Actigraphic Assessment of Psychomotor Patterns Associated with the Schizophrenia and Bipolar Spectra
  • Metaadatok
Tartalom: https://doktori.bibl.u-szeged.hu/id/eprint/13245/
Archívum: SZTE Doktori Értekezések Repozitórium
Gyűjtemény: Tudományterületek = Orvostudományok: Egészségtudományok
Típus = Disszertáció
Cím:
Actigraphic Assessment of Psychomotor Patterns Associated with the Schizophrenia and Bipolar Spectra
Létrehozó:
László Szandra
Dátum:
2026-11
Téma:
03.02.24.01. Pszichiátriai betegségek
Tartalmi leírás:
Psychomotor alterations may represent an important symptom dimension of major psychiatric disorders. Actigraphy enables the objective assessment of motor activity and rest–activity rhythms in naturalistic settings. The aim of this dissertation was to investigate psychomotor patterns associated with the schizophrenia and bipolar spectra using detailed actigraphic feature extraction and machine learning methods. The dissertation is based on two cross-sectional studies. In the first study, we examined the actigraphic profiles of individuals without a psychiatric diagnosis who were characterised by cyclothymic temperament (CFG) or positive schizotypal traits (PSF), compared with controls. In the second study, using two independent databases, we analysed the model patterns of the PSF group and individuals with chronic schizophrenia (CS), each relative to their respective control group. Models based on combinations of detailed actigraphic features distinguished the psychometric groups from controls more accurately than models based on simple activity measures. In the CFG group, activity during the rest period, the organisation of daily activity, and characteristics of nocturnal movements emerged as important features. In the PSF group, fine temporal and amplitude-based characteristics of movements during sleep contributed primarily to classification in both studies. In chronic schizophrenia, a broader range of daytime activity and rest–activity rhythm measures contributed alongside nocturnal movement features. Our findings demonstrate that detailed actigraphic feature extraction combined with machine learning enables the identification of psychomotor patterns beyond those captured by conventional activity measures.
Nyelv:
angol
magyar
angol
magyar
magyar
angol
Típus:
Disszertáció
NonPeerReviewed
Formátum:
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Azonosító:
László Szandra Actigraphic Assessment of Psychomotor Patterns Associated with the Schizophrenia and Bipolar Spectra. Doktori (PhD) értekezés, Szegedi Tudományegyetem (2000-). (2026)
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