Christoph Dinh

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This paper focuses on the challenge of automatical detecting an emergency, e.g., a fall by an elderly person, and to generate an alert such as a phone call or sending a SMS to a relative as fast as possible. The presented system only needs one single triaxial accelerometer. The algorithmic part uses the paradigm of knowledge-based methods. Unlike pattern(More)
With its millisecond temporal resolution, Magnetoencephalography (MEG) is well suited for real-time monitoring of brain activity. Real-time feedback allows the adaption of the experiment to the subject’s reaction and increases time efficiency by shortening acquisition and off-line analysis. Two formidable challenges exist in real-time analysis: the low(More)
Versatile controllers for accurate, fast, and real-time synchronized acquisition of large-scale data are useful in many areas of science, engineering, and technology. Here, we describe the development of a controller software based on a technique called queued state machine for controlling the data acquisition (DAQ) hardware, continuously acquiring a large(More)
Nowadays, advanced sensing technologies are used in manys cientific and engineering disciplines, e. g., in medical or industrial applications, enabling the usage of data-driven techniques to derive models. Measures are collected, filtered, aggregated, and processed in acomplexanalytic pipeline, joining them with static models to perform high-leveltasks(More)
We developed a 375-channel, whole-head magnetoencephalography (MEG) system ("BabyMEG") for studying the electrophysiological development of human brain during the first years of life. The helmet accommodates heads up to 95% of 36-month old boys in the USA. The unique two-layer sensor array consists of: (1) 270 magnetometers (10 mm diameter, ∼15 mm(More)
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