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We developed an application for Android™-based mobile devices that allows real-time electrocardiogram (ECG) monitoring and automated arrhythmia detection by analyzing ECG parameters. ECG data provided by pre-recorded files or acquired live by accessing a Shimmer™ sensor node via Bluetooth™ can be processed and evaluated. The application is based on the(More)
Motor impairments are the prerequisite for the diagnosis in Parkinson's disease (PD). The cardinal symptoms (bradykinesia, rigor, tremor, and postural instability) are used for disease staging and assessment of progression. They serve as primary outcome measures for clinical studies aiming at symptomatic and disease modifying interventions. One major caveat(More)
Cardiovascular diseases are the number one cause of death worldwide. Currently, portable battery-operated systems such as mobile phones with wireless ECG sensors have the potential to be used in continuous cardiac function assessment that can be easily integrated into daily life. These portable point-of-care diagnostic systems can therefore help unveil and(More)
The electrocardiogram (ECG) is a key diagnostic tool in heart disease and may serve to detect ischemia, arrhythmias, and other conditions. Automatic, low cost monitoring of the ECG signal could be used to provide instantaneous analysis in case of symptoms and may trigger the presentation to the emergency department. Currently, since mobile devices(More)
Insufficient physical activity is the 4th leading risk factor for mortality. Methods for assessing the individual daily life activity (DLA) are of major interest in order to monitor the current health status and to provide feedback about the individual quality of life. The conventional assessment of DLAs with self-reports induces problems like reliability,(More)
The measurement of video quality for lossy and low-bitrate network transmissions is a challenging topic. Especially, the temporal artifacts which are introduced by video transmission systems and their effects on the viewer's satisfaction have to be addressed. This paper focuses on a framework that adds a temporal distortion awareness to typical video(More)
Postural instability is one of the main motor impairment of Parkinson's disease (PD). The Pull Test is the most common clinical examination to assess postural instability in PD. However, the subjectivity and low discriminative power of this test presents as a major drawback. In this paper we propose a novel methodology to estimate the Pull Test scores from(More)
The development of wearable sensors has opened the door for long-term assessment of movement disorders. However, there is still a need for developing methods suitable to monitor motor symptoms in and outside the clinic. The purpose of this paper was to investigate deep learning as a method for this monitoring. Deep learning recently broke records in speech(More)
Embedded mobile systems for analysis and classification become more and more important in the field of sports and sports science. Small and lightweight sensors in sportswear offer the possibility to monitor the athletes in a realistic environment, e.g. during an outdoor run. During the activity, the sportswear can automatically adapt to the current(More)
The identification of differences between groups is often important in biomechanics. This paper presents group classification tasks using kinetic and kinematic data from a prospective running injury study. Groups composed of gender, of shod/barefoot running and of runners who developed patellofemoral pain syndrome (PFPS) during the study, and asymptotic(More)