A Review on Machine Learning Models for Breathing Pattern Analysis of Soldiers DOI

P. Kaleeswari,

R. Ramalakshmi,

Arunprasath Thiyagarajan

et al.

Published: Dec. 14, 2023

Since 2001, the U.S. military has sent 2.7 million people to support missions in Afghanistan and Asia. The experience of land-based employees is increased by exposure additional inhalational exposures particulate matter from a variety sources. For purpose preventing significant loss nation individual soldier, post-traumatic stress disorder (PTSD) must be identified. Breathing pattern analysis key method for detecting PTSD, various studies have used machine learning techniques this purpose. This survey examines multiple ML models determine soldiers' breathing patterns distinct works. overview discusses several strategies over past few decades conducting extensive research. Military personnel' are analyzed using datasets, statistical factors, methodologies. effectiveness algorithms compared qualitative as well quantitative approaches. potential future study areas with major challenges discussed reach conclusion.

Language: Английский

Characterizing PTSD Using Electrophysiology: Towards A Precision Medicine Approach DOI Creative Commons
Natasha Kovacevic, Amir H. Meghdadi, Chris Berka

et al.

Clinical EEG and Neuroscience, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 7, 2025

Objective. Resting-state EEG measures have shown potential in distinguishing individuals with PTSD from healthy controls. ERP components such as N2, P3, and late positive been consistently linked to cognitive abnormalities PTSD, especially tasks involving emotional or trauma-related stimuli. However, meta-analyses reported inconsistent findings. The understanding of biomarkers that can classify the varied symptoms remains limited. This study aimed develop a concise set electrophysiological biomarkers, using neutral tasks, could be applied across psychiatric conditions, identify associated anxiety depression dimensions PTSD. Approach. Continuous simultaneous recordings electrocardiogram (ECG) were obtained veterans (n = 29) controls 62) during computerized tasks. EEG, ERP, heart rate evaluated terms their ability discriminate between groups correlate psychological measures. Results. cohort exhibited faster alpha oscillations, reduced power, flatter power spectrum. Furthermore, stronger reduction was higher trait anxiety, while slope related more severe In visual memory sustained attention, demonstrated delayed exaggerated early components, along attenuated LPP amplitudes. three revealed distinct complementary signatures Significance. Multimodal individualized based on ERPs, ECG show promise objective tools for assessing mood disturbances within

Language: Английский

Citations

0
PTSD-related differences in neural connectivity among female trauma survivors DOI Creative Commons

Natalie C. Noble,

Mohammad S.E. Sendi, Julia B. Merker

et al.

Biological Psychiatry Global Open Science, Journal Year: 2025, Volume and Issue: unknown, P. 100491 - 100491

Published: March 1, 2025

Language: Английский

Citations

0
A systematic review of aperiodic neural activity in clinical investigations DOI Creative Commons
Thomas Donoghue

medRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: Oct. 15, 2024

Abstract In the study of neuro-electrophysiological recordings, aperiodic neural activity – with no characteristic frequency has increasingly become a common feature study. This interest rapidly extended to clinical work, many reports investigating from patients broad range disorders. work typically seeks evaluate as putative biomarker relating diagnosis or treatment response, and/or potential marker underlying physiological activity. There is thus far clear consensus on if and how relates disorders, nor best practices for it in research. To address this, this systematic literature review, following PRISMA guidelines, examines electrophysiological recordings human psychiatric neurological finding 143 across 35 distinct Reports within disorders are summarized current findings examine what can be learned pertains analysis, interpretations, overall utility investigations. Aperiodic commonly reported relate diagnoses, 31 reporting significant effect diagnostic related studies. However, there variation consistency results heterogeneity patient groups, disease etiologies, status arising themes different Overall, variability results, potentially confounding covariates, limitations understanding suggests further needed before established pathological physiology. Finally, series recommendations proposed, based findings, limitations, key discussion topics assist guiding productive future studying Project Repository The project repository contains code & data project: https://github.com/TomDonoghue/AperiodicClinical

Language: Английский

Citations

3
Resolving Heterogeneity in Posttraumatic Stress Disorder Using Individualized Structural Covariance Network Analysis DOI Creative Commons
Xueling Suo, Nanfang Pan, Li Chen

et al.

