REM sleep estimation only using respiratory dynamics

Abstract

Polysomnography (PSG) is currently considered the gold standard for assessing sleep quality. However, the numerous sensors that must be attached to the subject can disturb sleep and limit monitoring to within hospitals and sleep clinics. If data could be obtained without such constraints, sleep monitoring would be more convenient and could be extended to ordinary homes. During rapid-eye-movement (REM) sleep, respiration rate and variability are known to be greater than in other sleep stages. Hence, we calculated the average rate and variability of respiration in an epoch (30 s) by applying appropriate smoothing algorithms. Increased and irregular respiratory patterns during REM sleep were extracted using adaptive and linear thresholds. When both parameters simultaneously showed higher values than the thresholds, the epochs were assumed to belong to REM sleep. Thermocouples and piezoelectric-type belts were used to acquire respiratory signals. Thirteen healthy adults and nine obstructive sleep apnea (OSA) patients participated in this study. Kappa statistics showed a substantial agreement (kappa > 0.60) between the standard and respiration-based methods. One-way ANOVA analysis showed no significant difference between the techniques for total REM sleep. This approach can also be applied to the non-intrusive measurement of respiration signals, making it possible to automatically detect REM sleep without disturbing the subject.

Pediatric Obstructive Sleep Apnea assessment using pulse oximetry and dual RIP bands

“…Certain techniques are documented in providing alternative measurements based on RIP bands and heart rate. These techniques include using respiratory dynamics [13] such as phase and amplitude of RIP bands and pulse transit time (PTT) [14] to quantify events and arousals respectively. Given the significant classification accuracy advantage of SEA REM compared with SEA TS , it is also important to investigate the application methods to automatically identify REM sleep based on RIP or oximetry data alone [15].…”

“…At the same time, these variables should provide important information about the presence, and severity of OSA pathology. Based on literature [2,[7][8][9][10][11][12][13] and clinical experience, experts identified three critical clinical features:…”

Accuracy-coverage tradeoff of nocturnal vital sign estimation in smart beds

“…With an analysis window length of 15 to 30 s, the autocorrelation method was shown to provide sufficient sensitivity in respiration rate computation to estimate REM sleep [4].…”

“…For example, respiration rate is estimated using nasal monitors and face spirometers in clinical sleep analysis laboratories, among other equipment, to assess sleep abnormalities such as apneas. Furthermore, continuous respiration rate can be used to estimate sleep phases [4]. Adequate proportions of the different sleep phases are frequently considered as sleep quality measure [2].…”

Applications of evolving technologies in sleep medicine

“…Updates of current PSG systems are rare, while the market moves apace with new technologies, such as new sensors, Wi-Fi and remote monitoring (telephone or video). Integration of these new and innovative technologies could contribute to better patient care, while development of algorithms that can differentiate sleep stages from ECG, pulse wave, respiratory dynamics [7] and movement sensors can simplify the diagnostic procedure. The increase in the processing and integration capacity of electronic devices, as well as advances in low-power wireless communications, has enabled the development of unwired intelligent sensors for a wide set of applications.…”