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Acoustic Feature Selection with Fuzzy Clustering, Self Organizing Maps and Psychiatric Assessments
[chapter]
2020
Communications in Computer and Information Science
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Acoustic features about phone calls are promising markers for prediction of bipolar disorder episodes. ...
We start from the recursive feature elimination, then two alternative approaches to clustering (fuzzy clustering and self organizing maps) are performed. ...
Important feature of the self-organizing maps is the preservation of neighborhood between the clusters in the two-dimensional space. ...
doi:10.1007/978-3-030-50146-4_26
fatcat:noxep6cruvb5pon47fokhahreq
Mobile phones as medical devices in mental disorder treatment: an overview
2014
Personal and Ubiquitous Computing
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' daily lives to monitor the current state and development of their mental disorders. ...
Concerning the first point, we review various systems that utilize mobile phones for the treatment of mental disorders. ...
ACKNOWLEDGEMENTS Thanks go to Rosa Brown (www.topproofreading.com) for proofreading the manuscript. ...
doi:10.1007/s00779-014-0829-5
fatcat:unacdduktfbqvmynkht7tmwfgi
Validating Biobehavioral Technologies for Use in Clinical Psychiatry
2021
Frontiers in Psychiatry
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We define and discuss resolution in terms of traditional reliability and validity evaluation for psychiatric measures, then highlight its importance in a study using acoustic features to predict self-injurious ...
Regarding validity, accuracy based on machine learning of acoustic features predicting SITB varied as a function of resolution. ...
MLM, for example, has been used to understand how acoustics and facial features change as a function of time, social context and setting in schizophrenia (24, (84) (85) (86) . ...
doi:10.3389/fpsyt.2021.503323
pmid:34177631
pmcid:PMC8225932
fatcat:32cfzzrxwzekrd472lipwi5cri
Self-experience in the early phases of schizophrenia: 5-year follow-up of the Copenhagen Prodromal Study
2011
World Psychiatry
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High levels of perplexity and self-disorders baseline scores yielded the best prediction of the subsequent development of schizophrenia spectrum disorders. ...
We report here the results of the Copenhagen Schizophrenia Prodromal Study, a prospective, observational study of first admission patients in putative state of beginning psychosis (N=151) with a follow-up ...
Acknowledgements This study was supported by the Copenhagen Hospital Corporation, the European Union Marie-Curie RTN "DIS-COS -Disorders and Coherence of the Embodied Self", and the University of Copenhagen ...
doi:10.1002/j.2051-5545.2011.tb00057.x
pmid:21991279
pmcid:PMC3188774
fatcat:cbhxkfz32jbednnfvdefpzw3h4
A Comprehensive Review of Computational Methods for Automatic Prediction of Schizophrenia With Insight Into Indigenous Populations
2019
Frontiers in Psychiatry
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With recent advances in computational sciences, we have seen a re-emergence of novel research using computing methods to analyze free speech for improving prediction and diagnosis of psychosis. ...
Descriptive psychopathology and phenomenology form the basis of a common language used by psychiatrists to describe abnormal mental states. ...
Kessing (72) used voice analysis as an objective marker in bipolar disorder. This study found that changes in speech were sensitive and a valid measure of bipolar disorder. ...
doi:10.3389/fpsyt.2019.00659
pmid:31607962
pmcid:PMC6759015
fatcat:3afqtu74tren5pbfgdni37p6ji
Cohort Profile: The Heinz C. Prechter Longitudinal Study of Bipolar Disorder
2017
International Journal of Epidemiology
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The study is specifically designed to identify and characterize the mechanisms underlying bipolar disorder (BP) and to develop methods to predict clinical outcomes of the disorder. ...
Prechter Longitudinal Study of Bipolar Disorder (PrBP), launched in 2005, is an open cohort study at the University of Michigan, Ann Arbor, USA. ...
We especially thank Waltraud Prechter and her family and the many supporters of the Heinz C. Prechter Bipolar Research Fund who have made this work possible. ...
doi:10.1093/ije/dyx229
pmid:29211851
pmcid:PMC5837550
fatcat:4pdtv663n5e6vjigu2z2ypk5bi
A Review of Automated Speech and Language Features for Assessment of Cognition and Thought Disorders
2019
IEEE Journal on Selected Topics in Signal Processing
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2019 pre-print arXiv:1906.01157v1 fatcat:hz6hv5pm4fhg5kgtwddfompjjuOther Versions
With an emphasis on cognitive and thought disorders, in this paper we provide a review of existing speech and language features used in this domain, discuss their clinical application, and highlight their ...
It is widely accepted that information derived from analyzing speech (the acoustic signal) and language production (words and sentences) serves as a useful window into the health of an individual's cognitive ...
those with bipolar disorder/mania [12] . ...
doi:10.1109/jstsp.2019.2952087
pmid:33907590
pmcid:PMC8074691
fatcat:a6t24cpp6jbdxbxq5wzd3uz6jq
Personal Sensing: Understanding Mental Health Using Ubiquitous Sensors and Machine Learning
2017
Annual Review of Clinical Psychology
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We provide a layered, hierarchical model for translating raw sensor data into markers of behaviors and states related to mental health. ...
for the next generation of mobile health (or mHealth) interventions. ...
