Christoph Brüser

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A ballistocardiograph records the mechanical activity of the heart. We present a novel algorithm for the detection of individual heart beats and beat-to-beat interval lengths in ballistocardiograms (BCGs) from healthy subjects. An automatic training step based on unsupervised learning techniques is used to extract the shape of a single heart beat from the(More)
Reliable and accurate estimation of instantaneous frequencies of physiological rhythms, such as heart rate, is critical for many healthcare applications. Robust estimation is especially challenging when novel unobtrusive sensors are used for continuous health monitoring in uncontrolled environments, because these sensors can create significant amounts of(More)
Contactless vital sign measurement technologies often have the drawback of severe motion artifacts and periods in which no signal is available. However, using several identical or physically different sensors, redundancy can be used to decrease the error in noncontact heart rate estimation, while increasing the time period during which reliable data are(More)
Sensor fusion is a growing field within the medical signal processing community. Traditionally, it is performed implicitly by the physician when diagnosing the state of a patient from various measurement modalities such as elec-trocardiography (ECG), arterial blood pressure (ABP) or photoplethysmography (PPG). These may represent different physical(More)
We present a feasibility study on the automatic detection of atrial fibrillation (AF) from a cardiac vibration signal (ballistocardiogram). Considering the prevalence of AF among the elderly and the risk of silent and undetected AF, there is a need for screening this population. One way to unobtrusively measure cardiopulmonary activity is the integration of(More)
Our work covers improvements in sensors and signal processing for unobtrusive, long-term monitoring of cardiac (and respiratory) rhythms using only non-invasive vibration sensors. We describe a system for the unobtrusive monitoring of vital signs by means of an array of novel optical ballistocardiography (BCG) sensors placed underneath a regular bed(More)
We propose and evaluate an unsupervised method for the estimation of heart rate variability (HRV) indices from ballistocardiograms (BCGs) recorded by a bed-mounted, electromechanical film (EMFi) sensor during sleep. After estimating the beat-to-beat intervals from the BCGs, short-term time-and frequency-domain HRV indices are computed and compared to an ECG(More)
The aim of this paper is to present and evaluate algorithms for heartbeat interval estimation from multiple spatially distributed force sensors integrated into a bed. Moreover, the benefit of using multichannel systems as opposed to a single sensor is investigated. While it might seem intuitive that multiple channels are superior to a single channel, the(More)
Unobtrusive, long-term monitoring of cardiac (and respiratory) rhythms using only non-invasive vibration sensors mounted in beds promises to unlock new applications in home and low acuity monitoring. This paper presents a novel concept for such a system based on an array of near infrared (NIR) sensors placed underneath a regular bed mattress. We focus on(More)
BACKGROUND Heart rate monitoring is especially interesting in patients with atrial fibrillation (AF) and is routinely performed by ECG. A ballistocardiography (BCG) foil is an unobtrusive sensor for mechanical vibrations. We tested the correlation of heartbeat cycle length detection by a novel algorithm for a BCG foil to an ECG in AF and sinus rhythm (SR).(More)