Alzheimer Speech Signal Analysis of Persian speaking Alzheimer's patients

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

Rahmani Mahdiyeh; MOMENI MARYAM

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: COMPUTATIONAL INTELLIGENCE IN ELECTRICAL ENGINEERING (INTELLIGENT SYSTEMS IN ELECTRICAL ENGINEERING) Year:2020 | Volume:11 | Issue:1 Page(s): 81-94

Download Full-Text

Persian Verion

View:

837

Download:

Cites:

Information Journal Paper

Title

Alzheimer Speech Signal Analysis of Persian speaking Alzheimer's patients

Author(s)

Rahmani Mahdiyeh | MOMENI MARYAM | Issue Writer Certificate

Keywords

Alzheimer's diseaseQ1

Speech SignalQ2

Discrete Wavelet TransformQ1

Support Vector MachineQ2

Abstract

Alzheimer's is a type of brain dementia that gradually reduces mental abilities of the patient. The lack of memory, decision-making disorder, and mistakes in choosing the correct vocabulary are the early symptoms of Alzheimer's disease. Therefore, extensive studies have been conducted on the diagnosis of Alzheimer's disease using the noninvasive Speech Signal recognition method. Identifying of Alzheimer's disease is dependent on culture and language, speech content, gender, age, accent, and many other factors. Therefore, Alzheimer's Speech Signal has been studied in various languages. The purpose of this paper is to recognize Alzheimer's patients from healthy people by the use of their Speech Signal processing in Persian using the combination of time, frequency, and frequency-temporal features. In this paper, after pre-processing, the speech features extracted using the wavelet packet as a frequency-temporal feature next to Mel frequency Cepstral coefficients, zero crossing rate, spectral roll off, band width, root mean square and spectral centroid frequency. Finally, the extracted features have been classified by the Support Vector Machine which achieves recognition precision of 96% on Persian healthy and Alzheimer's speaker experiments. The acceptable results demonstrate the applicability of the proposed non-invasive and low-cost algorithm for the diagnosis of Persianspeaking Alzheimer's patients.

Cites

No record.

References

No record.

Cite

APA: Copy

Rahmani, Mahdiyeh, & MOMENI, MARYAM. (2020). Alzheimer Speech Signal Analysis of Persian speaking Alzheimer's patients. COMPUTATIONAL INTELLIGENCE IN ELECTRICAL ENGINEERING (INTELLIGENT SYSTEMS IN ELECTRICAL ENGINEERING), 11(1 ), 81-94. SID. https://sid.ir/paper/203105/en

Vancouver: Copy

Rahmani Mahdiyeh, MOMENI MARYAM. Alzheimer Speech Signal Analysis of Persian speaking Alzheimer's patients. COMPUTATIONAL INTELLIGENCE IN ELECTRICAL ENGINEERING (INTELLIGENT SYSTEMS IN ELECTRICAL ENGINEERING)[Internet]. 2020;11(1 ):81-94. Available from: https://sid.ir/paper/203105/en

IEEE: Copy

Mahdiyeh Rahmani, and MARYAM MOMENI, “Alzheimer Speech Signal Analysis of Persian speaking Alzheimer's patients,” COMPUTATIONAL INTELLIGENCE IN ELECTRICAL ENGINEERING (INTELLIGENT SYSTEMS IN ELECTRICAL ENGINEERING), vol. 11, no. 1 , pp. 81–94, 2020, [Online]. Available: https://sid.ir/paper/203105/en

Related Journal Papers