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In this paper, we propose motion and flying force analysis of ski-jumping using on-body acceleration sensors. We present our first analysis results of on-body acceleration sensor data from an Olympic ski jumping champion. In this study, we collected a data set of 37 ski jumps on the world-class athlete Simon Ammann, during training, World Cup competitions, and his Olympic victories 2010. Five miniaturized...
We present a wearable system approach to investigate changes in stage fright in professional musicians under realistic performance conditions. Towards this goal, we monitored stage fright in a young professional cellist during three consecutive performances of a skill-demanding piece in front of a professional audience. The wearable system measured ECG and body movement at multiple locations. We found...
We present a novel approach to analyse and model psycho-physiological body activation patterns that emerge from physical and mental activity during daily routines. We analyse our approach on a 62 h dataset of daily routine recordings using acceleration and heart rate sensors. We present a descriptive analysis of psycho-physiological activations during the routines using a novel visualisation technique...
Automatic dietary monitoring (ADM) offers new perspectives to reduce the self-reporting burden for participants in diet coaching programs. This paper presents an approach to predict weight of individual bites taken. We utilize a pattern recognition procedure to spot chewing cycles and food type in continuous data from an ear-pad chewing sound sensor. The recognized information is used to predict bite...
Chewing is an essential part of food intake. The analysis and detection of food patterns is an important component of an automatic dietary monitoring system. However chewing is a time-variable process depending on food properties. We present an automated methodology to extract sub-sequences of similar chews from chewing sound recordings. The approach is based on a chew-accurate segmentation of the...
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