Physiological measurement
-
Physiological measurement · Aug 2016
A practical algorithm to reduce false critical ECG alarms using arterial blood pressure and/or photoplethysmogram waveforms.
There has been a high rate of false alarms for the critical electrocardiogram (ECG) arrhythmia events in intensive care units (ICUs), from which the 'crying-wolf' syndrome may be resulted and patient safety may be jeopardized. This article presents an algorithm to reduce false critical arrhythmia alarms using arterial blood pressure (ABP) and/or photoplethysmogram (PPG) waveform features. We established long duration reference alarm datasets which consist of 573 ICU waveform-alarm records (283 for development set and 290 for test set) with total length of 551 patent days. ⋯ At the time of a critical ECG alarm, the corresponding EFI values of those ABP/PPG pulses around the alarm time are checked for adjudicating (accept/reject) this alarm. The algorithm retains all (100%) the true alarms and significantly reduces the false alarms. Our results suggest that the algorithm is effective and practical on account of its real-time dynamic processing mechanism and computational efficiency.
-
Physiological measurement · Aug 2016
Detection of false arrhythmia alarms with emphasis on ventricular tachycardia.
Our approach to detecting false arrhythmia alarms in the intensive care unit breaks down into several tasks. It involves beat detection on different signals: electrocardiogram, photoplethysmogram and arterial blood pressure. The quality of each channel has to be estimated in order to evaluate the reliability of obtained beat detections. ⋯ This feature was important in order to reduce misclassification of ventricular beats: there was an improvement in the ventricular tachycardia alarm true positive rate from 69% to 81%. However, the true negative rate was reduced from 95% to 69% and our global challenge score (real-time event) dropped from 79.02 to 74.28. Our challenge algorithm achieved the third best score in the 2015 PhysioNet/CinC challenge event 1 (real time).
-
Physiological measurement · Aug 2016
Real-time arrhythmia detection with supplementary ECG quality and pulse wave monitoring for the reduction of false alarms in ICUs.
False intensive care unit (ICU) alarms induce stress in both patients and clinical staff and decrease the quality of care, thus significantly increasing both the hospital recovery time and rehospitalization rates. In the PhysioNet/CinC Challenge 2015 for reducing false arrhythmia alarms in ICU bedside monitor data, this paper validates the application of a real-time arrhythmia detection library (ADLib, Schiller AG) for the robust detection of five types of life-threatening arrhythmia alarms. The strength of the application is to give immediate feedback on the arrhythmia event within a scan interval of 3 s-7.5 s, and to increase the noise immunity of electrocardiogram (ECG) arrhythmia analysis by fusing its decision with supplementary ECG quality interpretation and real-time pulse wave monitoring (quality and hemodynamics) using arterial blood pressure or photoplethysmographic signals. ⋯ The performance (true positive rate, true negative rate) is reported in the blinded challenge test set for different arrhythmias: asystole (83%, 96%), extreme bradycardia (100%, 90%), extreme tachycardia (98%, 80%), ventricular tachycardia (84%, 82%), and ventricular fibrillation (78%, 84%). Another part of this study considers the validation of ADLib with four reference ECG databases (AHA, EDB, SVDB, MIT-BIH) according to the international recommendations for performance reports in ECG monitors (ANSI/AAMI EC57). The sensitivity (Se) and positive predictivity (+P) are: QRS detector QRS (Se, +P) > 99.7%, ventricular ectopic beat (VEB) classifier VEB (Se, +P) = 95%, and ventricular fibrillation detector VFIB (P + = 94.8%) > VFIB (Se = 86.4%), adjusted to the clinical setting requirements, giving preference to low false positive alarms.
-
Physiological measurement · Jun 2016
Regional lung function determined by electrical impedance tomography during bronchodilator reversibility testing in patients with asthma.
The measurement of rapid regional lung volume changes by electrical impedance tomography (EIT) could determine regional lung function in patients with obstructive lung diseases during pulmonary function testing (PFT). EIT examinations carried out before and after bronchodilator reversibility testing could detect the presence of spatial and temporal ventilation heterogeneities and analyse their changes in response to inhaled bronchodilator on the regional level. We examined seven patients suffering from chronic asthma (49 ± 19 years, mean age ± SD) using EIT at a scan rate of 33 images s(-1) during tidal breathing and PFT with forced full expiration. ⋯ Spatial and temporal ventilation distribution improved in the patients with asthma after the bronchodilator administration as evidenced mainly by the histograms of pixel FEV1/FVC values and pixel expiration times. The examination of regional lung function using EIT enables the assessment of spatial and temporal heterogeneity of ventilation distribution during bronchodilator reversibility testing. EIT may become a new tool in PFT, allowing the estimation of the natural disease progression and therapy effects on the regional and not only global level.
-
Physiological measurement · Apr 2016
Pattern discovery in critical alarms originating from neonates under intensive care.
Patient monitoring generates a large number of alarms, the vast majority of which are false. Excessive non-actionable medical alarms lead to alarm fatigue, a well-recognized patient safety issue. While multiple approaches to reduce alarm fatigue have been explored, patterns in alarming and inter-alarm relationships, as they manifest in the clinical workspace, are largely a black-box and hamper research efforts towards reducing alarms. ⋯ Examination of the prevalent alarm sequences reveals that while many sequences comprised of multiple alarms, nearly 65% of the sequences were isolated instances of alarms and are potentially irreducible. Patterns in alarming, as they manifest in the clinical workspace were identified and visualized. This information can be exploited to investigate strategies for reducing alarms.