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1.
A wearable device perspective on the standard definitions of disability progression in multiple sclerosis.
Mult Scler
; 30(1): 103-112, 2024 Jan.
Artículo
en Inglés
| MEDLINE | ID: mdl-38084497
2.
Characterising illness stages and recovery trajectories of eating disorders in young people via remote measurement technology (STORY): a multi-centre prospective cohort study protocol.
BMC Psychiatry
; 24(1): 409, 2024 May 30.
Artículo
en Inglés
| MEDLINE | ID: mdl-38816707
3.
Challenges in Using mHealth Data From Smartphones and Wearable Devices to Predict Depression Symptom Severity: Retrospective Analysis.
J Med Internet Res
; 25: e45233, 2023 08 14.
Artículo
en Inglés
| MEDLINE | ID: mdl-37578823
4.
Automatic Assessment of the 2-Minute Walk Distance for Remote Monitoring of People with Multiple Sclerosis.
Sensors (Basel)
; 23(13)2023 Jun 29.
Artículo
en Inglés
| MEDLINE | ID: mdl-37447866
5.
Fitbeat: COVID-19 estimation based on wristband heart rate using a contrastive convolutional auto-encoder.
Pattern Recognit
; 123: 108403, 2022 Mar.
Artículo
en Inglés
| MEDLINE | ID: mdl-34720200
6.
Automatic Emotion Recognition in Children with Autism: A Systematic Literature Review.
Sensors (Basel)
; 22(4)2022 Feb 20.
Artículo
en Inglés
| MEDLINE | ID: mdl-35214551
7.
Investigating the impact of COVID-19 lockdown on adults with a recent history of recurrent major depressive disorder: a multi-Centre study using remote measurement technology.
BMC Psychiatry
; 21(1): 435, 2021 09 06.
Artículo
en Inglés
| MEDLINE | ID: mdl-34488697
8.
Real-time assessment of COVID-19 prevalence among multiple sclerosis patients: a multicenter European study.
Neurol Sci
; 41(7): 1647-1650, 2020 Jul.
Artículo
en Inglés
| MEDLINE | ID: mdl-32617741
9.
Using Smartphones and Wearable Devices to Monitor Behavioral Changes During COVID-19.
J Med Internet Res
; 22(9): e19992, 2020 09 25.
Artículo
en Inglés
| MEDLINE | ID: mdl-32877352
10.
Speech analysis for health: Current state-of-the-art and the increasing impact of deep learning.
Methods
; 151: 41-54, 2018 12 01.
Artículo
en Inglés
| MEDLINE | ID: mdl-30099083
11.
Emotional expression in psychiatric conditions: New technology for clinicians.
Psychiatry Clin Neurosci
; 73(2): 50-62, 2019 Feb.
Artículo
en Inglés
| MEDLINE | ID: mdl-30565801
12.
Automatic detection of expressed emotion from Five-Minute Speech Samples: Challenges and opportunities.
PLoS One
; 19(3): e0300518, 2024.
Artículo
en Inglés
| MEDLINE | ID: mdl-38512817
13.
Towards a scalable approach to assess speech organization across the psychosis-spectrum -online assessment in conjunction with automated transcription and extraction of speech measures.
Transl Psychiatry
; 14(1): 156, 2024 Mar 21.
Artículo
en Inglés
| MEDLINE | ID: mdl-38509087
14.
Identifying depression-related topics in smartphone-collected free-response speech recordings using an automatic speech recognition system and a deep learning topic model.
J Affect Disord
; 355: 40-49, 2024 Jun 15.
Artículo
en Inglés
| MEDLINE | ID: mdl-38552911
15.
Automated analysis of speech as a marker of sub-clinical psychotic experiences.
Front Psychiatry
; 14: 1265880, 2023.
Artículo
en Inglés
| MEDLINE | ID: mdl-38361830
16.
Online speech assessment of the psychotic spectrum: Exploring the relationship between overlapping acoustic markers of schizotypy, depression and anxiety.
Schizophr Res
; 259: 11-19, 2023 09.
Artículo
en Inglés
| MEDLINE | ID: mdl-37080802
17.
The Feasibility of Implementing Remote Measurement Technologies in Psychological Treatment for Depression: Mixed Methods Study on Engagement.
JMIR Ment Health
; 10: e42866, 2023 Jan 24.
Artículo
en Inglés
| MEDLINE | ID: mdl-36692937
18.
Digital endpoints in clinical trials of Alzheimer's disease and other neurodegenerative diseases: challenges and opportunities.
Front Neurol
; 14: 1210974, 2023.
Artículo
en Inglés
| MEDLINE | ID: mdl-37435159
19.
Multilingual markers of depression in remotely collected speech samples: A preliminary analysis.
J Affect Disord
; 341: 128-136, 2023 11 15.
Artículo
en Inglés
| MEDLINE | ID: mdl-37598722
20.
Autonomic response to walk tests is useful for assessing outcome measures in people with multiple sclerosis.
Front Physiol
; 14: 1145818, 2023.
Artículo
en Inglés
| MEDLINE | ID: mdl-37089424