Monitoring of nocturnal central sleep apnea in Heart failure patients using noncontact respiratory differences.

Monitoring of respiration patterns allows the early detection of various breathing disorders and may better identify those at risk for adverse acute outcomes in a variety of clinical settings. In this paper, we report on the use of SleepMinder (SM), a bedside non-contact Doppler-based biomotion recording sensor, to monitor remotely the nocturnal respiration patterns of 50 patients with systolic Heart failure (HF) while undergoing a lab based Polysomnography (PSG) test. A new respiration rate (RR) monitoring algorithm was developed based on the collected overnight radar signals. Two schemes of RR scoring were utilized: respiratory rate count (RRC) and instantaneous respiratory rates (IRR). Analysis of SM vs. PSG revealed that the mean/median IRR scored by SM is highly correlated with that scored on the nasal flow/effort signals from the corresponding PSG studies on all patients, with a significant correlation coefficient of 0.98 (average absolute difference of 0.31 breaths/min), and 0.97 (p<;0.01, average absolute difference of 0.38 breaths/min) for the median and mean of RR respectively. Our experimental results also show that the difference between the RR estimations from IRR and RRC schemes can be utilized to identify central sleep apnea (CSA)/Cheyne-Stokes respiration (CSR) sections without additional apnea detection modules. As a result, with a sensitivity and specificity of 71% and 88% respectively, and an accuracy of 86%, our CSA/CSR screener, plugged with our RR estimation, can play an important role in the remote management of HF patients.

Facial deformations during nasal continuous positive airway pressure therapy.

Obstructive Sleep Apnoea (OSA), characterised by repeated collapse of the pharyngeal airway during sleep, causes cessation of breathing followed by arousal, restoring normality. Continuous Positive Airway Pressure (CPAP) is a non-invasive, effective treatment for OSA where positive pressure is applied to the airway through a mask, maintaining patency. Nasal masks are commonly used, contacting the face across the upper lip, sides of the nose and the nasal bridge. Despite health benefits, therapy compliance is sub-optimal, often due to poor mask fit and discomfort. Masks have been designed to conform to the facial profile, but have not taken into account facial deformations. The nature of facial deformations while undergoing CPAP therapy is unknown. This study investigates the facial deformations experienced by a patient while undergoing nasal CPAP therapy. Magnetic Resonance Imaging (MRI) scans of the face were acquired of participants in the reference configuration and while undergoing CPAP therapy. The CPAP scan volume was registered onto the reference volume prior to surface generation for each state. Perpendicular deformation was measured from the reference facial profile to the deformed profile. Large facial deformations were measured at the sides of the nose (4.6±1.6mm) and the upper lip (4.9±1.8mm) with much smaller deformations at the nasal bridge (2.4±0.2mm). When normalised by applied load and tissue thickness, no difference was found. These findings and techniques can be used to consider facial deformation in the development of future nasal CPAP masks to improve comfort and compliance to therapy.

Early Warning of Acute Decompensation in Heart Failure Patients Using a Noncontact Measure of Stability Index.

OBJECTIVE: Hospitalization due to heart failure (HF) continues to be a major clinical and economic challenge. To reduce hospitalization, this paper proposes a novel home telemonitoring system for an early warning of acute decompensation in patients with chronic stable New York Heart Association class II-IV HF. METHODS: It is based on deriving nocturnal respiratory related time series using a noncontact radio-wave bio-motion sensor. The system generates an alert when there is a change in the underlying probability distribution of the time series which can be regarded as a surrogate marker of patient stability. RESULTS: The system's performance is evaluated using dual-site longitudinal data collected from 104 HF patients over 12-24 months. The system reported an average sensitivity of 0.62 to detect a change during an episode of acute decompensation and an average specificity of 0.67 on the blind validation set, when the frequency of alert was four weeks. The system also performed well to predict acute decompensation with an average sensitivity of 0.55 and specificity of 0.73 on the validation set, where an event window was defined as three weeks preceding an event. CONCLUSION: These results demonstrate that the design and implementation of such a system is a positive step toward developing noncontact systems capable of preventing acute decompensation, reducing readmissions to hospital and ensuring better quality of life for HF patients.

