Mirja Tenhunen

Emfit movement sensor in evaluating nocturnal breathing.

Obstructive sleep apnea (OSA) diagnostics by the movement sensors static charge-sensitive bed (SCSB) and electromechanical film transducer (Emfit) is based on dividing the signal into different breathing patterns. The usage of non-invasive mattress sensors in diagnosing OSA is particularly tempting if patient has many other non sleep-related monitoring sensors. However, a systematic comparison of the apnea-hypopnea index (AHI) with Emfit-parameters is lacking. In addition to periodic breathing, SCSB and Emfit visualize episodes of sustained negative increases in intrathoracic pressure (increased respiratory resistance, IRR), of which relevance is still ambiguous. Our aim is to compare Emfit-parameters with the AHI and to provide a description of the patients suffering from IRR. Time percentage with all obstructive periodic Emfit breathing patterns (OPTotal%) showed the best correlation with the AHI. The OPTotal percentage of 21 yielded to excellent accuracy in detecting subjects with an AHI of 15/h or more. Patients with IRR received high scores in GHQ-12-questionnaire. An Emfit movement sensor might offer additional information in OSA diagnostics especially if nasal pressure transducer cannot be used.

Evaluation of Pressure Bed Sensor for Automatic SAHS Screening

We evaluate the performance of an unobtrusive sleep monitoring system in the detection of the sleep apnea- hypopnea syndrome (SAHS). The proposed system is a pressure bed sensor (PBS) that incorporates multiple pressure sensors into a bed mattress to measure several physiological signals of the sleeping subject: respiration; heart rate; and body movements. An automatic algorithm is developed to calculate a respiratory event index (REI). The recordings of 24 patients with suspected sleep problems are analyzed, and the results are compared with the gold standard methods; first with manual scoring of polysomnography to calculate the apnea-hypopnea index (AHI), and second with automatic detection of REI from the respiratory inductive plethysmography belts. The correlation coefficient between AHI and REI from PBS is up to 0.93. Evaluating the ability of PBS in the diagnosis of pathologic (AHI ≥ 5) and nonpathologic (AHI <; 5) subjects, we obtained a sensitivity, specificity, and accuracy of 100%, 92%, and 96%, respectively. To diagnose three levels of SAHS, mild, moderate, and severe, the Cohens kappa value is 0.76. These findings support that PBS recording could provide a simple and unobtrusive method for detection of SAHS in home monitoring.

Intelligent methods for identifying respiratory cycle phases from tracheal sound signal during sleep

We present two methods for identifying respiratory cycle phases from tracheal sound signal during sleep. The methods utilize the Hilbert transform in envelope extraction. They determine automatically a patient-specific amplitude threshold to be used in the detection. The core of one method is designed to be amplitude-independent whereas the other method uses solely the amplitude information. The methods provided average sensitivities of 98% and 99%, respectively, and positive prediction values of 100% on the total of 1434 respiratory cycles analysed from six different patients. The developed methods seem promising as such or as tools for analysing sleep disordered breathing.

Tracheal sound parameters of respiratory cycle phases show differences between flow-limited and normal breathing during sleep

The objective of the present work was to develop new computational parameters to examine the characteristics of respiratory cycle phases from the tracheal breathing sound signal during sleep. Tracheal sound data from 14 patients (10 males and 4 females) were examined. From each patient, a 10 min long section of normal and a 10 min section of flow-limited breathing during sleep were analysed. The computationally determined proportional durations of the respiratory phases were first investigated. Moreover, the phase durations and breathing sound amplitude levels were used to calculate the area under the breathing sound envelope signal during inspiration and expiration phases. An inspiratory sound index was then developed to provide the percentage of this type of area during the inspiratory phase with respect to the combined area of inspiratory and expiratory phases. The proportional duration of the inspiratory phase showed statistically significantly higher values during flow-limited breathing than during normal breathing and inspiratory pause displayed an opposite difference. The inspiratory sound index showed statistically significantly higher values during flow-limited breathing than during normal breathing. The presented novel computational parameters could contribute to the examination of sleep-disordered breathing or as a screening tool.

