Wildhaber, Reto

Profilbild
E-Mail-Adresse
Geburtsdatum
Projekt
Organisationseinheiten
Berufsbeschreibung
Nachname
Wildhaber
Vorname
Reto
Name
Wildhaber, Reto

Filter

2011 - 2019122020 - 20236
Filter zurücksetzen

Einstellungen

Institut: Institut für Medizintechnik und Medizininformatik ×

Suchergebnisse

Gerade angezeigt 1 - 10 von 18
  • Vorschaubild nicht verfügbar
    Publikation
    Technical characterization of single-lead ECG signals from 4 different smartwatches and its potential clinical implications
    (Elsevier, 2023) Knecht, Sven; Waldmann, Frédéric; Kuhn, Raffael; Mannhart, Diego; Kühne, Michael; Sticherling, Christian; Badertscher, Patrick; Wildhaber, Reto [in: JACC: Clinical Electrophysiology]
    01A - Beitrag in wissenschaftlicher Zeitschrift
  • Vorschaubild nicht verfügbar
    Publikation
    Intracoronary ECG ST-segment shift remission time during reactive coronary hyperemia (tau-icECG): a new approach to assess hemodynamic coronary stenosis severity
    (Oxford University Press, 2023) Kieninger-Graefitsch, Andrea; Bigler, Marius Reto; Waldmann, Frédéric; Wildhaber, Reto; Seiler, Christian [in: European Heart Journal]
    Coronary pressure-derived fractional flow reserve (FFR) measurements are recommended for hemodynamic coronary stenosis assessment. Given temporary paralysis of the coronary microcirculation during hyperemia, pressure is, in theory, directly related to coronary flow. Pressure drop during hyperemia across a coronary stenosis, thus, provides an estimate of its restrictive effect on flow. FFR during reactive hyperemia induced by a proximal, 1-minute coronary artery balloon occlusion has been shown non-inferior to FFR as obtained by adenosine-induced hyperemia. Intracoronary ECG (icECG) is more sensitive in detecting myocardial ischemia than the surface ECG, and can be easily obtained.
    01A - Beitrag in wissenschaftlicher Zeitschrift
  • Vorschaubild
    Publikation
    Algorithm for real-time analysis of intracoronary electrocardiogram
    (Frontiers, 07.09.2022) Bigler, Marius Reto; Kieninger-Gräfitsch, Andrea; Waldmann, Frédéric; Seiler, Christian; Wildhaber, Reto [in: Frontiers in Cardiovascular Medicine]
    Since its first implementation in 1985, intracoronary (ic) electrocardiogram (ECG) has shown ample evidence for its diagnostic value given the higher sensitivity for myocardial ischemia detection in comparison to surface ECG. However, a lack of online systems to quantitatively analyze icECG in real-time prevents its routine use. The present study aimed to develop and validate an autonomous icECG analyzing algorithm.
    01A - Beitrag in wissenschaftlicher Zeitschrift
  • Vorschaubild
    Publikation
    Onset detection of pulse-shaped bioelectrical signals using linear state space models
    (De Gruyter, 02.09.2022) Waldmann, Frédéric; Baeriswyl, Christof; Andonie, Raphael; Wildhaber, Reto [in: Current Directions in Biomedical Engineering]
    Bioelectrical signals are often pulse-shaped with superimposed interference signals. In this context, accurate identification of features such as pulse onsets, peaks, amplitudes, and duration is a frequent problem. In this paper, we present a versatile method of rather low computational complexity to robustly identify such features in real-world signals. For that, we take use of two straight-line models fit to the observations by minimizing a quadratic cost term, and then identify desired features by tweaked likelihood measures. To demonstrate the idea and facilitate access to the method, we provide examples from the field of cardiology.
    01A - Beitrag in wissenschaftlicher Zeitschrift
  • Vorschaubild nicht verfügbar
    Publikation
    Windowed state space filters for peak interference suppression in neural spike sorting
    (IEEE, 2022) Wildhaber, Reto; Baeriswil, Christof; Bertrand, Alexander
    04B - Beitrag Konferenzschrift
  • Vorschaubild nicht verfügbar
    Publikation
    Signal analysis using local polynomial approximations
    (IEEE, 2020) Wildhaber, Reto; Ren, Elizabeth; Waldmann, Frederic; Loeliger, Hans-Andrea [in: 2020 28th European Signal Processing Conference (EUSIPCO)]
    Local polynomial approximations represent a versatile feature space for time-domain signal analysis. The parameters of such polynomial approximations can be computed by efficient recursions using autonomous linear state space models and often allow analytical solutions for quantities of interest. The approach is illustrated by practical examples including the estimation of the delay difference between two acoustic signals and template matching in electrocardiogram signals with local variations in amplitude and time scale.
    04B - Beitrag Konferenzschrift
  • Vorschaubild nicht verfügbar
    Publikation
    Toward a novel semi‐invasive activation mapping tool for the diagnosis of supraventricular arrhythmias from the esophagus
    (Wiley, 2019) Sweda, Romy; Wildhaber, Reto; Mortier, Simone; Bruegger, Dominik; Niederhauser, Thomas; Goette, Josef; Jacomet, Marcel; Tanner, Hildegard; Haeberlin, Andreas [in: Annals of Noninvasive Electrocardiology]
    Supraventricular arrhythmia diagnosis using the surface electrocardiogram (sECG) is often cumbersome due to limited atrial signal quality. In some instances, use of esophageal electrocardiography (eECG) may facilitate the diagnosis. Here, we present a novel approach to reconstruct cardiac activation maps from eECG recordings.
    01A - Beitrag in wissenschaftlicher Zeitschrift
  • Vorschaubild nicht verfügbar
    Publikation
    Estimation of the cardiac field in the esophagus using a multipolar esophageal catheter
    (IEEE, 2018) Wildhaber, Reto; Bruegger, Dominik; Zalmai, Nour; Malmberg, Hampus; Goette, Josef; Jacomet, Marcel; Tanner, Hildegard; Haeberlin, Andreas; Loeliger, Hans-Andrea [in: IEEE Transactions on Biomedical Circuits and Systems]
    The rapid progress of invasive therapeutic options for cardiac arrhythmias increases the need for accurate diagnostics. The surface electrocardiogram (ECG) is still the standard of noninvasive diagnostics but lacks atrial signal resolution. By contrast, esophageal electrocardiography (EECG) yields atrial signals of high amplitude and with a high signal-to-noise ratio. Esophageal electrocardiography has become fast and safe, but the mechanical constraints of esophageal measuring catheters and the “random” motion of the catheter inside the subject's esophagus limit the spatial resolution of EECG signals. In this paper, we propose a method to estimate the electrical field projected onto the esophagus with an increased spatial resolution, using commonly available esophageal catheters. In a first step, we estimate the time-varying catheter position, and in a second step, we estimate the projected electrical field with enhanced spatial resolution. The proposed algorithm comprises several consecutive optimization steps, where each intermediate step produces not just a single point estimate, but a cost function over multiple solutions, which reduces the information loss at each processing step. We conclude with examples from a clinical trial, where the fields of cardiac arrhythmias are presented as two-dimensional contour plots.
    01A - Beitrag in wissenschaftlicher Zeitschrift
  • Vorschaubild nicht verfügbar
    Publikation
    Windowed state-space filters for signal detection and separation
    (IEEE, 2018) Wildhaber, Reto; Zalmai, Nour; Jacomet, Marcel; Loeliger, Hans-Andrea [in: IEEE Transactions on Signal Processing]
    This paper introduces a toolbox for model-based detection, separation, and reconstruction of signals that is especially suited for biomedical signals, such as electrocardiograms (ECGs) or electromyograms (EMGs). The modeling is based on autonomous linear state space models (LSSMs), which are localized with flexible windows. The models are fit to observations by minimizing the squared error while the use of LSSMs leads to efficient recursive error computations and minimizations. Multisection windows enable complex models, and per-sample weights enable multistage processing or adaptive smoothing. This paper is motivated by, and intended for, practical applications, for which several examples and tabulated cost computations are given.
    01A - Beitrag in wissenschaftlicher Zeitschrift
  • Vorschaubild nicht verfügbar
    Publikation
    Signal detection and discrimination for medical devices using windowed state space filters
    (IEEE, 2017) Wildhaber, Reto; Zalmai, Nour; Jacomet, Marcel; Loeliger, Hans-Andrea [in: 2017 13th IASTED International Conference on Biomedical Engineering (BioMed)]
    We introduce a model-based approach for computationally efficient signal detection and discrimination, which is relevant for biological signals. Due to its low computational complexity and low memory need, this approach is well-suited for low power designs, as required for medical devices and implants. We use linear state space models to gain recursive, efficient computation rules and obtain the model parameters by minimizing the squared error on discrete-time observations. Furthermore we combine multiple models of different time-scales to match superpositions of signals of variable length. To give immediate access to our method, we highlight the use in several practical examples on standard and on esophageal ECG signals. This method was adapted and improved as part of a research and development project for medical devices.
    04B - Beitrag Konferenzschrift