이 연구의 목적은 폐쇄성수면무호흡환자들의 수면단계, AHI, 연령대 간 심박변이도의 통계적 유의성을 결정하는 것이다. 이 연구는 수면무호흡 성인 환자 40명을 대상으로 시간영역 및 주파수 영역에서 심박변이도의 주요 파라메타를 평가하였다. 비 램수면 단계는 3개 그룹 수면무호흡증 환자의 AHI 등급을 비교하여 통계적으로 검증되었다. NN50(p=0.043), pNN50(p=0.044), VLF peak(p=0.022) 및 LF/HF(p=0.028) 매개변수들은 대조군에서 수면무호흡증환자의 R-R 간격에서 통계적으로 유의하였다. 수면무호흡 환자들의 비 램수면(수면2단계)과 램수면 사이의 LF/HF(p=0.045)과 HF power(p=0.0395)파라메타들은 대조군 그룹에서 통계적 유의하였다. 우리는 이 연구에서 폐쇄성 수면무홉증환자들의 AHI, 수면단계 및 연령이 심박변이도 상관관계를 이해하는데 근거를 제시 할 수 있을 것이다.
이 연구의 목적은 폐쇄성수면무호흡환자들의 수면단계, AHI, 연령대 간 심박변이도의 통계적 유의성을 결정하는 것이다. 이 연구는 수면무호흡 성인 환자 40명을 대상으로 시간영역 및 주파수 영역에서 심박변이도의 주요 파라메타를 평가하였다. 비 램수면 단계는 3개 그룹 수면무호흡증 환자의 AHI 등급을 비교하여 통계적으로 검증되었다. NN50(p=0.043), pNN50(p=0.044), VLF peak(p=0.022) 및 LF/HF(p=0.028) 매개변수들은 대조군에서 수면무호흡증환자의 R-R 간격에서 통계적으로 유의하였다. 수면무호흡 환자들의 비 램수면(수면2단계)과 램수면 사이의 LF/HF(p=0.045)과 HF power(p=0.0395)파라메타들은 대조군 그룹에서 통계적 유의하였다. 우리는 이 연구에서 폐쇄성 수면무홉증환자들의 AHI, 수면단계 및 연령이 심박변이도 상관관계를 이해하는데 근거를 제시 할 수 있을 것이다.
The aim of this study was to determine the statistical significance of heart rate variability(HRV) between sleep stages, Apnea-hypopnea index(AHI) and age in patients with obstructive sleep apnea(OSA). This study evaluated the main parameters of HRV over time domain and frequency domain in 40 patien...
The aim of this study was to determine the statistical significance of heart rate variability(HRV) between sleep stages, Apnea-hypopnea index(AHI) and age in patients with obstructive sleep apnea(OSA). This study evaluated the main parameters of HRV over time domain and frequency domain in 40 patients with sleep apnea. The non-REM(sleep stage) was statistically validated by comparing the AHI degree of the three groups(mild, moderate, severe) of sleep apnea patients. The NN50(p=0.043), pNN50(p=0.044), VLF peak(p=0.022), LF/HF(p=0.028) were statistically significant in the R-R interval of patients with sleep apnea from the control group (p<0.05). The LF / HF (p = 0.045) and HF power (p = 0.0395) parameters between the non-RAM sleep (sleep 2 phase) and REM sleep in patients with sleep apnea were statistically significant in the control group(p<0.05). We may be able to provide a basis for understanding the correlation among AHI, sleep stage and age and heart rate variability in patients with obstructive sleep apnea.
The aim of this study was to determine the statistical significance of heart rate variability(HRV) between sleep stages, Apnea-hypopnea index(AHI) and age in patients with obstructive sleep apnea(OSA). This study evaluated the main parameters of HRV over time domain and frequency domain in 40 patients with sleep apnea. The non-REM(sleep stage) was statistically validated by comparing the AHI degree of the three groups(mild, moderate, severe) of sleep apnea patients. The NN50(p=0.043), pNN50(p=0.044), VLF peak(p=0.022), LF/HF(p=0.028) were statistically significant in the R-R interval of patients with sleep apnea from the control group (p<0.05). The LF / HF (p = 0.045) and HF power (p = 0.0395) parameters between the non-RAM sleep (sleep 2 phase) and REM sleep in patients with sleep apnea were statistically significant in the control group(p<0.05). We may be able to provide a basis for understanding the correlation among AHI, sleep stage and age and heart rate variability in patients with obstructive sleep apnea.
