An electrocardiogram-based analysis evaluating sleep quality in patients with obstructive sleep apnea.

Authors:
Harrington J, Schramm PJ, Davies CR, Lee-Chiong TL Jr.

Reference:
Sleep Breath. 2013 Sep;17(3):1071-8.

Objectives:
The study compares polysomnography (PSG) and cardiopulmonary coupling (CPC) sleep quality variables in patients with (1) obstructive sleep apnea (OSA) and (2) successful and unsuccessful continuous positive airway pressure (CPAP) response.

Conclusions:
Tests differentiated no and moderate to severe OSA groups by REM %, HFC, VLFC, and LFC/HFC ratio variables. The successful CPAP therapy group had more HFC, less LFC, and e-LFCBB compared to the unsuccessful CPAP therapy group. HFC ≥ 50 % showed high sensitivity (77.8 %) and specificity (88.9 %) in identifying successful CPAP therapy.

Practical Significance:
The results support the use of the SleepImage system to investigate and objectively measure sleep quality in patients complaining of a sleep disorder.

View Publication:

 

An Electrocardiogram-based Technique to Assess Cardiopulmonary Coupling During Sleep

Authors:
Thomas RJ, Mietus JE, Peng CK, Goldberger AL

Reference:
SLEEP 2005;28:1151-1161

Objectives:
Evaluate a new automated measure of CPC during sleep using a single-lead electrocardiographic (ECG) signal

Conclusions:
A sleep spectrogram derived from information in a single lead electrocardiogram can be used to dynamically track cardiopulmonary interactions. The 2 distinct (bimodal) regimes demonstrate a closer relationship with visual cyclic alternating pattern (CAP) and non-cyclic alternating pattern states than with standard sleep stages. This technique may provide a complementary approach to the conventional characterization of graded non-rapid eye movement (NREM) sleep stages

Practical Significance:
This seminal work establishes the link between High Frequency CPC with good sleep quality, and Low Frequency CPC with poor quality sleep

View Publication:

 

Applications of evolving technologies in sleep medicine

Authors:
Verbraecken J

Reference:
Breathe, December 2013, Volume 9, No 6

Objectives:
Nocturnal polysomnography (PSG) is the most important laboratory technique in the management of sleep–wake disturbances and is considered the “gold standard” [1]. New sensor technologies are entering the field, and rapid development in telecommunications and mobile technology has accelerated the introduction of telemedicine as a viable and reliable option [2]. The present broad review is an amalgam of the current knowledge with proposed new sensors and remote control. The reader should note that not all of the techniques discussed here have strong clinical validation, and this should be considered when purchasing equipment.

Conclusions:
Traditional sleep monitoring methods use a variety of leads and probes on the patient’s face and body to gather data. Additional information can be achieved from these signals by advanced processing based on complex algorithms. Moreover, a number of signals that are not traditionally used in clinical PSG will become of interest for specific patient categories. We are also faced with the development of innovative noncontact systems based on movement detection using radar and infrared technology. The idea of automatic sleep evaluation and monitoring through signals that are integrated into the environment (a sensorised bed) or through wearable textile technology will change the traditional paradigm of clinical polysomnography. Implementation of wireless applications and remote monitoring will lead to new platforms and evolve towards low-threshold sleep telemedicine. The available evidence base has, however, lagged far behind.

Practical Significance:
Based on the information obtained by electroencephalography, electro-oculography and electromyography (EMG), sleep stages can be defined according to the criteria of Rechtschaffenand Kales [3] and the new American Academy of Sleep Medicine criteria [4]. Ventilation is often measured qualitatively by means of thermistors but is more appropriately measured with nasal pressure cannulae, or by means of a pneumotachograph, connected with a full face mask, or calibrated inductance plethysmography, although calibration of this is difficult [5]. Breathing effort can also be detected by recording movements of the chest and abdomen, surface EMG, snoring, and changes in arterial blood pressure, but most effectively by detection of intrathoracic pressure swings. These swings can be detected by measuring oesophageal pressure. Movements of the chest and abdomen can be recorded with strain gauges (which detect changes in resistance according to length changes), inductance plethysmography or Respitrace (with detection of inductance characteristics of electrical conductors), impedance or even a static charge sensitive bed (which detects respiratory movements). If respiratory effort is detected during an apnoea, this can be explained by occlusion of the upper airways. Oxygen saturation is measured by means of pulse oximetry (SpO2), as well as transcutaneous carbon dioxide tension (PCO2). Sound recording is another method to detect ventilation. Frequency analysis of the sounds (predominantly snoring) can deliver more information on flow limitation. Routinely, body position (position sensor on the chest) is also recorded. The combined application of these measurement techniques allows the assessment of normal and abnormal physiological events in relation to sleep structure [6].

View Publication:

 

Differentiating Obstructive from Central & Complex Sleep Apnea Using an Automated Electrocardiogram-based Method

Authors:
Thomas RJ, Mietus JE, Peng CK, Gilmartin G, Daly RW, Goldberger AL, Gottlie DJ.

Reference:
Sleep. 2007 Dec;30(12):1756-69.

