Early cognitive disorders diagnosis is becoming increasingly important due to population aging. The most common causes include Alzheimer's disease and frontotemporal dementia. These diseases are also manifested by changes in speech. NLP allows us to identify and classify these changes. The project aims to develop a web application for self-assessment and automated detection of cognitive disorders from speech. The application will have a form of a dialogue system using machine learning methods. The novelty of this approach is the possibility of an efficient self-assessment of a wide spectrum of the Czech population from their homes and an automated evaluation of test results. Early detection can be followed by a more detailed diagnosis and adequate treatment.
Study Type
INTERVENTIONAL
Allocation
NON_RANDOMIZED
Purpose
DIAGNOSTIC
Masking
NONE
Enrollment
500
A brief individually administered battery to measure cognitive decline or improvement across five domains in ages 12 to 89 years 11 months.
he Mississippi Aphasia Screening Test (MAST) was developed as a brief, repeatable screening measure for individuals with severely impaired communication/language skills.
Very brief test used to measure deficits of more cognitive functions (short-term, episodic, semantic amnesia, sensory and motor aphasia, apraxia, psychomotor speed).
Very brief test used to measure deficits of more cognitive functions (short-term, episodic, semantic amnesia, sensory and motor aphasia, apraxia, psychomotor speed).
The Geriatric Depression Scale (GDS-15), used to screen for depression in adults aged 55 and older, consists of 15 items that assess mental health based on feelings over the past week.
A formative assessment and rating scale of anxiety.
Our experimental screening battery developed for this study.
Západočeská univerzita v Plzni / Fakulta aplikovaných věd
Pilsen, Czechia
Faculty Hospital Kralovske Vinohrady
Prague, Czechia
Fyzikální ústav AV ČR, v. v. i.
Prague, Czechia
The difference in results between groups of patients with cognitive impairment and healthy individuals in individual parts of our experimental neuropsychological battery Diagnostic Test: Digitial Diagnostics of Dementia (DDD)
Time frame: Through study completion, an average of 2 years
Correlation of the results of our experimental battery (DDD) with RBANS
Time frame: Through study completion, an average of 2 years
Correlation of the results of our experimental battery (DDD) with MAST
Time frame: Through study completion, an average of 2 years
Correlation of the results of our experimental battery (DDD) with ALBA
Time frame: Through study completion, an average of 2 years
Correlation of the results of our experimental battery (DDD) with POBAV
Time frame: Through study completion, an average of 2 years
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