ACKNOWLEDGEMENTS This work was supported by the National Institutes of Mental Health with grants P20MH090318, R01MH100482, and R01MH095753 to Dr. Mohr, and K08MH102336 to Dr. Schueller. ...
doi:10.1146/annurev-clinpsy-032816-044949
pmid:28375728
pmcid:PMC6902121
fatcat:rxu55uc7jvaeplcrzaeotkmv6i
Fear of harm, a possible phenotype of pediatric bipolar disorder: A dimensional approach to diagnosis for genotyping psychiatric syndromes
2009
Journal of Affective Disorders
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A strategy for identifying phenotypic subtypes: concordance of symptom dimensions between sibling pairs who met screening criteria for a genetic linkage study of childhood-onset bipolar disorder using ...
Trait factors were derived from a factor analysis of CBQ in a large population of children diagnosed with or at risk for PBD, and used to further elucidate trait features of children with FOH. ...
A genetic nosology of bipolar disorder could incorporate features of both traditions to provide a strategy for optimizing genetic approaches to bipolar disorder (BPD). ...
doi:10.1016/j.jad.2009.06.016
pmid:19631388
fatcat:v4nw6jsns5f3zawb7s32la7kti
Implications of the BATTERY 2030+ AI‐Assisted Toolkit on Future Low‐TRL Battery Discoveries and Chemistries
2021
Advanced Energy Materials
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, non-crystalline, nano-structured and disordered systems, organic battery materials, and bulk vs. interface-limited batteries. ...
The methodological perspectives and challenges in areas like predictive long time-and length-scale simulations of multi-species systems, dynamic processes at battery interfaces, deep learned multi-scaling ...
Acknowledgements The authors acknowledge the European Union's Horizon 2020 research and innovation program under grant agreements no. 957189 (BIG-MAP) and no. 957213 (BATTERY 2030+). ...
doi:10.1002/aenm.202102698
fatcat:muafelf4yrb7licg3lqpbmqmry
Basic self-disturbances independently predict recovery in psychotic disorders: A seven year follow-up study
2019
Schizophrenia Research
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Basic self-disturbances (BSDs) are non-psychotic phenomena associated with clinical outcome, present in prodromal, psychotic and residual phases of psychotic disorders. ...
Recovery is the ultimate goal of psychosis treatment. ...
III
RESEARCH ARTICLE Basic self-disturbances are associated with Sense of Coherence in patients with psychotic disorders
Acknowledgments The authors thank the patients for participating in the study ...
doi:10.1016/j.schres.2019.08.009
pmid:31420200
fatcat:glowjglgdffzxk6djdz2etg3nm
Feature Augmenting Networks for Improving Depression Severity Estimation from Speech Signals
2020
IEEE Access
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To alleviate this issue, in this work we propose to use Deep Convolutional Generative Adversarial Network (DCGAN) for features augmentation to improve depression severity estimation from speech. ...
of the state of the art results on AVEC 2016. ...
SPEECH ACOUSTIC FEATURES In this work, we make use of our previously proposed speech acoustic feature for depression severity prediction from speech [34] , [45] . ...
doi:10.1109/access.2020.2970496
fatcat:3nzusy7skndbjmhfpbwbyy56yq
DRIVER ASSISTANCE SYSTEM FOR DISORDERED PEOPLE
2020
International Journal of Engineering Applied Sciences and Technology
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The study of leverage the recently emerged methods for self-driving cars, and use it to develop assistive technology for the visually impaired, hearing impaired and mentally retarded. the task of perceiving ...
In this paper, we explore the synergies between the challenges in self-driving technology and development of navigation aids for blind people and hearing loss people. ...
An important stage in such system is lane prediction and on-road-self-positioning. ...
doi:10.33564/ijeast.2020.v04i10.047
fatcat:2vwr3n2eqzh7ndi5a5kgejgm7u
Neural And Music Correlates Of Music-Evoked Emotions
2016
Zenodo
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music-evoked emotions, based on acoustic features extracted from the music? ...
music using MIR (music information retreival) tools, a machine learning approach is selected for the creation of the model. ...
This feature vector, which in case of the audio tracks consists of audio descriptors, is used by the algorithms for predicting the class. ...
doi:10.5281/zenodo.1161286
fatcat:elnq7oi5nbakdgqaa6xphc6mne
Examination of Anomalous Self-Experience in First-Episode Psychosis: Interrater Reliability
2011
Psychopathology
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Structured Interview of Prodromal Syndromes (SIPS) and Comprehensive Assessment of at Risk Mental States (CAARMS), are less specific and identify early clinical features predictive of several forms of ...
The verbal memory test used in the current study requires rapid cognitive processing of incoming verbal information and efficient organization for accurate recall. ...
doi:10.1159/000325173
pmid:21847006
fatcat:sq6ihhtavjam7nw6ysxau3a37m
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