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문제 정의
In this paper, experiments were conducted to find statistical significance of HRV parameters associated with AHI, age, non-REM, and REM in sleep apnea patients. The HRV parameters are divided into the time domain and the frequency domain.
In this paper, we developed the R detection algorithm for HRV analysis and performed the necessary studies to diagnose major factors in adult patients with sleep apnea. The aim of this study was to determine the statistical significance of HRV parameters according to non-REM, REM, AHI, and age in sleep apnea patients.
제안 방법
PSG recording was performed using 14 channel positions. Activity was captured continuously overnight by a personal computer (Twin model polygraph) through an analog-to-digital converter with 12-bit resolution and a sampling rate of 200 Hz for off-line analysis using the acquisition program.
This paper presents the results of a double analysis of spectral parameters in 40 patients admitted to a hospital sleep unit. First, we have obtained the HRV spectral indices for all patients and we have analyzed the differences among OSA patients along the whole night. This study demonstrated that statistical significance of HRV parameters can be assessed according to various conditions such as AHI, NRM and REM.
This pattern is thought to reflect decreased parasympathetic and increased sympathetic modulation of heart rate. In this paper, we are expected to help understand the mechanisms of sleep apnea and HRV by analyzing AHI, sleep stages and age-based statistical analysis.
In this paper, we developed the R detection algorithm for HRV analysis and performed the necessary studies to diagnose major factors in adult patients with sleep apnea. The aim of this study was to determine the statistical significance of HRV parameters according to non-REM, REM, AHI, and age in sleep apnea patients.
In this study, we used a series of processes such as filtering and thresholding to the difference signal of the original signal. After the thresholding process we used weight function to detect the position of the peak R wave value because the R wave has both a large signal value and large magnitude of signal change.
The HRV indices were calculated in every 5-min interval of the patient’s recordings in order to look for significant differences between intervals in which apnea had occurred and intervals in which no apnea had occurred.
The REM stage was analyzed statistically by dividing the degree of the AHI into two groups(AHI[30≥30) during sleep apnea.
The HRV parameters are divided into the time domain and the frequency domain. The time domain analysis and the frequency domain included in the mean RR, STD RR, mean HR, STD HR, RMSSD, NN50, pNN50, RR Trian, TNN (STD), VLF peak, HF peak (Hz), VLF power (ms2), LF power (ms2), HF power (ms2), LF / HF ratio, VLF power (%), LF power(%)and HF power(%).
First, we have obtained the HRV spectral indices for all patients and we have analyzed the differences among OSA patients along the whole night. This study demonstrated that statistical significance of HRV parameters can be assessed according to various conditions such as AHI, NRM and REM. Patients with OSA have a decrease in the high frequency component of HRV and an increase in low frequency component.
데이터처리
, Chicago, IL, USA). Univariate correlations between clinical features were evaluated using the Student t test or Mann-Whitney U test with continuous variables after checking for normality using the Kolmogorov-Smirnov test. A 2-tailed p [ 0.
성능/효과
99 yr.All subjects met the following inclusion criteria; 1) male, 2) less than 70 yr old, 3) AHI greater than 5. The ECG signals were analyzed using the R wave peak detection algorithm developed in the research group.
Table 5 used in the experiment were used in 5 minutes and analysed the baseline and REM during sleep apnea. Statistical analysis showed that the Mean RR, RMSSD, pNN50 and TINN were not statistically significant in the time domain. In the frequency domain, VLF peak (Hz), LF peak (Hz), HF peak (Hz), VLF power (ms) and LF % were not statistically significant.
And other parameters of HRV showed statistical significance. The results of this study demonstrated that sleep stages and age, as in previous studies, affect HRV. AHI was compared between two levels (<30 ≥ 30) and three levels (5-15, 15-30, ≥30) in the HRV comparison study, NN50 and pNN50 parameters were statistically significant.
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