Objectives:
Complex sleep apnea is defined as sleep disordered breathing secondary to simultaneous upper airway obstruction and respiratory control dysfunction. The objective of this study was to assess the utility of an electrocardiogram (ECG) based CPC technique to distinguish obstructive from central or complex sleep apnea

Conclusions:
ECG based spectral analysis allows automated, operator-independent characterization of probable interactions between impaired respiration and upper airway anatomical obstruction. The clinical utility of spectrographic classification, especially in predicting failure of positive airway pressure therapy, remains to be more thoroughly tested

Practical Significance:
Using the Heart Health Study population of 3989 subjects, this study shows that CPC not only differentiated obstructive vs. central vs. complex sleep apnea, but it positively correlated with periodic breathing episodes in PSG and was the strongest predictor of success or failure with PAP titration.

View Publication:

 

HHT based cardiopulmonary coupling analysis for sleep apnea detection

Authors:
Dongdong Liu, Xiaochen Yang, Guangfa Wang, Jing Ma, Yanhui Liu, Chung-Kang Peng, Jue Zhang, Jing Fang

Reference:
Sleep Medicine 13(5):503-509, May 2012

Objectives:
To validate the feasibility of the Hilbert–Huang transform (HHT) based cardiopulmonary coupling (CPC) technique in respiratory events detection and estimation of the severity of apnea/hypopnea.

Conclusions:
The HHT-CPC spectrum provides much finer temporal resolution and frequency resolution (8s and 0.001Hz) compared with the original CPC (8.5min and 0.004Hz). The area under the ROC curve of pLFC was 0.79 in distinguishing respiratory events from normal breathing. Significant differences were found in TVDF among groups with different severities of OSAHS (normal, mild, moderate, and severe, p<0.001). TVDF has a strong negative correlation with the apnea/hypopnea index (AHI, correlation coefficient −0.71).

Practical Significance:
The spectrographic markers, pLFC and TVDF can be used to identify respiratory events and represent the disruption extent of sleep architecture in patients with sleep apnea/hypopnea, respectively.

View Publication:

 

Mapping Sleep Using Coupled Biological Oscillations

Authors:
Thomas RJ, Mietus JE

Reference:
Conf. Proc IEEE Eng Med Biol. Soc. 2011;2011:1479-82.

Objectives:
To examine the utility of an electrocardiogram-derived sleep spectrogram to provide a different view of sleep

Conclusions:
Non-electroencephalogram (EEG) recordings can provide an alternative approach to viewing sleep quality.

Practical Significance:
Novel insights into physiology and pathology of sleep can be obtained through the coupling of ECG and respiratory signal influences on the ECG R wave.

View Publication:

 

Relationship between delta power and the electrocardiogram-derived cardiopulmonary spectrogram: possible implications for assessing the effectiveness of sleep.

Authors:
Thomas RJ, Mietus JE, Peng CK2, Guo D, Gozal D, Montgomery-Downs H, Gottlieb DJ, Wang CY, Goldberger AL.

Reference:
Sleep Med. 2014 Jan; 15(1):125-31.

Objectives:
To evaluate the hypothesis that that slow-wave EEG power would show a relatively fixed-time relationship to periods of high-frequency CPC.

Conclusions:
The overall correlation (r) between delta power and high-frequency coupling (HFC) power was statistically significant.

Practical Significance:
The results support a tight temporal relationship between EEG slow wave power and high frequency cardiopulmonary coupling.

View Publication:

 

Technical advances in the characterization of the complexity of sleep and sleep disorders.

Authors:
Bianchi MT, Thomas RJ.

Reference:
Prog Neuropsychopharmacol Biol Psychiatry. 2013 Aug 1;45:277-86.

Objectives:
A review of the spectrum of approaches that have been leveraged towards improved understanding of the complexity of sleep.

Conclusions:
The complexity of sleep physiology has inspired alternative metrics that are providing additional insights into the rich dynamics of sleep. Electro-encephalography, magneto-encephalography, and functional magnetic resonance imaging represent advanced imaging modalities for understanding brain dynamics.

Practical Significance:
These methods are complemented by autonomic measurements that provide additional important insights.

View Publication:

 

Wearable Sleep Epidemiology In The Framingham Heart Study

Authors:
EJ Heckman, R Salazar, S Hardy, E Manders, Y Liu, R Au, G O’Connor, R Thomas

Reference:
Sleep, Volume 40, Issue suppl_1, 28 April 2017, Pages A289

Objectives:
Wearable devices for sleep assessments offer a cost-effective and convenient alternative to traditional measures of sleep. Devices are now available to measure oxygenation, respiration electrocardiogram, and electroencephalogram in the home environment. This study assessed standard (oximetry) and novel (cardiopulmonary coupling) measures of sleep state in a well-established epidemiology cohort.

Conclusions:
The results suggest that home/wearable assessment of sleep is 1) feasible, cost-effective, and yields reliable results; 2) inter-individual differences are stable; 3) measures can be readily repeated; 4) in-person visits are not required, markedly simplifying data collection. Both standard and novel measures can be collected.

Practical Significance:
A total of 972 participants agreed to participate. 126 participants were unable or refused to complete the study. 830 and 836 participants obtained at least 4 hours of data with the M1 and oximetry device for at least one night, respectively. 574 participants wore both devices for 2 consecutive nights (803 wore M1, 695 wore Ox for 2 consecutive nights). The mean (SD) were as follows: HFC 43.5%(18.8), LFC 37.28%(17.03), ODI 8.3(8.5), oxygen saturation below 90% 48.1(77.24) minutes, and 52.5% of the sample had narrow band coupling. The ICC for these variables ranged from 74.5%-99.9%, suggesting high night to night data and physiological signal stability. Associations with common medical co-morbidities will be presented.

View Publication: