Sebastian Zaunseder

University of Augbsurg · Professorship for Diagnostic Sensing

Im Auftrag des Bundesministeriums für Wirtschaft und Klimaschutz haben DIN und DKE im Januar 2022 die Arbeiten an der zweiten Ausgabe der Deutschen Normungsroadmap Künstliche Intelligenz gestartet. In einem breiten Beteiligungsprozess und unter Mitwirkung von mehr als 570 Fachleuten aus Wirtschaft, Wissenschaft, öffentlicher Hand und Zivilgesellsch...

Blood pressure (BP) is among the most important vital signals. Estimation of absolute BP solely using photoplethysmography (PPG) has gained immense attention over the last years. Available works differ in terms of used features as well as classifiers and bear large differences in their results. This work aims to provide a machine learning method fo...

Compensated shock and hypovolaemia are frequent conditions that remain clinically undetected and can quickly cause deterioration of perioperative and critically ill patients. Automated, accurate and non-invasive detection methods are needed to avoid such critical situations. In this experimental study, we aimed to create a prediction model for stro...

Photoplethysmographic Imaging (PPGI) allows the determination of pulse rate variability from sequential beat-to-beat intervals (BBI) and pulse wave velocity from spatially resolved recorded pulse waves. In either case, sufficient temporal accuracy is essential. The presented work investigates the temporal accuracy of BBI estimation from photoplethy...

Photoplethysmographic Imaging (PPGI) allows the determination of pulse rate variability from sequential beat-to-beat intervals (BBI) and pulse wave velocity from spatially resolved recorded pulse waves. In either case, sufficient temporal accuracy is essential. The presented work investigates the temporal accuracy of BBI estimation from photoplethy...

Objective In this contribution, we present an automated sleep stage classifier using modern machine learning methods with cardiorespiratory time series as input signals. We investigate (1) which classification quality we can yield, (2) how variations in the input data affect the results and (3) to which extend the proposed classifier model can serv...

Most of the work related to imaging photoplethysmography (iPPG) has its focus on methodological developments. To date, only few investigations addressed clinical applications. This chapter reviews the clinical usability of the iPPG. We present a number of potential applications together with their clinical background and relevant works. Covered app...

Push-broom HSI-cameras have a high spectral resolution but require scanning and stitching to get a correct spatial and spectral representation of a scene. The conventional approach is to calculate a scanning velocity that matches the camera’s frame rate so that the stitching becomes trivial. For this to work one needs to be able to apply the veloci...

Data-based clinical decision support systems (CDSSs) can provide personalized support in medical applications. Such systems are expected to play an increasingly important role in the future of healthcare. Within this work, we demonstrate an exemplary CDSS which provides individualized pharmaceutical drug recommendations to physicians and patients....

Arterial blood pressure is one of the most often measured vital parameters in clinical practice. State-of-the-art noninvasive ABP measurement technologies have noticeable limitations and are mainly based on uncomfortable techniques of complete or partial arterial occlusion by cuffs. Most commonplace devices provide only intermittent measurements, a...

This paper presents an approach for pulse rate extraction from videos. The core of the presented approach is a novel method to segment and track a suitable region of interest (ROI). The proposed method combines level sets with subject-individual Gaussian Mixture Models to yield a time varying ROI. The ROI builds up from multiple homogeneous skin ar...

Remote imaging photoplethysmography (iPPG) senses the cardiac pulse in outer skin layers and is responsive to mean arterial pressure and pulse pressure in critically ill patients. Whether iPPG is sufficiently sensitive to monitor cutaneous perfusion is not known. This study aimed at determining the response of iPPG to changes in cutaneous perfusion...

Coronavirus disease (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is rapidly spreading across the globe. The clinical spectrum of SARS-CoV-2 pneumonia requires early detection and monitoring, within a clinical environment for critical cases and remotely for mild cases, with a large spectrum of symptoms. The...

Imaging photoplethysmography (iPPG) is a contact-free monitoring of the cutaneous blood volume pulse by RGB (red-green-blue) cameras. It detects vital parameters from skin areas and is associated to cutaneous perfusion. This study investigated the use of iPPG to quantify changes in cutaneous perfusion after major surgery. Patients undergoing corona...

