Autonomic impairment in Alzheimer's disease is revealed by complexity analysis of functional thermal imaging signals during cognitive tasks.


Journal

Physiological measurement
ISSN: 1361-6579
Titre abrégé: Physiol Meas
Pays: England
ID NLM: 9306921

Informations de publication

Date de publication:
22 03 2019
Historique:
pubmed: 9 2 2019
medline: 10 3 2020
entrez: 9 2 2019
Statut: epublish

Résumé

Alzheimer's disease (AD) is characterized by progressive memory failures and visuospatial impairment. Moreover, AD can be accompanied by autonomic system alterations, which, among other impacts, affect thermoregulatory activity. We here investigate differences in autonomic activity between AD patients and healthy controls (HC), employing a complexity analysis of functional infrared imaging (fIRI) data acquired at rest and during the execution of clinical cognitive and mnemonic tests. fIRI allows for contactless monitoring of autonomic activity and its thermoregulatory expression without interfering with the psychophysiological state of the subject, preserving free interaction with the doctor. The signal complexity analysis, based on the sample entropy, was compared to a standard frequency-based analysis of autonomic-related signals. AD patients exhibited lower complexity of fIRI signals during the tests, which could be indicative of a stronger sympathetic activity with respect to HC. No significant effects were found at rest. No differences were found on employing frequency-based analysis. This study confirms that AD patients may exhibit peculiar autonomic responses associated with the execution of cognitive tasks that can be measured through fIRI. Moreover, these responses could be highlighted by a nonlinear metric of signal predictability such as the sample entropy establishing autonomic impairment of AD patients.

Identifiants

pubmed: 30736015
doi: 10.1088/1361-6579/ab057d
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

034002

Auteurs

David Perpetuini (D)

Infrared Imaging Lab, Centro ITAB-Institute for Advanced Biomedical Technologies, University G. d'Annunzio, Chieti, 66100, Italy. Department of Neurosciences, Imaging and Clinical Sciences, University G. d'Annunzio, Chieti-Pescara, 66100, Italy. Author to whom any correspondence should be addressed.

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Classifications MeSH