ArticleFrontiers in physiology2019
Cardiorespiratory Coupling Analysis Based on Entropy and Cross-Entropy in Distinguishing Different Depression Stages.
Article in Frontiers in physiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Oscillatory components of bidirectional cardio-respiratory coupling in depression and suicidal ideation: insights from swarm decomposition and entropy analysis.Frontiers in network physiology · 2025Article
- Diabetes alters cardiorespiratory dynamics: insights from short-term recurrence quantification analysis of pulse-respiration quotient.Frontiers in physiology · 2025Article
- Physiological Regularity and Synchrony in Individuals with Gaming Disorder.Entropy (Basel, Switzerland) · 2024Article
- Multimodal Mental Health Digital Biomarker Analysis From Remote Interviews Using Facial, Vocal, Linguistic, and Cardiovascular Patterns.IEEE journal of biomedical and health informatics · 2024Article
- Bradycardia May Decrease Cardiorespiratory Coupling in Preterm Infants.Entropy (Basel, Switzerland) · 2023Article
- Changes in the autonomic cardiorespiratory activity in parturient women with severe and moderate features of preeclampsia.Frontiers in immunology · 2023Article
- A study on the immediate effects of enhanced external counterpulsation on physiological coupling.Frontiers in neuroscience · 2023Article
- Cardiorespiratory dynamics during respiratory maneuver in athletes.Frontiers in network physiology · 2023Article
- Effects of 24-h acute total sleep deprivation on physiological coupling in healthy young adults.Frontiers in neuroscience · 2022Article
- Entropy of eye movement during rapid automatized naming.Frontiers in human neuroscience · 2022Article
- Discrimination of Patients with Varying Degrees of Coronary Artery Stenosis by ECG and PCG Signals Based on Entropy.Entropy (Basel, Switzerland) · 2021Article
- Article
- Frontal Alpha Complexity of Different Severity Depression Patients.Journal of healthcare engineering · 2020Article
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4 authors.
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Abstract
aimsThis study used entropy- and cross entropy-based methods to explore the cardiorespiratory coupling of depressive patients, and thus to assess the values of those entropy methods for identifying depression patients with different disease severities.
methodsElectrocardiogram (ECG) and respiration signals from 69 depression patients were recorded simultaneously for 5 min. Patients were classified into three groups according to the Hamilton Depression Rating Scale (HDRS) scores: group Non-De (HDRS 0-7), Mid-De (HDRS 8-17), and Con-De (HDRS >17). Sample entropy (SEn), fuzzy measure entropy (FMEn) and high-frequency power (HF) were computed on the original RR interval time series and breath-to-breath interval time series. Cross sample entropy (CSEn) and cross fuzzy measure entropy (CFMEn) were computed on interval time series resampled at 2 Hz and 4 Hz, respectively. The difference among three patient groups and correlation between entropy values and HDRS scores were analyzed by statistical analysis. Surrogate data were also employed to confirm the validation of entropy measures in this study.
resultsA consistent increasing trend has been found among most entropy measures from Non-De, to Mid-De, and to Con-De groups, and a significant (
conclusionThe current study demonstrates the potential of cardiorespiratory coupling in the auxiliary diagnosis of depression based on the entropy method.
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