Objectives: Changes in the autonomic nervous system have been observed in patients with depressive disorders by measuring their heart rate variability (HRV). However, whether HRV associates with depressive events in healthy people remains unknown. Methods: Four healthy people participated in the present study. Their HRVs were measured routinely for 6 to 13 months. During this time, two participants reported experiencing two and three bouts of depression, respectively. This approach allowed us to examine changes in the participants’ HRVs by comparing their HRVs from before and after the unexpected depressive events. Changes in HRV were compared against those of two participants who did not report any depressive event. Results: Participants’ low frequency/high frequency (LF/HF) ratios of HRV were lower after the event of depression than before. Their LF/HF ratios increased after recovery from the depressive events. In contrast, two participants who did not report any depressive event showed relatively smaller changes in their LF/HF ratios across measurements. Conclusions These results suggest that the LF/HF ratio may provide an objective measure of subjective experiences of depression and help identify potential cases of clinical depression.

Objectives: Changes in the autonomic nervous system have been observed in patients with depressive disorders by measuring their heart rate variability (HRV). However, whether HRV associates with depressive events in healthy people remains unknown. Methods: Four healthy people participated in the present study. Their HRVs were measured routinely for 6 to 13 months. During this time, two participants reported experiencing two and three bouts of depression, respectively. This approach allowed us to examine changes in the participants’ HRVs by comparing their HRVs from before and after the unexpected depressive events. Changes in HRV were compared against those of two participants who did not report any depressive event. Results: Participants’ low frequency/high frequency (LF/HF) ratios of HRV were lower after the event of depression than before. Their LF/HF ratios increased after recovery from the depressive events. In contrast, two participants who did not report any depressive event showed relatively smaller changes in their LF/HF ratios across measurements. Conclusions These results suggest that the LF/HF ratio may provide an objective measure of subjective experiences of depression and help identify potential cases of clinical depression.

OBJECTIVES: Soft-computing techniques are commonly used to detect medical phenomena and to help with clinical diagnoses and treatment. The purpose of this paper is to analyze the single electroencephalography (EEG) signal with the chaotic methods in order to identify the sleep stages. METHODS: Data acquisition (polysomnography) was performed on four healthy young adults (all males with a mean age of 27.5 years). The evaluated algorithm was designed with a correlation dimension and Lyapunov's exponent using a single EEG signal that detects differences in chaotic characteristics. RESULTS: The change of the correlation dimension and the largest Lyapunov exponent over the whole night sleep EEG was performed. The results show that the correlation dimension and largest Lyapunov exponent decreased from light sleep to deep sleep and they increased during the rapid eye movement stage. CONCLUSIONS: These results suggest that chaotic analysis may be a useful adjunct to linear (spectral) analysis for identifying sleep stages. The single EEG based nonlinear analysis is suitable for u-healthcare applications for monitoring sleep.
Delivery of Health Care ; Electroencephalography ; Humans ; Light ; Male ; Regression Analysis ; Sleep Stages ; Sleep, REM ; Young Adult