High frequency components of tracheal sound are emphasized during prolonged flow limitation

A nasal pressure transducer, which is used to study nocturnal airflow, also provides information about the inspiratory flow waveform. A round flow shape is presented during normal breathing. A flattened, non-round shape is found during hypopneas and it can also appear in prolonged episodes. The significance of this prolonged flow limitation is still not established. A tracheal sound spectrum has been analyzed further in order to achieve additional information about breathing during sleep. Increased sound frequencies over 500 Hz have been connected to obstruction of the upper airway. The aim of the present study was to examine the tracheal sound signal content of prolonged flow limitation and to find out whether prolonged flow limitation would consist of abundant high frequency activity. Sleep recordings of 36 consecutive patients were examined. The tracheal sound spectral analysis was performed on 10 min episodes of prolonged flow limitation, normal breathing and periodic apnea-hypopnea breathing. The highest total spectral amplitude, implicating loudest sounds, occurred during flow-limited breathing which also presented loudest sounds in all frequency bands above 100 Hz. In addition, the tracheal sound signal during flow-limited breathing constituted proportionally more high frequency activities compared to normal breathing and even periodic apnea-hypopnea breathing.

Spectral analysis of snoring events from an Emfit mattress.

The aim of this study is to explore the capability of an Emfit (electromechanical film transducer) mattress to detect snoring (SN) by analyzing the spectral differences between normal breathing (NB) and SN. Episodes of representative NB and SN of a maximum of 10 min were visually selected for analysis from 33 subjects. To define the bands of interest, we studied the statistical differences in the power spectral density (PSD) between both breathing types. Three bands were selected for further analysis: 6-16 Hz (BW1), 16-30 Hz (BW2) and 60-100 Hz (BW3). We characterized the differences between NB and SN periods in these bands using a set of spectral features estimated from the PSD. We found that 15 out of the 29 features reached statistical significance with the Mann-Whitney U-test. Diagnostic properties for each feature were assessed using receiver operating characteristic analysis. According to our results, the highest diagnostic performance was achieved using the power ratio between BW2 and BW3 (0.85 area under the receiver operating curve, 80% sensitivity, 80% specificity and 80% accuracy). We found that there are significant differences in the defined bands between the NB and SN periods. A peak was found in BW3 for SN epochs, which was best detected using power ratios. Our work suggests that it is possible to detect snoring with an Emfit mattress. The mattress-type movement sensors are inexpensive and unobtrusive, and thus provide an interesting tool for sleep research.

Screening Sleep Disordered Breathing in Stroke Unit

In acute stroke, OSA has been found to impair rehabilitation and increase mortality but the effect of central apnea is more unclear. The aim of the present study was to evaluate the feasibility of using limited ambulatory recording system (sleep mattress to evaluate nocturnal breathing and EOG-electrodes for sleep staging) in sleep disordered breathing (SDB) diagnostics in mild acute cerebral ischemia patients and to discover the prevalence of various SDB-patterns among these patients. 42 patients with mild ischemic stroke or transient ischemic attack were studied. OSA was found in 22 patients (52.4%). Central apnea was found in two patients (4.8%) and sustained partial obstruction in only one patient (2.4%). Sleep staging with EOG-electrodes only yielded a similar outcome as scoring with standard rules. OSA was found to be common even after mild stroke. Its early diagnosis and treatment would be favourable in order to improve recovery and reduce mortality. Our results suggest that OSA can be assessed by a limited recording setting with EOG-electrodes, sleep mattress, and pulse oximetry.