Depression and Anxiety, Journal Year: 2024, Volume and Issue: 2024(1)

Published: Jan. 1, 2024

The heterogeneity of posttraumatic stress disorder (PTSD) is an obstacle to both understanding and therapy, this has prompted a search for internally homogeneous neuroradiological subgroups within the broad clinical diagnosis. We set out do using individual differential structural covariance network (IDSCN). constructed cortical thickness-based IDSCN T1-weighted images 89 individuals with PTSD (mean age 42.8 years, 60 female) demographically matched trauma-exposed non-PTSD (TENP) controls 43.1 63 female). metric quantifies how edges in patient differ from those controls. examined diversity variation among subtypes hierarchical clustering analysis. patients exhibited notable distinct but mainly affecting three networks: default mode, ventral attention, sensorimotor. These changes predicted symptom severity. identified two neuroanatomical subtypes: one higher severity showed lower frontal cortex between frontal, parietal, occipital cortex-regions that are functionally implicated selective response selection, learning tasks. Thus, deviations large-scale networks common fall into subtypes. This work sheds light on neurobiological mechanisms underlying may aid personalized diagnosis therapeutic interventions.

Language: Английский

Citations

1
Construction and Validation of a New BrainView qEEG Discriminant Database DOI Open Access

Annie TL Young,

Slav Danev,

Jonathan R. T. Lakey

et al.

Acta Scientific Neurology, Journal Year: 2024, Volume and Issue: unknown, P. 25 - 51

Published: June 1, 2024

A normative quantitative electroencephalogram (qEEG) database is vital for assessing brain disorders.However, constructing qEEG databases research and clinical applications has posed challenges over the past 61 years, due to defining 'normal' population lack of standardized procedures EEG data.This study aims build a new BrainView discriminant that meets strict data criteria derived from field's milestones, using method similar used construct database.It follows key procedures: collection preprocessing, feature extraction selection, as well classification validation.BrainView comprises 28,283 subjects (7,798 healthy subjects) eyesopen eyes-closed conditions, spanning ages 4 85 years.Developed patient data, BrainView's function identifies patient's likelihood belonging specific group, aiding in precise diagnosis.The goal establish gold standard diagnosis prognosis various disorders, enabling use practice.

Language: Английский

Citations

0
Potential Neurophysiological Markers of Combat-Related Post-Traumatic Stress Disorder: A Cross-Sectional Diagnostic Study DOI Creative Commons
Klavdiya Telesheva, Valeria Savenkova, Irina Morozova

et al.

Consortium Psychiatricum, Journal Year: 2024, Volume and Issue: 5(2), P. 31 - 44

Published: June 28, 2024

BACKGROUND: Studies suggest that the components of brain-evoked potentials (EPs) may serve as biomarkers post-traumatic stress disorder (PTSD) caused by participation in combat operations; however, to date, research remains fragmented, with no studies have attempted combine different paradigms. In addition, mismatch negativity component has not been studied a Russian sample veterans PTSD. AIM: To identify objective neurophysiological markers combat-related PTSD using method auditory-evoked active and passive listening METHODS: The study included recording auditory EPs an oddball paradigm three settings: 1) directed attention stimuli, 2) while viewing neutral video sequence, 3) sequence associated traumatic event. Combatants diagnosed (18 people) were compared mentally healthy civilian volunteers (22 people). RESULTS: An increase latency period early EP (N100 P200), amplitude P200 deviant stimulus, decrease standard one established group. There significant differences parameters P300 component. characteristics revealed: phenomenon amplitude, both when shown event sequence. A binary logistic regression model constructed selected showed identified can potentially be considered diagnostic combatants, classification accuracy stood at 87% (sensitivity — 81%, specificity 91%). CONCLUSION: Potential are following: stimuli during attention.

Language: Английский

Citations

0
A Review on Machine Learning Models for Breathing Pattern Analysis of Soldiers DOI

P. Kaleeswari,

R. Ramalakshmi,

Arunprasath Thiyagarajan

et al.

Published: Dec. 14, 2023

Since 2001, the U.S. military has sent 2.7 million people to support missions in Afghanistan and Asia. The experience of land-based employees is increased by exposure additional inhalational exposures particulate matter from a variety sources. For purpose preventing significant loss nation individual soldier, post-traumatic stress disorder (PTSD) must be identified. Breathing pattern analysis key method for detecting PTSD, various studies have used machine learning techniques this purpose. This survey examines multiple ML models determine soldiers' breathing patterns distinct works. overview discusses several strategies over past few decades conducting extensive research. Military personnel' are analyzed using datasets, statistical factors, methodologies. effectiveness algorithms compared qualitative as well quantitative approaches. potential future study areas with major challenges discussed reach conclusion.

Language: Английский

Citations

0