This work aims to classify sleep stages based on tachograms using Convolutional Neural Networks (CNNs) and investigate advantages of specialized classifiers over general classifiers. The tachograms of 5422 patients were extracted from the Sleep Heart Health Study. A CNN was trained to classify each 30 s epoch into four distinct sleep stages. The pa...

Photplethysmography (PPG) is known to reflect changes in sympathetic tone. This contribution investigates the behaviour of imaging photoplethysmography (iPPG) upon sympathetic activation. To that end, we assessed the impact of a distal painful stimulus on the facial iPPG and con-tralateral finger PPG waveforms. Our results show that alternating com...

Objective: Photoplethysmography imaging (PPGI) has gained immense attention over the last few years but only a few works have addressed morphological analysis so far. Pulse wave decomposition (PWD), i.e. the decomposition of a pulse wave by a varying number of kernels, allows for such analyses. This work investigates the applicability of PWD algor...

Coronavirus disease (COVID-19) is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that is rapidly spreading across the globe. The clinical spectrum of SARS-CoV-2 pneumonia ranges from mild to critically ill cases and requires early detection and monitoring, within a clinical environment for critical cases and remotely for...

This work targets the development of a neighborhood-based Collaborative Filtering therapy recommender system for clinical decision support. The proposed algorithm estimates outcome of pharmaceutical therapy options in order to derive recommendations. Two approaches, namely a Relief-based algorithm and a metric learning approach are investigated. Bo...

Imaging photoplethysmography allows to capture spatio-temporal patterns related to the perfusion. One such approach is based on the analysis of the time delay between pulse waves at different locations by so-called phase maps. There are different ways to establish such maps. However, neither a comparison between existing methods has been published...

Objective: Predicting sepsis onset with a recurrent neural network and performance comparison with InSight - a previously proposed algorithm for the prediction of sepsis onset. Methodology: A retrospective analysis of adult patients admitted to the intensive care unit (from the MIMIC III database) who did not fall under the definition of sepsis...

In this work we developed a simple distance metric which uses only one channel to detect fQRS morphology changes introduced by fetal movement.

Imaging photoplethysmography (iPPG) is an interesting alternative to laser speckle contrast imaging for the analysis of spatio-temporal patterns in the cutaneous microcirculation. Recent years have witnessed the development of sophisticated techniques for the non-invasive extraction of vascular-related features. These techniques, referred to as pul...

The objective of the present study was to quantify repolarization lability and its association with sex, sleep stage, and cardiovascular mortality. We analyzed polysomnographic recordings of 2,263 participants enrolled in the Sleep Heart Health Study (SHHS-2). Beat-to-beat QT interval variability (QTV) was quantified for consecutive epochs of 5 min...

Purpose: Camera-based photoplethysmography (cbPPG) remotely detects the volume pulse of cardiac ejection in the peripheral circulation. The cbPPG signal is sourced from the cutaneous microcirculation, yields a two-dimensional intensity map and is therefore an interesting monitoring technique. In this study we investigated, whether cbPPG is in gene...

We study the impact of prior knowledge about invariance for the task of heart rate estimation from face videos in the wild (e.g. in presence of disturbing factors like rigid head motion, talking, facial expressions and natural illumination conditions under different scenarios). We introduce features invariant with respect to the action of a differe...

Over the last few years, the contactless acquisition of cardiovascular parameters using cameras has gained immense attention. The technique provides an optical means to acquire cardiovascular information in a very convenient way. This review provides an overview on the technique’s background and current realizations. Besides giving detailed informa...

The assessment of subtle morphological changes in noisy signals is a common challenge in the field of biomedical signal processing. Concerning the electrocardiogram (ECG), it may yield novel risk factors for cardiac mortality. Here, we describe an iterative two-dimensional signal warping algorithm (i2DSW), which morphological analyses even in case...

Online review sites and opinion forums contain a wealth of information regarding user preferences and experiences over multiple product domains. This information can be leveraged to obtain valuable insights using data mining approaches such as sentiment analysis. In this work we examine online user reviews within the pharmaceutical field. Online us...

Background: Camera-based photoplethysmography (cbPPG) is a measurement technique which enables remote vital sign monitoring by using cameras. To obtain valid plethysmograms, proper regions of interest (ROIs) have to be selected in the video data. Most automated selection methods rely on specific spatial or temporal features limiting a broader appl...

Imaging photoplethysmography (iPPG) has attracted much attention over the last years. The vast majority of works focuses on methods to reliably extract the heart rate from videos. Only a few works addressed iPPG’s ability to exploit spatio-temporal perfusion pattern to derive further diagnostic statements. This work directs at the spatio-temporal...

Objective: Novel minimum-contact vital signs monitoring techniques like textile or capacitive electrocardiogram (ECG) provide new opportunities for health monitoring. These techniques are sensitive to artifacts and require handling of unstable signal quality. Spatio-temporal Blind Source Separation (BSS) is capable of processing suchlike multichan...

Telemedicine focuses on improving the quality of health care, particularly in out-of-hospital settings. One of the most important applications is the continuous remote monitoring of vital parameters. Long-term monitoring of biopotentials requires skin-electrodes. State-of-the-art electrodes such as Ag/AgCl wet electrodes lead, especially during lon...

The role of physiological signals has a large impact on driver monitoring systems, since it tells something about the human state. This work addresses the recursive probabilistic inference problem in time-varying linear dynamic systems to incorporate invariance into the task of heart rate estimation from face videos under realistic conditions. The...

Camera-based photoplethysmography (cbPPG) is an innovative measuring technique that enables the remote extraction of vital signs using video cameras. Most studies in the field focus on heart rate detection while other physiological quantities are often ignored. In this work, we analyzed the relation between the pulse pressure and the pulsation stre...

Camera-based photoplethysmography (cbPPG) is a novel measuring technique that permits the remote acquisition of cardiovascular signals using video cameras. Research still lacks in fundamental studies to reach a deeper technical and physiological understanding. This work analyzes the employment of polarization filtration to (i) assess the gain for t...

Over the past years, various systems and techniques enabling unobtrusive/minimally obtrusive acquisition of physiological signals have evolved. These systems and techniques open up novel opportunities for sleep medicine. This work provides an overview of unobtrusive systems and techniques to monitor cardiorespiratory function. We present basic prin...

We present a system for data-driven therapy decision support based on techniques from the field of recommender systems. Two methods for therapy recommendation, namely, Collaborative Recommender and Demographic-based Recommender , are proposed. Both algorithms aim to predict the individual response to different therapy options using diverse patient...

Blind source separation (BSS) aims at separating useful signal content from distortions. In the contactless acquisition of vital signs by means of the camera-based photoplethysmogram (cbPPG), BSS has evolved the most widely used approach to extract the cardiac pulse. Despite its frequent application, there is no consensus about the optimal usage of...

Camera-Based Photoplethysmography is a measuring technique that permits the remote assessment of vital signs by using cameras. The face is the preferred area of measurement (region of interest: ROI) that has to be selected automatically for convenient application. Most works use common face detection algorithm for this purpose. However, these appro...

Objective: The noninvasive fetal ECG (NI-FECG) from abdominal recordings offers novel prospects for prenatal monitoring. However, NI-FECG signals are corrupted by various nonstationary noise sources, making the processing of abdominal recordings a challenging task. In this paper, we present an online approach that dynamically assess the quality of...

Monitoring the fetal behavior does not only have implications for acute care but also for identifying developmental disturbances that burden the entire later life. The concept, of "fetal programming", also known as "developmental origins of adult disease hypothesis", e.g. applies for cardiovascular, metabolic, hyperkinetic, cognitive disorders. Sin...

Camera-based photoplethysmography (cbPPG) is a novel technique that allows the contactless acquisition of cardio-respiratory signals. Previous works on cbPPG most often focused on heart rate extraction. This contribution is directed at the assessment of vasomotor activity by means of cameras. In an experimental study, we show that vasodilation and...

In this paper two approaches for facilitating therapy decision support are proposed and compared. Both approaches, the Collaborative Recommender and hybrid Demographic-based Recommender, are based on recommender system methods which origin from the field of product recommendation in e-commerce applications. An exemplary dataset comprising health re...

Wearable sensor technology like textile electrodes provides novel ambulatory health monitoring solutions but most often goes along with low signal quality. Blind Source Separation (BSS) is capable of extracting the Electrocardiogram (ECG) out of heavily distorted multichannel recordings. However, permutation indeterminacy has to be solved, i.e. the...

Objectives: The inverse relationship between QT interval variability (QTV) and T wave amplitude potentially confounds QT variability assessment. We quantified the influence of the T wave amplitude on QTV in a comprehensive dataset and devised a correction formula. Methods: Three ECG datasets of healthy subjects were analyzed to model the relatio...

Over the past decades, many studies have been published on the extraction of non-invasive foetal electrocardiogram (NI-FECG) from abdominal recordings. Most of these contributions claim to obtain excellent results in detecting foetal QRS (FQRS) complexes in terms of location. A small subset of authors have investigated the extraction of morphologic...

Non-Invasive foetal electrocardiography (NI-FECG) represents an alternative foetal monitoring technique to traditional Doppler ultrasound approaches, that is non-invasive and has the potential to provide additional clinical information. However, despite the significant advances in the field of adult ECG signal processing over the past decades, the...

For centuries, rocking has been used to promote sleep in babies or toddlers. Recent research suggested that relaxation could play a role in facilitating the transition from waking to sleep during rocking. Breathing techniques are often used to promote relaxation. However, studies investigating head motions and body rotations showed that vestibular...

Beat-to-beat variability of the QT interval (QTV) has been used as a marker of repolarization lability and sympathetic activation. The aim of this study was to establish ECG sampling rate requirements for reliable QT interval variability measurement. We measured QTV in high resolution simulated (1000 Hz) and real ECG (1600 Hz; in the supine positio...

Background: Camera-based photoplethysmography (cbPPG) is an optical measurement technique that reveals pulsatile blood flow in cutaneous microcirculation from a distance. cbPPG has been shown to reflect pivotal haemodynamic events like cardiac ejection in healthy subjects. In addition, it provides valuable insight into intrinsic microcirculatory r...

The QT interval in an electrocardiogram (ECG) reflects complex processes affecting the repolarization of ventricular myocardium. Increased QT interval variability (QTV) is thought to be caused by ventricular repolarization lability and has been associated with cardiac mortality. Recent publications have shown that template-based methods are more ro...

Camera-based photoplethysmography is a contactless mean to assess vital parameters, such as heart rate and respiratory rate. In the field of camera-based photoplethysmography, blind source separation (BSS) techniques have been extensively applied to cope with artifacts and noise. Despite their wide usage, there is no consensus that common BSS ap- p...

In the field of camera-based photoplethysmography the application of blind source separation (BSS) techniques has extensively stressed to cope with frequently occurring artifacts and noise. Although said techniques can help to extract the cardiac component from a mixture of input sources, permutation indeterminacy inherit to BSS techniques often in...

Camera-based photoplethysmography (cbPPG) is a recent development in biomedical engineering, which is primarily used to the contactless assessment of subject's heart rate. cbPPG's easy acquisition scheme comes at cost of an usually low signal-to-noise ratio. Artefacts such as subject's movements and light changes impose severe difficulties and have...

Autonomic activity affects beat-to-beat variability of heart rate and QT interval. The aim of this study was to explore whether entropy measures are suitable to detect changes in neural outflow to the heart elicited by two different stress paradigms. We recorded short-term ECG in 11 normal subjects during an experimental protocol that involved head...

We propose a novel method for evaluating the similarity between two 1d patterns. Our method, referred to as two-dimensional signal warping (2DSW), extends the basic ideas of known warping techniques such as dynamic time warping and correlation optimized warping. By employing twodimensional piecewise stretching 2DSW is able to take into account inho...