| 1. |
- Isasi, Iraia, et al.
(författare)
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Restoration of the electrocardiogram during mechanical cardiopulmonary resuscitation
- 2020
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Ingår i: Physiological Measurement. - : IOP Publishing. - 0967-3334 .- 1361-6579. ; 41:10
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Tidskriftsartikel (refereegranskat)abstract
- Objective: An artefact-free electrocardiogram (ECG) is essential during cardiac arrest to decide therapy such as defibrillation. Mechanical cardiopulmonary resuscitation (CPR) devices cause movement artefacts that alter the ECG. This study analyzes the effectiveness of mechanical CPR artefact suppression filters to restore clinically relevant ECG information. Approach: In total, 495 10 s ECGs were used, of which 165 were in ventricular fibrillation (VF), 165 in organized rhythms (OR) and 165 contained mechanical CPR artefacts recorded during asystole. CPR artefacts and rhythms were mixed at controlled signal-to-noise ratios (SNRs), ranging from –20 dB to 10 dB. Mechanical artefacts were removed using least mean squares (LMS), recursive least squares (RLS) and Kalman filters. Performance was evaluated by comparing the clean and the restored ECGs in terms of restored SNR, correlation-based similarity measures, and clinically relevant features: QRS detection performance for OR, and dominant frequency, mean amplitude and waveform irregularity for VF. For each filter, a shock/no-shock support vector machine algorithm based on multiresolution analysis of the restored ECG was designed, and evaluated in terms of sensitivity (Se) and specificity (Sp). Main results: The RLS filter produced the largest correlation coefficient (0.80), the largest average increase in SNR (9.5 dB), and the best QRS detection performance. The LMS filter best restored VF with errors of 10.3% in dominant frequency, 18.1% in amplitude and 11.8% in waveform irregularity. The Se/Sp of the diagnosis of the restored ECG were 95.1/94.5% using the RLS filter and 97.0/91.4% using the LMS filter. Significance: Suitable filter configurations to restore ECG waveforms during mechanical CPR have been determined, allowing reliable clinical decisions without interrupting mechanical CPR therapy.
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| 2. |
- Mihandoost, Sara, et al.
(författare)
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A comparative study of the performance of methods for f-wave extraction
- 2022
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Ingår i: Physiological Measurement. - : IOP Publishing. - 0967-3334 .- 1361-6579. ; 43:10
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Tidskriftsartikel (refereegranskat)abstract
- Objective. This study proposes a novel technique for atrial fibrillatory waves (f-waves) extraction and investigates the performance of the proposed method comparing with different f-wave extraction methods. Approach. We propose a novel technique combining a periodic component analysis (PiCA) and echo state network (ESN) for f-waves extraction, denoted PiCA-ESN. PiCA-ESN benefits from the advantages of using both source separation and nonlinear adaptive filtering. PiCA-ESN is evaluated by comparing with other state-of-the-art approaches, which include template subtraction technique based on principal component analysis, spatiotemporal cancellation, nonlinear adaptive filtering using an echo state neural network, and a source separation technique based on PiCA. Quality assessment is performed on a recently published reference database including a large number of simulated ECG signals in atrial fibrillation (AF). The performance of the f-wave extraction methods is evaluated in terms of signal quality metrics (SNR, ΔSNR) and robustness of f-wave features. Main results. The proposed method offers the best signal quality performance, with a ΔSNR of approximately 22 dB across all 8 sets of the reference database, as well as the most robust extraction of f-wave features, with 75% of all estimates of dominant atrial frequency well below 1 Hz.
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| 3. |
- Rosengren, William, et al.
(författare)
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Waveform characterisation and comparison of nystagmus eye-tracking signals
- 2021
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Ingår i: Physiological Measurement. - : IOP Publishing. - 0967-3334 .- 1361-6579. ; 42:1
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Tidskriftsartikel (refereegranskat)abstract
- Pathological nystagmus is a symptom of oculomotor disease where the eyes oscillate involuntarily. The underlying cause of the nystagmus and the characteristics of the oscillatory eye movements are patient specific. An important part of clinical assessment in nystagmus patients is therefore to characterise different recorded eye-tracking signals, i.e. waveforms. Approach. A method for characterisation of the nystagmus waveform morphology is proposed. The method extracts local morphologic characteristics based on a sinusoidal model, and clusters these into a description of the complete signal. The clusters are used to characterise and compare recordings within and between patients and tasks. New metrics are proposed that can measure waveform similarity at different scales; from short signal segments up to entire signals, both within and between patients. Main results. The results show that the proposed method robustly can find the most prominent nystagmus waveforms in a recording. The method accurately identifies different eye movement patterns within and between patients and across different tasks. Significance. In conclusion, by allowing characterisation and comparison of nystagmus waveform patterns, the proposed method opens up for investigation and identification of the underlying condition in the individual patient, and for quantifying eye movements during tasks.
