2023 Fiscal Year Annual Research Report
Automatic assessment of somatic depressive symptoms from physiological signals
| Project/Area Number |
20K16627
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| Research Institution | Hiroshima University |
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Principal Investigator |
CHAN HUILING 広島大学, 脳・こころ・感性科学研究センター, 特任助教 (80867979)
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| Project Period (FY) |
2020-04-01 – 2024-03-31
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| Keywords | Somatic symptom / Heart rate variability / Depression / Multiscale entropy / Biomarker |
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| Outline of Annual Research Achievements |
This study has identified neurophysiological markers for depressive somatic symptoms. These markers include reduced low-frequency heart rate variability in photoplethysmography (PPG) signals and altered connectivity between the insula and anterior cingulate cortex in brain imaging data. In our final year, we delved into the potential of multiscale entropy in PPG signals as somatic symptom biomarkers. Our results highlight that multiscale increment entropy of spline-interpolated interbeat intervals also holds promise as a biomarker. In sum, our findings suggest that neurophysiological activity changes with somatic symptoms. Consequently, using multi-modal neurophysiological biomarkers may offer a more comprehensive way for assessing somatic symptoms compared to single-modal indicators.
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