Alternative TitleIoTベースのメンタルヘルスケアシステム構築のための日内心拍変動を用いたフロー測定
Note (General)Background: With considerable advancements in the field of technology, it is now more convenient and easier to acquire biomedical signals. These signals not only can be used in the evaluation of physical wellness but also may be helpful in the assessment of mental health if applied properly and precisely. With psychological measures to track mental wellness, and searching for relevant physiological parameters to reveal the underlying physiological bases of mental health, it may be possible for individuals to be healthy both physically and mentally in order to achieve full health and high life expectancy in an ageing society. Objectives: This study investigated whether six dispositional psychological measures, Frequency of Flow Experience, Trait-Coping, Self-Image, Self-Awareness, Will for Meaningful Life, and State-Trait Anxiety are associated with physiological parameters of diurnal heart rate rhythm. Psychological measures are evaluated by questionnaires related to the psychological attributes of a person that can be based on either the experienced sampling method or the dispositional method. The dispositional approach, as the main focus of this study, is designed to quantify one's personality with a long-term psychological nature whereas the experienced sampling approach is for short-term measures to quantify the psychological state of a person during specific short activities. These methods have different questionnaires with experienced sampling using nine items for Frequency of Flow Experience while the dispositional method is only containing four items. Methods: The association of four physiological parameters of diurnal heart rate rhythm-24-hour and 12-hour periodic component amplitudes, diurnal heart rate range over a day and autonomic switching rate with six dispositional psychological measures were analyzed. The physiological parameters were extracted using conventional double cosinor rhythmometry and smoothing of splines methods from heart rate data continuously recorded at one-minute intervals by a wrist device. The double cosinor method is a well-known signal processing technique in heart rate variability. The spline method was considered an alternative approach to capture a more detailed trend pattern of the heart rate diurnal change and address the multicollinearity issue in heart rate parameters. The experiment was conducted on 20 healthy Japanese engineers aged 25-60. Four physiological datasets (weekday only, weekday and weekend data each with mean and median values) were used. Results: The dataset containing weekday-only data with median values gave better results. One reason was that median values were generally suitable for small-size sample. The main reason was that circadian rhythm showed a regular pattern on weekdays since participants spent most of their time in desk work or indoor meeting which corresponded to mental activities. However, during the weekends, there were inconsistent patterns heart rate patterns due to extreme physical activities. Therefore, eliminating the effect of extreme physical activities was important for an accurate mental health assessment. The Spearman single regression analysis revealed a significant correlation (p < 0.05) of Frequency of Flow Experience, and Trait-Coping, a trend of significant correlation (p < 0.1) of Self-Awareness, Will for Meaningful Life, and State-Trait Anxiety while showing no correlation (p > 0.1) of Self-Image with spline-based parameters. The regular single regression analysis revealed a significant correlation of Frequency of Flow Experience, Trait-Coping, and Will for Meaningful Life, a trend of significant correlation of Self-Image, while showing no correlation of Self-Awareness and State-Trait Anxiety with spline-based parameters. The only negative psychological measure; State-Trait Anxiety showed a negative correlation in both Spearman and regular single regression analyses. The regular multiple regression analysis showed a significant correlation of Frequency of Flow Experience, Trait-Coping, and Self-Image, a trend of significant correlation of Will for Meaningful Life, while showing no correlation of Self-Awareness and State-Trait Anxiety with cosinor-based parameters. Principal component analysis extracted one to three orthogonal components with which single component regression analysis showed a significant correlation of Frequency of Flow Experience, Trait-Coping, and Self-Image, a trend of significant correlation of Self-Awareness, Will for Meaningful Life, and State-Trait Anxiety with cosinor-based parameters. Finally, multiple components regression analysis yielded better scores by showing a significant correlation of Frequency of Flow Experience, Trait-Coping, Self-Image, and Will for Meaningful Life, a trend of significant correlation of Self-Awareness, while showing no correlation of State-Trait Anxiety. Generally, cosinor-based physiological parameters gave better scores in regular multiple regression and multiple principal components regression analyses since more heart rate parameters were used to improve the correlation results. Therefore, for regular single regression and Spearman analyses, spline-based heart rate parameters are to be considered as they are a more detailed representation of heart rate change. Conclusion: Dispositional psychological measures were associated with physiological parameters of diurnal heart rate rhythm introduced by this study, representing long-term characteristics of autonomic nervous activity. Integrating such psychological measures and heart rate parameters may lead to a comprehensive understanding of the psychological characteristics of people. The research outcome may be applied to the development of ubiquitous healthcare monitoring systems that integrate both physiological bio-signals and psychological measures.
新大院博(工)第543号
Collection (particular)国立国会図書館デジタルコレクション > デジタル化資料 > 博士論文
Date Accepted (W3CDTF)2023-06-02T22:06:20+09:00
Data Provider (Database)国立国会図書館 : 国立国会図書館デジタルコレクション