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| 4. |
- Saiz-Vivo, Javier, et al.
(författare)
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Heart rate characteristic based modelling of atrial fibrillatory rate using implanted cardiac monitor data
- 2023
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Ingår i: Physiological Measurement. - : IOP Publishing. - 0967-3334 .- 1361-6579. ; 44:3
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Tidskriftsartikel (refereegranskat)abstract
- OBJECTIVE: The objective of the present study is to investigate the feasibility of using heart rate characteristics to estimate atrial fibrillatory rate (AFR) in a cohort of atrial fibrillation (AF) patients continuously monitored with an implantable cardiac monitor (ICM). We will use a mixed model approach to investigate population effect and patient specific effects of heart rate characteristics on AFR, and will correct for the effect of previous ablations, episode duration, and onset date and time.APPROACH: The f-wave signals, from which AFR is estimated, were extracted using a QRST cancellation process of the AF episodes in a cohort of 99 patients (67% male; 57±12 years) monitored for 9.2(0.2-24.3) months as median(min-max). The AFR from 2453 f-wave signals included in the analysis was estimated using a model-based approach. The association between AFR and heart rate characteristics, prior ablations, and episode-related features were modelled using fixed-effect and mixed-effect modelling approaches.MAIN RESULTS: The mixed-effect models had a better fit to the data than fixed-effect models showing higher coefficients of determination (R2=0.49 vs R2=0.04) when relating the variations of AFR to the heart rate features. However, when correcting for the other factors, the mixed-effect model showed the best fit (R2=0.56). AFR was found to be significantly affected by previous catheter ablations (p<0.05), episode duration (p<0.05), and irregularity of the RR interval series (p<0.05).SIGNIFICANCE: Mixed-effect models are more suitable for AFR modelling. AFR was shown to be faster in episodes with longer duration, less organized RR intervals and after several ablation procedures.
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| 5. |
- Bäcklund, Tomas, et al.
(författare)
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Novel, clinically applicable method to measure step-width during the swing phase of gait
- 2020
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Ingår i: Physiological Measurement. - : Institute of Physics Publishing (IOPP). - 0967-3334 .- 1361-6579. ; 41:6
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Tidskriftsartikel (refereegranskat)abstract
- Objective: Step-width during walking is an indicator of stability and balance in patients with neurological disorders, and development of objective tools to measure this clinically would be a great advantage. The aim of this study was to validate an in-house-developed gait analysis system (Striton), based on optical and inertial sensors and a novel method for stride detection, for measuring step-width during the swing phase of gait and temporal parameters.Approach: The step-width and stride-time measurements were validated in an experimental setup, against a 3D motion capture system and on an instrumented walkway. Further, test-retest and day-to-day variability were evaluated, and gait parameters were collected from 87 elderly persons (EP) and four individuals with idiopathic normal pressure hydrocephalus (iNPH) before/after surgery.Main results: Accuracy of the step-width measurement was high: in the experimental setup mean error was 0.08 +/- 0.25 cm (R = 1.00) and against the 3D motion capture system 0.04 +/- 1.12 cm (R = 0.98). Test-retest and day-to-day measurements were equal within +/- 0.5 cm. Mean difference in stride time was -0.003 +/- 0.008 s between Striton and the instrumented walkway. The Striton system was successfully applied in the clinical setting on individuals with iNPH, which had larger step-width (6.88 cm, n = 4) compared to EP (5.22 cm, n = 87).Significance: We conclude that Striton is a valid, reliable and wearable system for quantitative assessment of step-width and temporal parameters during gait. Initial measurements indicate that the newly defined step-width parameter differs between EP and patients with iNPH and before/after surgery. Thus, there is potential for clinical applicability in patients with reduced gait stability.
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| 6. |
- Bäcklund, Tomas, 1958-, et al.
(författare)
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Single sensor measurement of heel-height during the push-off phase of gait
- 2021
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Ingår i: Physiological Measurement. - : Institute of Physics (IOP). - 0967-3334 .- 1361-6579. ; 42:10
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Tidskriftsartikel (refereegranskat)abstract
- Objective: In healthy gait a forceful push-off is needed to get an efficient leg swing and propulsion, and a high heel lift makes a forceful push-off possible. The power of the push-off is decreased with increased age and in persons with impaired balance and gait. The aim of this study was to evaluate whether a wearable equipment (Striton) and algorithms to estimate vertical heel-height during gait from a single optical distance sensor is reliable and feasible for clinical applications.Approach: To assess heel-height with the Striton system an optical distance sensor was used to measure the distance to the floor along the shank. An algorithm was created to transform this measure to a vertical distance. The heel-height was validated in an experimental setup, against a 3D motion capture system (MCS), and test-retest and day-to-day tests were performed on 10 elderly persons. As a reference material 83 elderly persons were included, and heel-height was measured before and after surgery in four patients with the neurological disorder idiopathic normal pressure hydrocephalus (iNPH).Main results: In the experimental setup the accuracy was high with a maximum error of 2% at all distances, target colours and inclination angles, and the correlation to the MCS was R = 0.94. Test-retest and day-to-day tests were equal within ±1.2 cm. Mean heel-height of the elderly persons was 16.5 ± 0.6 cm and in the patients with iNPH heel-height was increased from 11.2 cm at baseline to 15.3 cm after surgery.Significance: Striton can reliably measure heel-height during gait, with low test-retest and day-to-day variability. The system was easy to attach, and simple to use, which makes it suitable for clinical applications.
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| 7. |
- Grivans, C., et al.
(författare)
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Gas distribution by EIT during PEEP inflation: PEEP response and optimal PEEP with lowest trans-pulmonary driving pressure can be determined without esophageal pressure during a rapid PEEP trial in patients with acute respiratory failure
- 2022
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Ingår i: Physiological Measurement. - : IOP Publishing. - 0967-3334 .- 1361-6579. ; 43:11
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Tidskriftsartikel (refereegranskat)abstract
- Objective. Protective ventilation should be based on lung mechanics and transpulmonary driving pressure (Delta PTP), as this 'hits' the lung directly. Approach. The change in end-expiratory lung volume (Delta EELV) is determined by the size of the PEEP step and the elastic properties of the lung (EL), Delta EELV/Delta PEEP. Consequently, EL can be determined as Delta PEEP/Delta EELV. By calibration of tidal inspiratory impedance change with ventilator inspiratory tidal volume, end-expiratory lung impedance changes were converted to volume changes and lung P/V curves were obtained during a PEEP trial in ten patients with acute respiratory failure. The PEEP level where Delta PTP was lowest (optimal PEEP) was determined as the steepest point of the lung P/V curve. Main results. Over-all EL ranged between 7.0-23.2 cmH(2)O/L. Optimal PEEP was 12.9 cmH(2)O (10-16) with Delta PTP of 4.1 cmH(2)O (2.8-7.6). Patients with highest EL were PEEP non-responders, where EL increased in non-dependent and dependent lung at high PEEP, indicating over-distension in all lung. Patients with lower EL were PEEP responders with decreasing EL in dependent lung when increasing PEEP. Significance. PEEP non-responders could be identified by regional lung P/V curves derived from ventilator calibrated EIT. Optimal PEEP could be determined from the equation for the lung P/V curve.
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| 8. |
- Hentze, Benjamin, et al.
(författare)
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A model-based source separation algorithm for lung perfusion imaging using electrical impedance tomography
- 2021
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Ingår i: Physiological Measurement. - : Institute of Physics Publishing (IOPP). - 0967-3334 .- 1361-6579. ; 42:8
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Tidskriftsartikel (refereegranskat)abstract
- Objective. Electrical impedance tomography (EIT) for lung perfusion imaging is attracting considerable interest in intensive care, as it might open up entirely new ways to adjust ventilation therapy. A promising technique is bolus injection of a conductive indicator to the central venous catheter, which yields the indicator-based signal (IBS). Lung perfusion images are then typically obtained from the IBS using the maximum slope technique. However, the low spatial resolution of EIT results in a partial volume effect (PVE), which requires further processing to avoid regional bias. Approach. In this work, we repose the extraction of lung perfusion images from the IBS as a source separation problem to account for the PVE. We then propose a model-based algorithm, called gamma decomposition (GD), to derive an efficient solution. The GD algorithm uses a signal model to transform the IBS into a parameter space where the source signals of heart and lung are separable by clustering in space and time. Subsequently, it reconstructs lung model signals from which lung perfusion images are unambiguously extracted. Main results. We evaluate the GD algorithm on EIT data of a prospective animal trial with eight pigs. The results show that it enables lung perfusion imaging using EIT at different stages of regional impairment. Furthermore, parameters of the source signals seem to represent physiological properties of the cardio-pulmonary system. Significance. This work represents an important advance in IBS processing that will likely reduce bias of EIT perfusion images and thus eventually enable imaging of regional ventilation/perfusion (V/Q) ratio.