Evaluation of the different sleep-disordered breathing patterns of the compressed tracheal sound

OBJECTIVE Suitability of the compressed tracheal sound signal for screening different sleep-disordered breathing patterns was evaluated. The previous results suggest that the plain pattern in the compressed sound signal represents mostly normal, unobstructed breathing, the thick pattern consists of periodic apneas/hypopneas and during the thin pattern, flow limitation in the nasal cannula signal is abundant. METHODS Twenty-seven patients underwent a polysomnography with a tracheal sound and oesophageal pressure monitoring. The tracheal sound data was compressed and scored visually into three different breathing patterns. The percentage of oesophageal pressure values under -8cm H2O, the minimum pressure value and the average duration of the breathing cycles were extracted from 10-min episodes of those plain, thick and thin patterns. In addition, the spectral contents of the tracheal sound during the different breathing patterns were evaluated. RESULTS The percentage of time when the oesophageal pressure negativity increased was highest during the thin pattern and lowest during the plain pattern. In addition, the thin pattern presented most high frequency components in the 1001-2000Hz frequency band of the tracheal sound. CONCLUSIONS The results confirmed our previous findings that both the thick and thin patterns seem to consist of obstructed breathing, whereas during the plain pattern the breathing is normal, unobstructed. SIGNIFICANCE Most screening methods for sleep-disordered breathing reveal only periodic apneas/hypopneas, but with the compressed sound signal the sustained partial obstruction can be estimated as well.

Heart rate variability evaluation of Emfit sleep mattress breathing categories in NREM sleep

OBJECTIVE Heart rate variability (HRV) analysis of obstructive sleep apnea patients reveals an increase in sympathetic activity. Sleep disordered breathing (SDB) can be also assessed with sleep mattress sensors, as the Emfit sensor, by dividing the signal into different breathing categories. In addition to normal breathing (NB) and periodic apneas/hypopneas (POB), the sleep mattress unveils a breathing category consisting of sustained partial obstruction (increased respiratory resistance, IRR). The aim of our study was to evaluate HRV during these three breathing categories in NREM sleep. METHODS 53 patients with suspected SDB underwent an overnight polysomnography with an Emfit mattress. The Emfit signal was scored in 3-min epochs according to the established rules. The NB, POB, and IRR epochs were combined to as long NB, POB and IRR periods as possible and HRV was calculated from at least 6-min epochs. RESULTS The meanHR did not differ between the breathing categories. HRV parameters revealed an increase in sympathetic activity during POB. The mean LF/HF ratio was highest during POB (3.0) and lowest during IRR (1.3). During NB it was 1.7 (all p-values ⩽ 0.001). Interestingly sympathetic activity decreased and parasympathetic activity increased during IRR as compared to NB (the mean HF power was 1113.8 ms(2) during IRR and 928.4 ms(2) during NB). CONCLUSIONS The HRV findings during POB resembled HRV results of sleep apnea patients but during sustained prolonged partial obstruction a shift towards parasympathetic activity was achieved. SIGNIFICANCE The findings encourage the use of sleep mattresses in SDB diagnostics. In addition the findings suggest that sustained partial obstruction represents its own SDB entity.

Detection of Snores Using Source Separation on an Emfit Signal

Snoring (SN) is an early sign of upper airway dysfunction, and it is strongly associated with obstructive sleep apnea. SN detection is important to monitor SN objectively and to improve the diagnostic sensitivity of sleep-disordered breathing. In this study, an automatic snore detection method using an electromechanical film transducer (Emfit) signal is presented. Representative polysomnographs of normal breathing and SN periods from 30 subjects were selected. Individual SN events were identified using source separation applying nonnegative matrix factorization deconvolution. The algorithm was evaluated using manual annotation of the polysomnographic recordings. According to our results, the sensitivity, and the positive predictive value of the developed method to reveal snoring from the Emfit signal were 82.81% and 86.29%, respectively. Compared to other approaches, our method adapts to the individual spectral snoring profile of the subject rather than matching a particular spectral profile, estimates the snoring intensity, and obtains the specific spectral profile of the snores in the epoch. Additionally, no training is necessary. This study suggests that it is possible to detect individual SN events with Emfit mattress, which can be used as a contactless alternative to more conventional methods such as piezo-snore sensors or microphones.