Development and validation of a novel non-contact monitor of nocturnal respiration for identifying sleep-disordered breathing in patients with heart failure.

AIMS: At least 50% of patients with heart failure (HF) may have sleep-disordered breathing (SDB). Overnight in-hospital polysomnography (PSG) is considered the gold standard for diagnosis, but a lack of access to such testing contributes to under-diagnosis of SDB. Therefore, there is a need for simple and reliable validated methods to aid diagnosis in patients with HF. The aim of this study was to investigate the accuracy of a non-contact type IV screening device, SleepMinderTM (SM), compared with in-hospital PSG for detecting SDB in patients with HF. METHODS AND RESULTS: The study included 75 adult patients with systolic HF and suspected SDB who underwent simultaneous PSG and SM recordings. An algorithm was developed from the SM signals, using digital signal processing and pattern recognition techniques to calculate the SM apnoea-hypopnoea index (AHI). This was then compared with expert-scored PSGAHI . The SM algorithm had 70% sensitivity and 89% specificity for identifying patients with clinically significant SDB (AHI ≥ 15/h). At this threshold, it had a positive likelihood ratio of 6.3 and a negative likelihood ratio of 0.16. The overall accuracy of the SMAHI algorithm was 85.8% as shown by the area under a receiver operator characteristic curve. The mean AHI with SM was 3.8/h (95% confidence interval 0.5-7.1) lower than that with PSG. CONCLUSIONS: The accuracy of the non-contact type IV screening device SM is good for clinically significant SDB in patients with systolic HF and could be considered as a simple first step in the diagnostic pathway.

Online estimation of respiratory mechanics in non-invasive pressure support ventilation: a bench model study.

An online algorithm for determining respiratory mechanics in patients using non-invasive ventilation (NIV) in pressure support mode was developed and embedded in a ventilator system. Based on multiple linear regression (MLR) of respiratory data, the algorithm was tested on a patient bench model under conditions with and without leak and simulating a variety of mechanics. Bland-Altman analysis indicates reliable measures of compliance across the clinical range of interest (± 11-18% limits of agreement). Resistance measures showed large quantitative errors (30-50%), however, it was still possible to qualitatively distinguish between normal and obstructive resistances. This outcome provides clinically significant information for ventilator titration and patient management.

Automated detection of asynchrony in patient-ventilator interaction.

An automated classification algorithm for the detection of expiratory ineffective efforts in patient-ventilator interaction is developed and validated. Using this algorithm, 5624 breaths from 23 patients in a pulmonary ward were examined. The participants (N = 23) underwent both conventional and non-invasive ventilation. Tracings of patient flow, pressure at the airway, and transdiaphragmatic pressure were manually labeled by an expert. Overall accuracy of 94.5% was achieved with sensitivity 58.7% and specificity 98.7%. The results demonstrate the viability of using pattern classification techniques to automatically detect the presence of asynchrony between a patient and their ventilator.

Hematologic and biochemical effects of the Gradiflow in an ex vivo ovine model.

The Gradiflow (Life Therapeutics, Frenchs Forest, Australia) system is a novel electrophoretic technique that uses the dual characteristics of size and charge to separate target macromolecules from complex biological solutions. The system has the potential to selectively remove a range of moieties from blood and plasma in an in vivo system such as hemodialysis or, alternatively, in an in vitro setting such as a blood bank. In this study, the safety of a scaled down Gradiflow prototype device with a membrane surface area of 16 cm2 was investigated using an ex vivo ovine model. Physiologic, hematologic, and biochemical parameters were assessed in 12 sheep: 6 animals treated using the Gradiflow and 6 controls. The effects of the Gradiflow procedure on both whole blood and plasma were analyzed. The Gradiflow procedure was well tolerated, and the application of an electrical potential or exposure to the Gradiflow membrane did not cause any significant changes in the parameters measured. Hemoglobin levels remained stable in all groups during the 4-hour experiment. An early neutropenia was observed in all groups, although this appeared to be more pronounced with exposure to a plasma filter; the presence of the Gradiflow component had no separate influence. One sheep in the plasma group experienced septic shock, caused by Staphylococcus contamination of the separation membrane. Overall, the results indicate that there were no gross physiologic, hematologic, or biochemical adverse reactions to the ex vivo Gradiflow procedure.