2022 Fiscal Year Research-status 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 |
Identifying biomarkers of somatic depressive symptoms from heart activity is one of the objectives in this research. This year several indices of heart activity were computed from PPG data of 92 healthy participants and 84 patients of major depressive disorder and the relationships to somatic symptoms quantified using Beck Depression Inventory were examined. Among indices of heart rate variability, LF was significantly correlated to somatic symptoms, suggesting the modulation of sympathetic systems. We also found that multiscale entropy of preprocessed heartbeat intervals was sensitive to somatic symptoms and the mood states of participants. These results demonstrated that the autonomic complexity reflects somatic symptoms and could be potential biomarkers of somatic depressive symptoms.
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| Current Status of Research Progress |
Current Status of Research Progress
3: Progress in research has been slightly delayed.
Reason
The goal of this research includes four items: (1) develop PPG-based biomarker for assessment of somatic depressive symptoms; (2) examine whether interoceptive accuracy can improve the assessment accuracy of somatic depressive symptoms; (3) identify abnormality of neural activity associated with somatic depressive symptoms; (4) investigate whether somatic symptoms related PPG parameters are regulated through the interoceptive system. The (3) and (4) items were completed in the first year. In this year, item (1) was accomplished. Research item (2) was not accomplished since the difficulty of data acquisition during pandemic situation.
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| Strategy for Future Research Activity |
(1)Investigating the relationship between heart activity and interoceptive awareness: To accomplish research item 2, the PI collaborates with Prof. Takafume Sasaoka. He collected resting state heart activity from 80 healthy participants. In this dataset, interoceptive accuracy was not collected. Instead interoceptive awareness was measured. Since studies of interoceptive awareness training have shown effects to alleviate somatic symptoms [Rossi et al., Adv Mind Body Med 2020], we hypothesized that interoceptive awareness links to indices of autonomic activity reflecting somatic symptoms.
(2)Developing machine learning models for assessing somatic depressive symptoms: Automatic feature selection methods will be applied to identify important features which achieves high assessment accuracy.
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| Causes of Carryover |
The budget includes English editing, publication fee, travel expanse for conference. Because of the lockdown under COVID-19 situation, most
conferences were cancelled or hold in a virtual way. The journal manuscript was submitted but not accepted and another journal manuscript is under preparation. Thus, the incurring amount will be used in the process of publishing the results, data analysis, and attending conference next year.
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