Effect of a digital patient motivation and support tool on CPAP/APAP adherence and daytime sleepiness: a randomized controlled trial.

Unlabelled: The purpose of this study was to assess the effect of a digital patient support (DPS) tool, complementary to standard care on continuous or automatic positive airway pressure (auto)CPAP adherence and daytime sleepiness after 12 weeks in patients diagnosed with severe obstructive sleep apnea (OSA). All patients with apnea-hypopnea index (AHI) ≥ 30 per hour were prospectively included and randomized to receive standard care (SC) or standard care with personalized DPS via a mobile app prototype version (SC + DPS). Patients in the SC + DPS arm received additionally automated feedback on their therapy, motivational messages and therapy recommendations.

Reliability of respiratory event detection with continuous positive airway pressure in moderate to severe obstructive sleep apnea - comparison of polysomnography with a device-based analysis.

Purpose: Monitored polysomnography (PSG) is considered the gold standard technique to diagnose obstructive sleep apnea (OSA) and titrate continuous positive airway pressure (CPAP), the accepted primary treatment method. Currently, the American Academy of Sleep Medicine (AASM) considers automatic PAP therapy initiation at home comparable to laboratory titration and recommends telemonitoring-guided interventions. Advanced CPAP devices evaluate and report the residual apnea-hypopnea index (AHI).

Extended evaluation of the efficacy of a proactive forced oscillation technique-based auto-CPAP algorithm.

Purpose: Previous studies revealed substantially varying therapy efficacy of automatic continuous positive airway pressure (APAP) devices in the treatment of obstructive sleep apnea (OSA). We evaluated the efficacy of a new APAP device using the forced oscillation technique (FOT) to evaluate upper airway obstruction during apneas and flow contour analyses during hypopneas.

Methods: Forty-six initially diagnosed OSA patients were included and the pressure range was set from 5 to 20 hPa.

Feasibility of noninvasive single-channel automated differentiation of obstructive and central hypopneas with nasal airflow.

Background: The identification of obstructive and central hypopneas is considered challenging in clinical practice. Presently, obstructive and central hypopneas are usually not differentiated or scores lack reliability due to the technical limitations of standard polysomnography. Esophageal pressure measurement is the gold-standard for identifying these events but its invasiveness deters its usage in daily practice.

Comparison of upper airway respiratory resistance measurements with the esophageal pressure/airflow relationship during sleep.

Measurement of upper airway resistance is of interest in sleep disordered breathing to estimate upper airway patency. Resistance is calculated with the airflow and respiratory effort signals. However, there is no consensus on a standard for upper airway resistance measurement.

Automatic non-invasive differentiation of obstructive and central hypopneas with nasal airflow compared to esophageal pressure.

The differentiation of obstructive and central respiratory events is a major challenge in the diagnosis of sleep disordered breathing. Esophageal pressure (Pes) measurement is the gold-standard method to identify these events but its invasiveness deters its usage in clinical routine. Flattening patterns appear in the airflow signal during episodes of inspiratory flow limitation (IFL) and have been shown with invasive techniques to be useful to differentiate between central and obstructive hypopneas.

An invasive and a noninvasive approach for the automatic differentiation of obstructive and central hypopneas.

The automatic differentiation of obstructive and central respiratory events is a major challenge in the diagnosis of sleep-disordered breathing. Esophageal pressure (Pes) measurement is the gold-standard method to identify these events. This study presents a new classifier that automatically differentiates obstructive and central hypopneas with the Pes signal and a new approach for an automatic noninvasive classifier with nasal airflow.

Automatic differentiation of obstructive and central hypopneas with esophageal pressure measurement during sleep.

The differentiation between obstructive and central respiratory events is one of the most recurrent tasks in the diagnosis of sleep disordered breathing. Esophageal pressure measurement is the gold-standard method to assess respiratory effort and identify these events. But as its invasiveness discourages its use in clinical routine, non-invasisve systems have been proposed for differentiation.

