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Volume 08 No. 02
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Accepted Papers

Scientific Investigations

Neurophysiological Two-Channel Polysomnographic Device in the Diagnosis of Sleep Apnea

Álex Ferré, M.D.1,2; Gabriel Sampol, Ph.D.1,3,4; Maria José Jurado, M.D.1,2; Roser Cambrodi, M.D.1,2; Patricia Lloberes, Ph.D.1,3,4; Odile Romero, M.D.1,2,4
1Multidisciplinary Sleep Unit; 2Clinical Neurophysiology Department; 3Pneumology Department, Hospital Universitari Vall d'Hebron, Universitat Autónoma de Barcelona, Barcelona, Spain; 4CIBER de Enfermedades Respiratorias (CIBERES), Barcelona, Spain


Study Objective:

Our objective was to evaluate a portable device (Somté, Compumedics, Australia), which incorporates 2 neurophysiological channels (electroencephalography and electrooculography) with cardiorespiratory monitoring for the diagnosis of obstructive sleep apnea (OSA).


Full polysomnography (PSG) and Somté recordings were simultaneously performed in 68 patients with suspected OSA. Data were analyzed blindly by 2 scorers.


A good agreement between methods in sleep efficiency was observed (68.8% [18.4] with PSG vs 68% [19.1] with Somté [p: n.s.] for scorer 1, and 67.5% [19.1] vs 68.4% [18.5; p: n.s.] for scorer 2). The apnea-hypopnea index (AHI) obtained with Somté was lower than with PSG: 19 (17.8) vs 21.7 (19) (p < 0.001) for scorer 1, and 16.6 (16.7) vs 20 (18.8) (p < 0.001) for scorer 2. The sensitivity of Somté for a PSG-AHI > 5 was 91% for scorer 1 and 90% for scorer 2, while specificity was 77% and 90%, respectively. The areas under the receiver operating curve for different PSG-AHI cutoff points (≥ 5, ≥ 15, and ≥ 30) were 0.81, 0.90, and 0.86, respectively, for scorer 1, and 0.90, 0.88, and 0.83 for scorer 2.


These data suggest that Somté is an effective device to identify sleep and respiratory variables in patients with suspected OSA.


Ferré Á; Sampol G; Jurado MJ; Cambrodi R; Lloberes P; Romero O. Neurophysiological two-channel polysomnographic device in the diagnosis of sleep apnea. J Clin Sleep Med 2012;8(2):163-168.

Obstructive sleep apnea syndrome (OSA) is a highly prevalent disorder1 and a well-documented risk factor for impaired quality of life,2 cardiovascular disease and mortality,35 and accidents.6 A number of recommended methods are used for diagnosing OSA. In 1994, the American Sleep Disorders Association, now the American Academy of Sleep Medicine (AASM), defined 4 levels for sleep studies, based on the number and type signals recorded.7 Type 1, known as full attended polysomnography (PSG), is the “gold standard” for the diagnosis of OSA; however, this procedure is both labor- and resource-intensive, leading to long waiting lists in sleep laboratories.8 For these reasons, many laboratories have incorporated simpler tests in order to facilitate the diagnosis of OSA. Type 2 is an ambulatory PSG. The most widely used technique is the type 3 study or respiratory polygraphy,9 which allows for the assessment of cardiorespiratory variables only, without neurophysiological parameters. However, the lack of sleep variables in type 3 studies in patients with suspected OSA has two potentially relevant limitations. First, without data on sleep efficiency, the apnea-hypopnea index (AHI) is estimated based on recorded time in bed. Second, hypopnea is defined as a reduction of airflow usually associated with a desaturation; hypopnea episodes characterized by the presence of transient electroencephalographic arousals following airflow reduction but without desaturation are not identified. A number of studies have been conducted comparing type 3 devices with conventional PSG, which have shown good AHI concordance. Customarily, patients presenting classic OSA symptoms (usually somnolence) are selected for these studies,1017 which is a clinical characteristic associated with heightened sleep efficiency throughout the sleep study.18 Furthermore, some studies do not measure the number of hypopneas based on arousal criteria during the PSG.15,19,20 These study design choices favor results that will yield good AHI concordance with both methods.


Current Knowledge/Study Rationale: Portable monitoring testing is increasingly being used to evaluate patients with suspected sleep apnea (OSA). The most widely used approach are type 3 studies or respiratory polygraphy, but the obtained Apnea-Hypopnea Index with this technique could be affected by its lack of sleep variables.

Study Impact: The addition of two neurophysiological channels, EEG and EOG, to respiratory polygraphy showed high diagnostic accuracy for OSA. This approach could be a complementary diagnostic alternative to full polysomnography and respiratory polygraphy.

Based on these considerations, we evaluated the potential value of a commercially available portable device (Somté, Compumedics, Abbotsford, Australia), which allows for the inclusion of 2 high-frequency channels when assessing cardiorespiratory variables. Previously, Cunnington et al.21 used this by adding an EEG channel and a leg movement channel in order to detect arousals, although they did not measured sleep efficiency or sleep stages. In this study, we have used an EEG channel and an EOG channel to score sleep stages in patients with suspected OSA. We compared results obtained with this device to those obtained simultaneously using PSG in the sleep laboratory.



The study group consisted of a total of 68 patients with suspected OSA who were consecutively referred to our sleep unit. We obtained a detailed medical history, the Epworth sleepiness scale, and performed a physical examination for each patient. Exclusion criteria were significant commorbidities (dialysis-dependent renal failure, congestive heart failure, severe chronic obstructive pulmonary disease, previous stroke or psychiatric disorders). The protocol was approved by our institutional review board, and signed informed consent was obtained from all patients.


Fully attended PSG and non-attended Somté overnight recordings were simultaneously conducted for each participant. Patients were admitted to the unit in the evening, and both system sensors were attached by expert technicians in the sleep laboratory. Every system used its own sensors except the nasal cannula, which used a single cannula attached to the patient and a Y-connector to split the cannula tubing to the 2 devices. The sleep study began at 23:00 and ended at 06:30. Each recording was evaluated manually by 2 expert scorers without knowledge of the patient's identity or the results obtained with the other system.


This procedure included the following: electroencephalogram (EEG; F3, F4, C1, C3, O1, O2, M1, M2), bilateral electroculogram (EOG), submental electromyogram (EMG), oronasal airflow (thermistor and nasal cannula), thoracic and abdominal movements, arterial oxygen saturation (SaO2), snoring, electrocardiogram, leg movements, and body position recordings. All PSG data were collected and stored using an E-Series digital system (Compumedics, Abbotsford, Australia).


The Somté polygraph allows the recording of 2 neurophysiological signals. Recorded signals included EEG (C3/A2) and EOG (left eye movements channel referenced to right eye), airflow (nasal cannula), thoracic and abdominal movements, SaO2, body position, heart rate, and snoring (Figure 1). The sleep study technician did not have access to the signals being registered during the study and was instructed not to alter any of the sensor attachments throughout the night.

Somté screen shot

Black line correlates the end of respiratory event (hypopnea) with the cortical arousal.


Figure 1

Somté screen shotBlack line correlates the end of respiratory event (hypopnea) with the cortical arousal.

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Scoring Criteria

Sleep stages were scored using Rechtschaffen and Kales standard criteria.22 Arousals were identified on PSG recordings according to AASM standard criteria.23 Given the absence of EMG channel, the following modifications to these criteria were introduced when scoring Somté recordings:

  1. Sleep staging: We identified NREM sleep stages using standard criteria without considering any reference to EMG activity. Based on the criteria used by Dauvilliers et al.24 in REM sleep behavior disorder, REM sleep was identified when low amplitude, mixed frequency activity in the EEG channel (with or without sawtooth waves) was accompanied by rapid eye movements. The chosen EOG montage, referencing left eye movements to the right eye, maximized the signal amplitude of conjugate eye movements typical of REM sleep.12 REM sleep end was considered when K complexes or sleep spindles (N2 stage), delta waves (20% to 50% of the epoch, N3; > 50% of the epoch, N4), alpha activity, or body movement (> 50% of the epoch wakefulness) was present in the epoch.

  2. Arousals were identified according to standard criteria23 during NREM sleep; in REM sleep, they were coded when an EMG artifact rapid (> 16 Hz) and high amplitude (> 8 μV) activity lasting > 3 sec was identified on the EEG and/or EOG channels.

  3. Respiratory events: Apnea was defined as a decrease in airflow amplitude (nasal cannula) to < 10% for ≥ 10 seconds. Differentiation was made between obstructive and central apneas according to respiratory effort channels (presence or absence of thoracoabdominal movement). Hypopnea was defined as ≥ 50% reduction in flow amplitude of the surrounding baseline for ≥ 10 sec associated with a cyclical dip in SaO2 ≥ 3% or an arousal.25 The apnea-hypopnea index was defined as the sum of the number of apneas plus hypopneas divided by total sleep time.

Statistical Analysis

Descriptive variables were expressed as mean (standard deviation) or percentages. Paired or unpaired t-test was used to compare means. The agreement between the AHI obtained with PSG and Somté was evaluated using the Bland and Altman method26 and Pearson correlation. The diagnostic accuracy of Somté was evaluated by obtaining receiver operating characteristic curves, and by calculating the sensitivity, specificity, positive and negative predictive values, and positive and negative likelihood ratios for different cutoff points of the AHI during PSG. To determine the agreement between the 2 observers in the analysis of the Somté studies, the ? coefficient of agreement was calculated. A p-value < 0.05 was considered statistically significant. The statistical analysis was performed using SPSS statistical software (SPSS 12.0; SPSS Inc., Chicago, IL, USA).


Sixty-eight patients completed the protocol, and all studies were considered valid for analysis. Patient characteristics are described in Table 1. Sleep and respiratory data from PSG and Somté are shown in Tables 2 and 3, respectively. Small but statistically significant differences in time spent at different sleep phases, and in awake time during the night, were observed when comparing systems; however, there were no significant differences in sleep efficiency, sleep latency, REM sleep latency, and number of sleep cycles. The AHI obtained with Somté was lower than with PSG: 19 (17.8) vs. 21.7 (19) (p < 0.001) for scorer 1; 16.6 (16.7) vs. 20 (18.8) (p < 0.001) for scorer 2.

Population characteristics

Age (years)55.9 (14.5) (R: 15-81)
BMI (kg/m2)28.5 (4.8) (R: 15-81)
Epworth Sleepiness Scale8.6 (9.5) (R: 15-81)

[i] M, male; F, female; SD, standard deviation; BMI, body mass index; R, range.

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Table 1

Population characteristics

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Sleep data

Scorer 1
Scorer 2
Scorer 1- Scorer 2
Mean dif (SD)pMean dif (SD)p
E (%)68.8 (18.4)68.0 (19.1)0.35167.5 (19.1)68.4 (18.5)0.1491.2 (5.6)0.069−0.3 (5.8)0.601
SL (min)26.7 (48.1)32.5 (57.4)0.09332.5 (57.8)24.7 (34.5)0.1400.2 (22.4)0.9947.7 (37.9)0.095
RL (min)125.4 (78.2)126.9 (80.4)0.829130.7 (78.7)133.7 (89.8)0.665−3.59 (29.0)0.358−1.9 (40.2)0.715
WASO (min)95.4 (64.9)87.7 (62.7)0.010*96.0 (64.7)97.8 (62.8)0.689−0.6 (17.9)0.777−10.0 (36.5)0.026*
REM (min)38.8 (27.6)41.2 (29.9)0.05437.8 (26.9)39.1 (27.4)0.3492.8 (9.6)0.022*3.7 (14.2)0.033*
NREM (min)255.7 (74.4)253.2 (78.14)0.303253.4 (73.3)255.8 (75.4)0.3051.5 (16.3)0.426−5.7 (22.9)0.042*
N1 (min)20.8 (12.7)17.2 (14.0)< 0.001*38.6 (25.4)33.3 (20.8)0.005*−17.7 (20.6)< 0.001*−16.0 (16.1)< 0.001*
N2 (min)186.2 (67.1)189.9 (71.1)0.168166.6 (64.1)165.5 (62.7)0.75219.6 (21.0)< 0.001*24.3 (27.6)< 0.001*
N3 (min)27.9 (19.2)25.8 (22.5)0.21829.4 (23.4)35.5 (25.7)0.004*−1.5 (11.4)0.269−9.7 (19.8)< 0.001*
N4 (min)19.4 (23.9)17.0 (21.4)0.05618.7 (22.6)21.4 (24.8)0.017*1.2 (6.8)0.147−4.4 (13.9)0.011*
NSC2.3 (1.4)2.3 (1.4)0.7082.1 (1.3)2.5 (3.7)0.2720.1 (0.5)< 0.009*−0.2 (3.2)0.578

[i] PSG, nocturnal polysomnography; SD, standard deviation; Mean dif, mean difference; min, minutes; E, sleep efficiency; SL, sleep latency; RL, REM latency; WASO, wake after sleep onset; REM, REM sleep; NREM, no REM sleep; N1; stage 1; N2, stage 2; N3, stage3; N4, stage 4; NSC, number of sleep cycles.

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Table 2

Sleep data

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Respiratory events

Scorer 1
Scorer 2
PSG Mean (SD)SOMTE Mean (SD)pPSG Mean (SD)SOMTE Mean (SD)p
AI7.0 (15.3)9.2 (15.7)0.0067.7 (16.0)7.0 (13.4)0.444
HI14.6 (12.6)9.7 (9.1)< 0.00112.1 (11.9)9.8 (10.8)0.025
AHI21.7 (19.0)19.0 (17.8)< 0.00120.0 (18.8)16.6 (16.7)< 0.001

[i] SD, standard deviation; AI, apnea index; HI, hypopnea index; AHI, apnea-hypopnea index; PSG, nocturnal polysomnography.

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Table 3

Respiratory events

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Table 4 reports the sensitivity, specificity, positive predictive value, and negative predictive value for the AHI obtained with Somté, according to AHI cutoff points ≥ 5, ≥ 15, and ≥ 30 in the PSG. The κ coefficients of agreement between the 2 scorers for these cutoff points were 0.66, 0.70, and 0.85, respectively. With PSG, the κ coefficients for these cutoff values were 0.84, 0.65, and 1, respectively. There was a significant correlation between the AHI obtained with PSG and Somté (r = 0.959 for scorer 1 and r = 0.937 for scorer 2; Figure 2).

Sensitivity, specificity, and positive and negative predictive values of Somté, and κ coefficient of agreement between scorers for different AHI cutoff values

SOMTE Scorer 1
SOMTE Scorer 2
n (%)n (%)SensSpecPPVNPVLR+LR−n (%)SensSpecPPVNPVLR+LR−
    ≥ 555 (81)53 (78)91%77%94%67%40.1252 (80)90%90%98%60%90.11
    ≥ 1536 (53)32 (47)86%97%97%86%24.70.1425 (36)83%92%89%88%10.50.18
    ≥ 3018 (26)13 (19)61%96%85%87%15.30.4112 (17)67%100%100%89%20.33

[i] n, number; Sens, sensitivity; Spec, specificity; PPV, positive predictive value; NPV, negative predictive value; LR+, positive likelihood ratio; LR−, negative likelihood ratio; AHI, apnoea hypopnoea index; PSG, nocturnal polysomnography.

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Table 4

Sensitivity, specificity, and positive and negative predictive values of Somté, and κ coefficient of agreement between scorers for different AHI cutoff values

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Scatter plots showing the linear correlation between PSG and Somté for AHI


Figure 2

Scatter plots showing the linear correlation between PSG and Somté for AHI

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Figure 3 shows Bland and Altman plots comparing the AHI from the 2 methods, with only 4 (6%) outliers for scorer 1 and 5 (7%) for scorer 2. No systematic trend was found, and the mean observed difference was 2.6 (5.4) for scorer 1 and 3.4 (6.6) for scorer 2.

Bland and Altman plots showing the mean difference (thick line) and the limits of agreement (2 SD; dotted line) for AHI with PSG and Somté


Figure 3

Bland and Altman plots showing the mean difference (thick line) and the limits of agreement (2 SD; dotted line) for AHI with PSG and Somté

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The areas under the receiver operating characteristic curve of the AHI obtained with Somté for different cutoff points of PSG are shown in Table 5.

Area under the receiver operator characteristics curve of the AHI with Somté for different cutoff points for the AHI with PSG

SOMTE Scorer 2
    ≥ 50.810.66-0.960.900.78-1.00
    ≥ 150.900.82-0.980.880.78-0.97
    ≥ 300.860.73-0.990.830.70-0.97

[i] AHI, apnea-hypopnea index; AUC, Area under curve; CI95%, 95% confidence interval.

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Table 5

Area under the receiver operator characteristics curve of the AHI with Somté for different cutoff points for the AHI with PSG

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The study shows good agreement between the Somté system and full PSG results in adult patients referred for assessment of OSA. The two neurophysiological channels incorporated by the device allowed for an accurate estimation of both sleep parameters and respiratory events.

Population-based studies have shown that the majority of patients with OSA are not sleepy1,27,28 and that the absence of somnolence is not associated with a better long-term prognosis.29,30 Additionally, other population-based27,28 and clinical series3135 studies have reported high variability in sleep efficiency in OSA patients without somnolence, being sleep efficiency notably low in a subgroup of them. In line with these observations, our patients had a mean ESS < 10, and 26.4% of them showed a sleep efficiency < 60% during the sleep study. Furthermore, insomnia is also associated with low sleep efficiency; we now know that it is a frequent complaint in OSA patients36 and that a significant percentage of patients with insomnia have OSA.37 PSG in patients with OSA and insomnia shows lower sleep efficiency.38 For all these reasons, we believe that in some OSA patients, an accurate determination of AHI is only achieved if we obtain sleep efficiency during the sleep study.

To our knowledge this is the first time that sleep in patients with suspected OSA has been scored with only two neurophysiological channels. Thus, in comparing against PSG results, we found statistically significant differences for several sleep stages. However, these differences were small, similar to those reported when comparing inter-laboratory agreement in sleep staging with PSG39,40 and of no clinical significance in OSA diagnosis.

There are several definitions of hypopnea that include different requirements for concomitant oxyhemoglobin desaturation and/or arousal in association with an airflow signal change.25 There are differences in the measured AHI depending on the adopted definition. One of the factors contributing to these differences is the lack of inclusion of the arousal criteria, leading to a markedly lower AHI value than that obtained when it is included.4143 Furthermore, several studies have shown improved somnolence and quality of life when OSA is treated with nasal CPAP and obstructive events and arousals are abolished.34,44,45 After monitoring for AHI, the frequency of arousals is independently associated with fatigue symptoms in OSA patients.21 For these reasons, the AASM has maintained as a valid option the definition of hypopnea as a reduction of airflow associated with an arousal.25 Our approach with Somté allowed us to identify arousal-related hypopneas, and the obtained AHI showed good agreement with the one obtained with PSG.

The study has strong points and limitations that must be emphasized. On the one hand, we have included a wide group of patients with different degrees of suspected OSA, 28% of whom are over 65 years of age. Also, PSG and Somté studies were performed simultaneously, avoiding internight46 and postural variability,47 and the studies were manually scored as recommended.14,48 Furthermore, our data were analyzed by two scorers and the κ coefficients of agreement obtained for different AHI cutoff points were good or excellent according to accepted criteria.49 On the other hand, while studies with Somté were performed in our sleep unit, this device could be especially useful for home sleep testing, reducing the long wait time for diagnostic tests in patients with suspected OSA. However, the studies were unattended by sleep technicians, and we think that our results could be extrapolated to those obtained in a home study. Another limitation that we faced is that we studied patients referred to the sleep unit for suspected OSA; although many patients did not have somnolence, OSA prevalence was 80%. Our findings does do not necessarily support the use of Somté as a tool for screening OSA in a general population with much lower pretest probabilities. Another constraint is that we relied on R&K criteria. While our main objective was to establish an effective correlation with sleep efficiency, we also established a good correlation with the various sleep stages. Towards this end, we would need to further review these results using new AASM coding criteria.

In conclusion, in our study the Somté recording device has shown high diagnostic accuracy for OSA. Our results suggest that this device could be a complementary diagnostic alternative to PSG and respiratory polygraphy. Further studies are required to define what clinical characteristics are needed for optimal implementation of this approach.


This was not an industry supported study. The authors have indicated no financial conflicts of interest.


The authors thank our night sleep technicians (M. Bartolomé, A. Garcia, and J. Ros), and A. Saheb specially, for their assistance in performing the sleep studies and data management.



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