–77 (2017)
Izawa, S., Sugaya, N., Shirotsuki, K., Yamada, K.C., Ogawa, N., Ouchi, Y., Nagano, Y., Suzuki, K., Nomura, S.: Salivary dehydroepiandrosterone secretion in response to acute psychosocial stress and its correlations with biological and psychological changes. Biol. Psychol. 79(3), 294–298 (2008)
Jan, A., Meng, H., Gaus, Y.F.A., Zhang, F., Turabzadeh, S.: Automatic depression scale prediction using facial expression dynamics and regression. In: Proceedings of the 4th International Workshop on Audio/Visual Emotion Challenge, Orlando, pp. 73–80 (2014)
Kalender, B., Ozdemir, A.C., Koroglu, G.: Association of depression with markers of nutrition and inflammation in chronic kidney disease and end-stage renal disease. Nephron Clin. Pract. 102(3–4), c115–121 (2006)
Kaplan, H.I., Sadock, B.J., Greb, J.A.: Synopsis of Psychiatry, 7th edn. Williams & Willkins, Baltimore (1994)
Katon, W.J.: Clinical and health services relationships between major depression, depressive symptoms, and general medical illness. Biol. Psychiatry 54(3), 216–226 (2003)
Omiya, Y., Hagiwara, N., Shinohara, S., Nakamura, M., Mitsuyoshi, S., Tokuno, S.: Development of mind monitoring system using call voice. In: Proceedings of Neuroscience 2016, San Diego (2016)
Mann, H.B., Whitney, D.R.: On a test of whether one of two random variables is stochastically larger than the other. Ann. Math. Stat. 18(1), 50–60 (1947)
Mitsuyoshi, S.: Development of verbal analysis pathophysiology. Econophysics Sociophysics Other Multi. Sci. J. 5(1), 11–16 (2015)
Sekiyama, A.: Interleukin-18 is involved in alteration of hipothalamic-pituitary-adrenal axis activity by stress. In: Society of Biological Psychiatry Annual Meeting, San Diego (2007)
Shinohara, S., Mitsuyoshi, S., Nakamura, M., Omiya, Y., Tsumatori, G., Tokuno, S.: Validity of a voice-based evaluation method for effectiveness of behavioural therapy. In: Serino, S., Matic, A., Giakoumis, D., Lopez, G., Cipresso, P. (eds.) MindCare 2015. CCIS, vol. 604, pp. 43–51. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-32270-4_5
Spearman, C.: The proof and measurement of association between two things. Am. J. Psychol. 15(1), 72–101 (1904)
Steel, R.G.D.: A rank sum test for comparing all pairs of treatments. Technometrics 2, 197–207 (1960)
Tokuno, S., Mitsuyoshi, S., Suzuki, G., Tsumatori, G.: STRESS EVALUATION BY VOICE: a novel stress evaluation technology. In: The 9th International Conference on Early Psychosis, Tokyo, pp. 17–19 (2014)
World Population Ageing: 1950–2050. United Nations Population Division (n.d.)
Acknowledgements
This research is (partially) supported by the Center of Innovation Program from Japan Science and Technology Agency, JST. This work was supported by JSPS KAKENHI Grant Numbers JP15H03002 and JP17K01404.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG, part of Springer Nature
About this paper
Cite this paper
Higuchi, M. et al. (2018). Study on Indicators for Depression in the Elderly Using Voice and Attribute Information. In: Röcker, C., O’Donoghue, J., Ziefle, M., Maciaszek, L., Molloy, W. (eds) Information and Communication Technologies for Ageing Well and e-Health. ICT4AWE 2017. Communications in Computer and Information Science, vol 869. Springer, Cham. https://doi.org/10.1007/978-3-319-93644-4_7
Download citation
DOI: https://doi.org/10.1007/978-3-319-93644-4_7
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-93643-7
Online ISBN: 978-3-319-93644-4
eBook Packages: Computer ScienceComputer Science (R0)