Assessment of changes in upper airway obstruction by automatic identification of inspiratory flow limitation during sleep.

New techniques for automatic invasive and noninvasive identification of inspiratory flow limitation (IFL) are presented. Data were collected from 11 patients with full nocturnal polysomnography and gold-standard esophageal pressure (Pes) measurement. A total of 38,782 breaths were extracted and automatically analyzed.

Characterization of inspiratory flow limitation during sleep with an exponential model.

Assessing incidence and severity of inspiratory flow limitation (IFL) is of importance for patients suffering of sleep disordered breathing (SDB) in order to diagnose a spectrum of different pathologies. In this study a new exponential equation is proposed to characterize the pressure/flow relationship of IFL and non-IFL breaths. Classical and alternative criteria are applied on the model's predictions in order to assess IFL, and its outcome is compared to the outcome of other models.

Automatic classification of inspiratory flow limitation assessed non-invasively during sleep.

Detection of inspiratory flow limitation (IFL) is being recognized of increasing importance in order to diagnose pathologies related to sleep disordered breathing. Currently, IFL is usually identified with the help of invasive esophageal pressure measurement, still considered the gold-standard reference to assess respiratory effort. But the invasiveness of esophageal pressure measurement and its impact on sleep discourages its use in clinical routine.

Bench model to simulate upper airway obstruction for analyzing automatic continuous positive airway pressure devices.

Background: Automatic positive airway pressure (APAP) devices are increasingly being used in patients with obstructive sleep apnea. Some APAP devices present an unstable behavior when subjected to some events or artifacts. The aims were to develop a bench model capable of reproducing real flow, snoring, and obstructive patterns and to compare the response of APAP devices based on flow and snoring with other devices using, in addition, the forced oscillation technique (FOT).

Evaluation and optimization of different spectral estimation methods for EEG signals.

The goal of this work was the evaluation of various spectral estimation methods with regard to their suitability for classifying EEG data. A test environment was implemented in which the algorithms are optimized and evaluated using various artificial and real EEG data. The methods are based on autoregressive approaches, as well as from FFT, wavelet, and matching pursuit-based spectral estimations.

Miniaturized module for the wireless transmission of measurements with Bluetooth.

The wiring of patients for obtaining medical measurements has many disadvantages. In order to limit these, a miniaturized module was developed which digitalizes analog signals and sends the signal wirelessly to the receiver using Bluetooth. Bluetooth is especially suitable for this application because distances of up to 10 m are possible with low power consumption and robust transmission with encryption.

The wireless monitoring of vital parameters: a design study.

This project shows the way vital parameters can be transmitted and visualized with no connecting cables necessary to the PDA. This was realized using a sensor developed with an integrated Bluetooth interface and a PDA, also equipped with Bluetooth. This radio connection can span up to 10 m, and parameters, such as pulse frequency, oxygen saturation in blood, ECG measurements and plethysmograms, can be transmitted.

Design aspects for novel, telemedical unattended diagnosis and therapy control systems for sleep disorders.

Medical research confirmed the relevance of diagnosis and therapy of sleep-related breathing disorders, revealing prevalence and patho-physiological mechanisms [1-10]. Reliable sleep assessment currently demands examinations in the sleep-lab, which is very technical and time-consuming. Thus, expanding the conventional procedure to meet capacity demands does not seem realistic regarding cost aspects.

[Development of Bluetooth wireless sensors].

Wireless communication could help to overcome current obstacles in medical devices and could enable medical services to offer completely new scenarios in health care. The Bluetooth technology which is the upcoming global market leader in wireless communication turned out to be perfectly suited not only for consumer market products but also in the medical environment [1]. It offers a low power, low cost connection in the medium range of 1-100 m with a bandwidth of currently 723.

Automated sleep stage detection with a classical and a neural learning algorithm--methodological aspects.

For classification tasks in biosignal processing, several strategies and algorithms can be used. Knowledge-based systems allow prior knowledge about the decision process to be integrated, both by the developer and by self-learning capabilities. For the classification stages in a sleep stage detection framework, three inference strategies were compared regarding their specific strengths: a classical signal processing approach, artificial neural networks and neuro-fuzzy systems.

[Artificial intelligence in sleep analysis (ARTISANA)--modelling visual processes in sleep classification].

We describe a novel approach to the problem of automated sleep stage recognition. The ARTISANA algorithm mimics the behaviour of a human expert visually scoring sleep stages (Rechtschaffen and Kales classification). It comprises a number of interacting components that imitate the stepwise approach of the human expert, and artificial intelligence components.

Delayed VO2 kinetics during ramp exercise: a criterion for cardiopulmonary exercise capacity in chronic heart failure.

Purpose: Kinetics of VO2 at onset of constant work rate exercise was previously shown to be slowed in patients with chronic heart failure (CHF) compared with that in healthy normals. Because bicycle ergometry with ramp protocol is usually used for exercise testing with CHF patients, it would be of practical importance if it can be shown that a delay in the time interval of linear increase of VO2 (TILIV) to work rate occurs after beginning ramp exercise. Data of central hemodynamics (CHF) and noninvasive cardiopulmonary parameters (CHF, normals) should also correlate with VO2 delay time if this parameter is related to cardiopulmonary exercise capacity.

Short-term reproducibility of cardiopulmonary measurements during exercise testing in patients with severe chronic heart failure.

Eleven men with severe chronic heart failure (peak cardiac index 4.0 +/- 0.2 L/m2/min), six on a heart transplantation waiting list, were prospectively assessed.

Predictors of response to exercise training in severe chronic congestive heart failure.

We prospectively assessed whether baseline central hemodynamics and exercise capacity can predict improvement of VO2 at ventilatory threshold (VT) after exercise training in patients with severe chronic congestive heart failure. Eighteen patients (mean +/- SEM; age 52 +/- 2 years), half of them listed for transplant, underwent 3 weeks of exercise training (interval cycle and treadmill walking; 5 x/week) and 3 weeks of activity restriction in a random-order crossover trial. Baseline data were not significantly different for groups with exercise training first and activity restriction first: cardiac index at rest (2.

Effects of exercise training and activity restriction on 6-minute walking test performance in patients with chronic heart failure.

Eighteen hospitalized patients with severe chronic heart failure (ejection fraction [mean +/- SEM] 21% +/- 1%) underwent 3 weeks of exercise training (interval bicycle ergometer and treadmill walking training exercises) and 3 weeks of activity restriction in a random-order crossover trial. Before and after exercise training and after activity restriction, a 6-minute walking test was performed to determine the maximum distance walked, hemodynamic and cardiopulmonary responses, norepinephrine levels, and ratings of leg fatigue and dyspnea while walking. A ramp test on bicycle ergometer (increments of 12.

Interval training in patients with severe chronic heart failure: analysis and recommendations for exercise procedures.

This study analyzes a new exercise training procedure, which includes interval exercise training on cycle ergometer (IntCT) (30-s work phases/60-s recovery phases) and on treadmill (60-s work and recovery phases each). Training was applied for 3 wk in 18 patients with severe chronic heart failure (CHF) ((mean +/- SEM) age 52 +/- 2 yr, ejection fraction 21 +/- 1%). Peak VO2 was increased from 12.

Cardiopulmonary determinants of functional capacity in patients with chronic heart failure compared with normals.

Background: Patients with chronic heart failure (CHF) are characterized by abnormal gas exchange and ventilatory responses to exercise.

Hypothesis: This study compares variables obtained from cardiopulmonary exercise testing in 35 patients with CHF with 35 age- and weight-matched healthy subjects. A second goal was to obtain cardiopulmonary variables measured at ventilatory threshold to distinguish patient changes from those of healthy subjects.