Analiza mowy jako narzędzie diagnozy chorób neurodegeneracyjnych

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analiza mowy
choroby neurodegeneracyjne

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Jankowska , K. (2022). Analiza mowy jako narzędzie diagnozy chorób neurodegeneracyjnych. Investigationes Linguisticae, 45, 83–92.


Objective: The aim of the work is to compare the results of research on the oral language of people with neurodegenerative diseases. On the basis of literature, research results and available information, research methodologies in the subject and test results are presented. Speech variables that have been considered in the studies were presented, including linguistic, phonetic and phonological features, prosodic, acoustic, lexical, semantic, syntactic and morpho-syntactic features. Material and methods: A comprehensive review and analysis of literature, articles in peer-reviewed journals, in the field of language disorders resulting from brain damage resulting from neurodegenerative diseases. Conclusions: Studies show that the speech analysis is a crucial diagnosis tool, which can be used for early neurodegenerative changes recognition. No such studies have been carried out in the Polish language so far.


Ahmed, S., d. J. C., H. M. i Garrard, P., 2013. Semantic processing in connected speech at a uniformly early stage of autopsy-confirmed Alzheimer's disease. Neuropsychology, pp. 79-85. DOI:

Benton, A. I., Hamsher, K. i Sivan, A., 2000. Multilingual Aphasia Examination, Iowa City: IA: AJA Associates.

Boschi, V. i inni, 2017. Connected Speech in Neurodegenerative Language Disorders: A Review. Frontiers in Psychology, 6 March. DOI:

Fraser A., K. C., Meltzerb, J. A. i Rudzicza, F., 2015. Linguistic Features Identify Alzheimer's Disease in Narrative Speech. Journal of Alzheimer's Disease, August, p. 407-422. DOI:

Gaweł, M. i Potulska-Chromik, A., 2015. Choroby neurodegeneracyjne: choroba Alzheimera i Parkinsona. Postępy Nauk Medycznych, pp. 468-476.

Gliwa, R., 2017. Logopeadica Lodzienia. brak miejsca:brak nazwiska

Gonzalez-Moreira, E. i inni, 2015. Automatic Prosodic Analysis to Identify Mild Dementia. BioMed Research International. DOI:

Goodglass H, K. E. B. B., 2001. Boston Diagnostic Aphasia Examination. 3rd ed..

Hoffman, I. i inni, 2010. Temporal parameters of spontaneous speech in Alzheimer's disease. International Journal of Speech-Language Pathology, pp. 29-34. DOI:

Khodabakhsh, A., Yesil, F., Guner, E. i Demiroglu, C., 2015. Evaluation of linguistic and prosodic features for detection of Alzheimer's disease in Turkish conversational speech. EURASIP: Journal on Audio, Speech and Music Processing. DOI:

König, A. i inni, 2015. Automatic speech analysis for the assessment of patients with predementia and Alzheimer's disease. Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring, March, pp. 112-124. DOI:

Lewicka, T., Stompel, D. i Nowakowska-Kempna, I., 2014. Zaburzenia językowe w chorobach neurodegeneracyjnych : aspekty diagnostyczne i terapeutyczne. Logopedia Silesiana 3, pp. 76-94.

Pagliarin, i inni, 2014. Montreal-Toulouse language assessment battery for aphasia: validity and reliability evidence. NeuroRehabilitation, pp. 463-471. DOI:

Podemski, R., 2008. Kompendium neurologii. Gdańsk: Via Medica.

Rudzicz, F., 2016. Toward Dementia Diagnosis via Artificial Intelligence. Today's Geriatric Medicine, March/April, p. 8.

Rymarczyk, K., 1999. Zaburzenia prozodii emocjonalnej i lingwistycznej u pacjentów z uszkodzeniami mózgu. Przegląd Psychologiczny , pp. 135 - 150 .

Sajjadi, S. A., Patterson, K., Tomek, M. i Nestor, P. J., 2011. Abnormalities of connected speech in semantic dementia vs Alzheimer's disease. Aphasiology, pp. 847-866. DOI:

Singh, S., Bucks, R. S. i Cuerden, J. M., 2000. An evaluation of an objective technique for analysing temporal variables in DAT spontaneous speech. Aphasiology. DOI:

Szczudlik, A. i inni, 2016. Sytuacja osób chorych na chorobę Alzheimera w Polsce, Warszawa: Polskie Towarzystwo Alzheimerowskie.

Szepietowska, E. M. i Daniluk, B., 2000. Zaburzenia językowe w demencji w ujęciu neuropsychologii klinicznej. Audiofonologia, pp. 117-135.

Yancheva, M., Fraser, K. i Rudzicz, F., 2015. Using linguistic features longitudinally to predict clinical scores for Alzheimer's disease and related dementias. Drezno, Association for Computational Linguistics . DOI: