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Deep Learning-Based Human Activity Recognition for Continuous Activity and Gesture Monitoring for Schizophrenia Patients With Negative Symptoms

Datos Bibliográficos

ID15524897
AutoresDaniel Umbricht (0000-0003-0272-2157, Roche (Switzerland), autor de correspondencia), Wei-Yi Cheng (0000-0001-6913-4320), Wei‐Yi Cheng (0000-0002-7588-298X, La Roche College), Florian Lipsmeier (0000-0002-8663-819X, Roche (Switzerland)), Atieh Bamdadian (0000-0003-0459-9244, Roche (Switzerland)), Michael Lindemann (0000-0003-1010-3890, Roche (Switzerland))
Año2020
Volumen11
Páginas574375-574375
Fecha de publicación2020-09-16
Open AccessSí
TipoARTICLE
RevistaFrontiers in Psychiatry (JOURNAL)
Identificadores de la revistaISSN: 1664-0640 • E-ISSN: 1664-0640
EditorialFrontiers Media (PUBLISHER • CH)
DOI10.3389/fpsyt.2020.574375
PMID33192706
OpenAlexW3085738965
IdiomaEN
Citas recibidas1
Referencias citadas34

Our findings support the use of wrist-worn devices to derive activity and gesture-based digital outcome measures for patients with schizophrenia with negative symptoms in a clinical trial setting

Actigraphy · Ambulatory · Physical medicine and rehabilitation · Physical therapy · Placebo · Positive and Negative Syndrome Scale · Psychiatry · Psychosis · Schizophrenia (object-oriented programming · Digital Mental Health Interventions · Medicine · Psychology · Psychosomatic Disorders and Their Treatments · Schizophrenia research and treatment · Internal Medicine

  • Predicting Symptoms of Depression and Anxiety Using Smartphone and Wearable Data

    Open Access•Isaac Moshe, Yannik Terhorst et al.•Frontiers in Psychiatry•2021

  • The Positive and Negative Syndrome Scale (PANSS) for Schizophrenia

    Stanley R Kay, Abraham Fiszbein et al.•Schizophrenia Bulletin•1987

Citas por año0,2
Intervalo de citas2021 - 2021 (1)
Altamente citadoNo

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Ethnos_APP • Proyecto Open Source • Licencia MIT • Frontend v2.0.0 • Privacidad y Cookies • Documentación de la API: api.ethnos.app/docs • Código de la API: GitHub • DOI: 10.5281/zenodo.17049435 • Código del Frontend: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae