Muscle fatigue degrades force sense at the ankle joint

To investigate the effects of muscle fatigue on force sense at the ankle joint, 10 young healthy adults were asked to perform an isometric contra-lateral force ankle-matching task in two experimental conditions of: (1) no-fatigue and (2) fatigue of the plantar-flexor muscles. Measures of the overall accuracy and the variability of the force matching performances were determined using the absolute error and the variable error, respectively. Results showed less accurate and less consistent force matching performances in the fatigue than no fatigue condition, as indicated by decreased absolute and variable errors, respectively. The present findings evidence that muscle fatigue degrades force sense at the ankle joint

Substrats neurophysiologiques des interactions patient- ventilateur et des sensations respiratoires correspondantes

Ventilatory support must be tailored to the load capacity balance of the respiratory system to avoid patient-ventilator dysharmony as it may lead to patient-ventilator asynchronies and dyspnea. Minimizing this dysharmony is crucial. Neurally Ventilatory Assist Ventilation (NAVA) and Proportional Assist Ventilation (PAV) modes may improve patient-ventilator interaction. We showed in this work that PAV and NAVA both prevents overdistension, restores breath by breath variability of the breathing pattern and improves neuromechanical coupling and patient- ventilator asynchrony in fairly similar ways compared to pressure support ventilation. In addition the use of NAVA with non-invasive ventilation may also improve patient-ventilator interaction. We also demonstrated that dyspnea is a frequent issue in mechanically ventilated ICU patients and it can be difficult to assess when the patient is unable to report it. Surface electromyograms of extradiaphragmatic inspiratory muscles provides a simple, reliable and non-invasive indicator of respiratory muscle loading/unloading in mechanically ventilated patients. Because this EMG activity is strongly correlated to the intensity of dyspnea, it could be used as a surrogate of respiratory sensations in mechanically ventilated patients, and might, therefore, provide a monitoring tool in patients in whom detection and quantification of dyspnea is complex if not impossible. These data provide a better understanding of patient-ventilator dysharmony. Further studies are needed to evaluate the possible clinical benefits of NAVA and PAV on clinical outcomes and the impact of an early detection of dyspnea in mechanical ventilation.En ventilation assistée, l’inadéquation entre l’activité des muscles respiratoires du patient et l’assistance délivrée par le ventilateur se traduit par la survenue d’une dysharmonie patient-ventilateur potentiellement associée avec la survenue d’asynchronies patient-ventilateur et d’une dyspnée. Minimiser cette dysharmonie est un objectif majeur de la ventilation assistée. Le Neuro Asservissement de la Ventilation Assistée (NAVA) et la Ventilation Assistée Proportionnelle (PAV) sont deux nouveaux modes qui pourraient améliorer l’harmonie patient-ventilateur. Nous avons montré que, de façon similaire, le NAVA et la PAV diminuent le nombre d’asynchronie patient-ventilateur, préviennent la surdistension pulmonaire, restaurent la variabilité cycle à cycle du comportement ventilatoire et améliorent l’équilibre charge-capacité et le couplage neuromécanique. De plus, l’utilisation du mode NAVA en ventilation non invasive pourrait également permettre d’améliorer la synchronisation patient-ventilateur. Nous avons également montré aux cours de différents travaux sur la dyspnée en ventilation mécanique que celle ci était fréquente mais néanmoins difficile à identifier, en particulier chez les patients non communicants. L’EMG de surface des muscles inspiratoires extra-diaphragmatiques pourrait constituer un outil simple et objectif pouvant permettre au clinicien de diagnostiquer une dyspnée en ventilation mécanique et optimiser les réglages du ventilateur dans le but de minimiser la dysharmonie patient-ventilateur. Ces données permettent de progresser vers une meilleure connaissance de la dysharmonie patient- ventilateur. L’impact clinique de l’utilisation des modes proportionnels et d’une détection précoce de la dyspnée doit maintenant être évalué par des essais cliniques

Optimal color channel combination across skin tones for remote heart rate measurement in camera-based photoplethysmography

Objective: The heart rate is an essential vital sign that can be measured remotely with camera-based photoplethysmography (cbPPG). Systems for cbPPG typically use cameras that deliver red, green, and blue (RGB) channels. The combination of these channels has been proven to increase signal-to-noise ratio (SNR) and heart rate measurement accuracy (ACC). However, many combinations remain untested, the comparison of proposed combinations on large datasets is insufficiently investigated, and the interplay with skin tone is rarely addressed. Methods: Eight regions of interest and eight color spaces with a total of 25 color channels were compared in terms of ACC and SNR based on the Binghamton-Pittsburgh-RPI Multimodal Spontaneous Emotion Database (BP4D+). Additionally, two systematic grid searches were performed to evaluate ACC in the space of linear combinations of the RGB channels. Results: Glabella and forehead regions of interest provided highest ACC (up to 74.1 %) and SNR (> -3 dB) with the hue channel H from HSV color space and the chrominance channel Q from NTSC color space. The grid searches revealed a global optimum of linear RGB combinations (ACC: 79.2 %). This optimum occurred for all skin tones, although ACC dropped for darker skin tones. Conclusion: Through systematic grid searches we were able to identify the skin tone independent optimal linear RGB color combination for measuring heart rate with cbPPG. Our results proved on a large dataset that the identified optimum outperformed conventionally used color channels. Significance: The presented findings provide useful evidence for future considerations of algorithmic approaches for cbPPG

Developing a Complex Independent Component Analysis (CICA) technique to extract non-stationary patterns from geophysical time series

In recent decades, decomposition techniques have enabled increasingly more applications for dimension reduction, as well as extraction of additional information from geophysical time series. Traditionally, the principal component analysis (PCA)/empirical orthogonal function (EOF) method and more recently the independent component analysis (ICA) have been applied to extract, statistical orthogonal (uncorrelated), and independent modes that represent the maximum variance of time series, respectively. PCA and ICA can be classified as stationary signal decomposition techniques since they are based on decomposing the autocovariance matrix and diagonalizing higher (than two) order statistical tensors from centered time series, respectively. However, the stationarity assumption in these techniques is not justified for many geophysical and climate variables even after removing cyclic components, e.g., the commonly removed dominant seasonal cycles. In this paper, we present a novel decomposition method, the complex independent component analysis (CICA), which can be applied to extract non-stationary (changing in space and time) patterns from geophysical time series. Here, CICA is derived as an extension of real-valued ICA, where (a) we first define a new complex dataset that contains the observed time series in its real part, and their Hilbert transformed series as its imaginary part, (b) an ICA algorithm based on diagonalization of fourth-order cumulants is then applied to decompose the new complex dataset in (a), and finally, (c) the dominant independent complex modes are extracted and used to represent the dominant space and time amplitudes and associated phase propagation patterns. The performance of CICA is examined by analyzing synthetic data constructed from multiple physically meaningful modes in a simulation framework, with known truth. Next, global terrestrial water storage (TWS) data from the Gravity Recovery And Climate Experiment (GRACE) gravimetry mission (2003–2016), and satellite radiometric sea surface temperature (SST) data (1982–2016) over the Atlantic and Pacific Oceans are used with the aim of demonstrating signal separations of the North Atlantic Oscillation (NAO) from the Atlantic Multi-decadal Oscillation (AMO), and the El Niño Southern Oscillation (ENSO) from the Pacific Decadal Oscillation (PDO). CICA results indicate that ENSO-related patterns can be extracted from the Gravity Recovery And Climate Experiment Terrestrial Water Storage (GRACE TWS) with an accuracy of 0.5–1 cm in terms of equivalent water height (EWH). The magnitude of errors in extracting NAO or AMO from SST data using the complex EOF (CEOF) approach reaches up to ~50% of the signal itself, while it is reduced to ~16% when applying CICA. Larger errors with magnitudes of ~100% and ~30% of the signal itself are found while separating ENSO from PDO using CEOF and CICA, respectively. We thus conclude that the CICA is more effective than CEOF in separating non-stationary patterns

Automatic Classification of Full- and Reduced-Lead Electrocardiograms Using Morphological Feature Extraction

Cardiovascular diseases are the global leading cause of death. Automated electrocardiogram (ECG) analysis can support clinicians to identify abnormal excitation of the heart and prevent premature cardiovascular death. An explainable classification is particularly important for support systems. Our contribution to the PhysioNet/CinC Challenge 2021 (team name: ibmtPeakyFinders) therefore pursues an approach that is based on interpretable features to be as explainable as possible. To meet the challenge goal of developing an algorithm that works for both 12-lead and reduced lead ECGs, we processed each lead separately. We focused on signal processing techniques based on template delineation that yield the template's fiducial points to take the ECG waveform morphology into account. In addition to beat intervals and amplitudes obtained from the template, various heart rate variability and QT interval variability features were extracted and supplemented by signal quality indices. Our classification approach utilized a decision tree ensemble in a one-vs-rest approach. The model parameters were determined using an extensive grid search. Our approach achieved challenge scores of 0.47, 0.47, 0.34, 0.40, and 0.41 on hidden 12-, 6-, 4-, 3-, and 2-lead test sets, respectively, which corresponds to the ranks 12, 10, 23, 18, and 16 out of 39 teams

Patients with hematologic malignancies have many reasons to die during extracorporeal membrane oxygenation

We read with great interest the article by Wohlfarth and colleagues regarding the use of extracorporeal membrane oxygenation (ECMO) in 14 adult patients with hematological malignancies. We would like to highlight two main points. First, the authors focused their report and their discussion on bleeding complications and anticoagulation management in this high-risk population. Although we concede that it is a serious concern in these patients, it is not the only one. ECMO support is associated with nosocomial infections. Impairment of cellular immunity, cytopenia and chemotherapy (CT) may further increase the risks of infection and may dissuade clinicians from using ECMO in these patients. Developing new strategies that aim to limit nosocomial infections is crucial to improving outcomes in this population. ECMO in awake, non-intubated, spontaneously breathing patients with acute respiratory distress syndrome, to avoid mechanical ventilation and its related adverse events, is a potentially promising application. Thus, in our opinion, it would also be important to provide a thorough description of nosocomial infections that might have occurred in these 14 patients. Second, the authors reported that 5 of 14 patients initially received CT while receiving ECMO. The pharmacokinetics of many of the medications administered to patients receiving ECMO are complex and, to date, there are very limited data to guide our daily practice. Therefore, clinicians must be aware that providing CT to patients receiving ECMO is a potential gamble, which risks worsening patient outcomes due to ineffective drug regimens. CT during ECMO should be restricted to those cases where postponing therapy is not an option

Ice mass change in Greenland and Antarctica between 1993 and 2013 from satellite gravity measurements

We construct long-term time series of Greenland and Antarctic ice sheet mass change from satellite gravity measurements. A statistical reconstruction approach is developed based on a Principal Component Analysis to combine high-resolution spatial modes from the Gravity Recovery and Climate Experiment (GRACE) mission with the gravity information from conventional satellite track-ing data. Uncertainties of this reconstruction are rigorously assessed; they include temporal limitations for short GRACE measurements, spatial limitations for the low-resolution conventional tracking data measurements, and limitations of the estimated statistical relationships between low and high degree potential coe�cients re ected in the PCA modes. Trends of mass variations in Greenland and Antarctica are assessed against a number of previous studies. The resulting time series for Greenland show a higher rate of mass loss than other methods before 2000, while the Antarctic ice sheet appears heavily in uenced by interannual variations

Camera-based assessment of cutaneous perfusion strength in a clinical setting

Objective. After skin flap transplants, perfusion strength monitoring is essential for the early detection of tissue perfusion disorders and thus to ensure the survival of skin flaps. Camera-based photoplethysmography (cbPPG) is a non-contact measurement method, using video cameras and ambient light, which provides spatially resolved information about tissue perfusion. It has not been researched yet whether the measurement depth of cbPPG, which is limited by the penetration depth of ambient light, is sufficient to reach pulsatile vessels and thus to measure the perfusion strength in regions that are relevant for skin flap transplants. Approach. We applied constant negative pressure (compared to ambient pressure) to the anterior thighs of 40 healthy subjects. Seven measurements (two before and five up to 90 min after the intervention) were acquired using an RGB video camera and photospectrometry simultaneously. We investigated the performance of different algorithmic approaches for perfusion strength assessment, including the signal-to-noise ratio (SNR), its logarithmic components logS and logN, amplitude maps, and the amplitude height of alternating and direct signal components. Main results. We found strong correlations of up to r = 0.694 (p < 0.001) between photospectrometric measurements and all cbPPG parameters except SNR when using the green color channel. The transfer of cbPPG signals to POS, CHROM, and O3C did not lead to systematic improvements. However, for direct signal components, the transformation to O3C led to correlations of up to r = 0.744 (p < 0.001) with photospectrometric measurements. Significance. Our results indicate that a camera-based perfusion strength assessment in tissue with deep-seated pulsatile vessels is possible