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| 9. |
- Hultman, Martin, et al.
(författare)
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Driver sleepiness detection with deep neural networks using electrophysiological data
- 2021
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Ingår i: Physiological Measurement. - : IOP PUBLISHING LTD. - 0967-3334 .- 1361-6579. ; 42:3
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Tidskriftsartikel (refereegranskat)abstract
- Objective. The objective of this paper is to present a driver sleepiness detection model based on electrophysiological data and a neural network consisting of convolutional neural networks and a long short-term memory architecture. Approach. The model was developed and evaluated on data from 12 different experiments with 269 drivers and 1187 driving sessions during daytime (low sleepiness condition) and night-time (high sleepiness condition), collected during naturalistic driving conditions on real roads in Sweden or in an advanced moving-base driving simulator. Electrooculographic and electroencephalographic time series data, split up in 16 634 2.5 min data segments was used as input to the deep neural network. This probably constitutes the largest labeled driver sleepiness dataset in the world. The model outputs a binary decision as alert (defined as <= 6 on the Karolinska Sleepiness Scale, KSS) or sleepy (KSS >= 8) or a regression output corresponding to KSS epsilon [1-5, 6, 7, 8, 9]. Main results. The subject-independent mean absolute error (MAE) was 0.78. Binary classification accuracy for the regression model was 82.6% as compared to 82.0% for a model that was trained specifically for the binary classification task. Data from the eyes were more informative than data from the brain. A combined input improved performance for some models, but the gain was very limited. Significance. Improved classification results were achieved with the regression model compared to the classification model. This suggests that the implicit order of the KSS ratings, i.e. the progression from alert to sleepy, provides important information for robust modelling of driver sleepiness, and that class labels should not simply be aggregated into an alert and a sleepy class. Furthermore, the model consistently showed better results than a model trained on manually extracted features based on expert knowledge, indicating that the model can detect sleepiness that is not covered by traditional algorithms.
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| 10. |
- Tran, Minh Cong, et al.
(författare)
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Lung heterogeneity and deadspace volume in acute respiratory distress syndrome animals using the inspired sinewave test
- 2020
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Ingår i: Physiological Measurement. - : IOP Publishing. - 0967-3334 .- 1361-6579. ; 41:11
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Tidskriftsartikel (refereegranskat)abstract
- The acute respiratory distress syndrome is associated with a high rate of morbidity and mortality, as patients undergoing mechanical ventilation are at risk of ventilator-induced lung injuries.OBJECTIVE: To measure the lung heterogeneity and deadspace volume to find safer ventilator strategies. Then, the ventilator settings could offer homogeneous ventilation and theoretically equalise and reduce tidal strain/stress in the lung parenchyma.APPROACH: The Inspired Sinewave Test (IST) is a non-invasive lung measurement tool, which does not require patients' cooperation. The IST can measure the effective lung volume, pulmonary blood flow and deadspace volume. We developed a computational simulation of the cardiopulmonary system to allow lung heterogeneity to be quantified using data solely derived from the IST. Then, the method to quantify lung heterogeneity using two IST tracer gas frequencies (180s and 60s) was introduced and experimented in the simulation lungs and in animal models. Thirteen anaesthetised pigs were studied with the IST, both before and after experimental lung injury (saline-lavage ARDS model). The deadspace volume is compared between IST and the SF_{6} Washout method.RESULTS: The IST could measure the lung heterogeneity using two frequencies tracer gases. Furthermore, the value of IST ventilation heterogeneity in ARDS lungs were higher than in control lungs at PEEP 10cmH_{2}O (AuC=0.85, p<0.001). Deadspace volume values measured by the IST has a strong relationship with the measured values of the SF_{6} (9mL bias and limits of agreement from -79mL to 57mL in control animals).SIGNIFICANCE: the potential impact of the IST technique in the identification of ventilation and perfusion heterogeneity during ventilator support.
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