How photoplethysmography can be used to detect major depressive disorder among patients with obstructive sleep apnea during sleep.
| Title: | How photoplethysmography can be used to detect major depressive disorder among patients with obstructive sleep apnea during sleep. |
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| Authors: | Shaw V; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India; CSIR-Central Scientific Instruments Organisation (CSIR-CSIO), Chandigarh, 160030, India; School of Engineering, STEM College, RMIT University, Melbourne, VIC, 3000, Australia.; Ngo QC; School of Engineering, STEM College, RMIT University, Melbourne, VIC, 3000, Australia.; Pah ND; School of Engineering, STEM College, RMIT University, Melbourne, VIC, 3000, Australia.; Khandoker AH; Department of Biomedical Engineering and Biotechnology, Khalifa University, Abu Dhabi, United Arab Emirates.; Mahapatra PK; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India; CSIR-Central Scientific Instruments Organisation (CSIR-CSIO), Chandigarh, 160030, India.; Pankaj D; CSIR-Central Scientific Instruments Organisation (CSIR-CSIO), Chandigarh, 160030, India.; Kumar DK; School of Engineering, STEM College, RMIT University, Melbourne, VIC, 3000, Australia. Electronic address: dinesh.kumar@rmit.edu.au. |
| Source: | Computers in biology and medicine [Comput Biol Med] 2025 Sep; Vol. 196 (Pt B), pp. 110814. Date of Electronic Publication: 2025 Jul 24. |
| Publication Type: | Journal Article |
| Language: | English |
| Journal Info: | Publisher: Elsevier Country of Publication: United States NLM ID: 1250250 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1879-0534 (Electronic) Linking ISSN: 00104825 NLM ISO Abbreviation: Comput Biol Med Subsets: MEDLINE |
| Imprint Name(s): | Publication: New York : Elsevier; Original Publication: New York, Pergamon Press. |
| MeSH Terms: | Photoplethysmography*/methods ; Sleep Apnea, Obstructive*/physiopathology ; Sleep Apnea, Obstructive*/complications ; Sleep Apnea, Obstructive*/diagnosis ; Major Depressive Disorder*/diagnosis ; Major Depressive Disorder*/physiopathology ; Major Depressive Disorder*/complications ; Signal Processing, Computer-Assisted*; Humans ; Male ; Female ; Middle Aged ; Adult |
| Abstract: | Major Depressive Disorder (MDD) frequently coexists with Obstructive Sleep Apnea (OSA), yet it remains underdiagnosed in OSA populations due to overlapping symptoms and limited access to psychiatric sleep evaluations. Earlier studies have explored photoplethysmography (PPG) for screening either OSA or MDD individually but have not investigated the use of PPG to analyze comorbid MDD in patients with OSA. Additionally, beat-level entropy and complexity features, which quantify subtle nonlinear variations in pulse morphology and may reflect autonomic nervous system dysregulation associated with this comorbidity, have been largely overlooked. This study investigates whether beat-to-beat PPG-derived features can distinguish among healthy controls (CO), individuals with OSA only, referred to as OSA-, and those with OSA and comorbid MDD, referred to as OSA+. PPG recordings from 60 participants (CO: 25, OSA-: 20, OSA+: 15) were preprocessed to extract artifact-free segments. For each segment, skewness (Sk) and kurtosis (Ku) were computed on a beat-to-beat basis, followed by the extraction of Approximate Entropy (ApEn), Hjorth Activity (HA), Hjorth Mobility (HM), and Hjorth Complexity (HC) parameters to quantify signal variability. Feature selection was conducted within a 5-fold nested cross-validation framework using Spearman correlation, and only features that satisfied both a correlation threshold and statistical significance (p |
| Competing Interests: | Declaration of competing interest None of the co-authors have any conflict of interest with the publication of this paper. |
| Contributed Indexing: | Keywords: Major depressive disorder; Obstructive sleep apnea; Photoplethysmography |
| Entry Date(s): | Date Created: 20250725 Date Completed: 20250826 Latest Revision: 20260127 |
| Update Code: | 20260130 |
| DOI: | 10.1016/j.compbiomed.2025.110814 |
| PMID: | 40712210 |
| Database: | MEDLINE |
Journal Article