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Figure 1. Exemplars of Human-Computer Integration: extending the body with additional robotic arms; [70] embedding computation into the body using electric muscle stimulation to manipulate handwriting [48]; and, a tail extension controlled by body movements [86].

We present a set of heuristics that significantly increase the robustness of motion sensor-based activity recognition with respect to sensor displacement. In this paper placement refers to the position within a single body part (e.g, lower arm). We show how, within certain limits and with modest quality degradation, motion sensorbased activity recognition can be implemented in a displacement tolerant way. We first describe the physical principles that lead to our heuristic. We then evaluate them first on a set of synthetic lower arm motions which are well suited to illustrate the strengths and limits of our approach, then on an extended modes of locomotion problem (sensors on the upper leg) and finally on a set of exercises performed on various gym machines (sensors placed on the lower arm). In this example our heuristic raises the displaced recognition rate from 24% for a displaced accelerometer, which had 96% recognition when not displaced, to 82%.

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Opportunistic sensing allows to efficiently collect information about the physical world and the persons behaving in it. This may mainstream human context and activity recognition in wearable and pervasive computing by removing requirements for a specific deployed infrastructure. In this paper we introduce the newly started European research project OPPORTUNITY within which we develop mobile opportunistic activity and context recognition systems. We outline the project's objective, the approach we follow along opportunistic sensing, data processing and interpretation, and autonomous adaptation and evolution to environmental and user changes, and we outline preliminary results.

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Beside their stunning graphics, modern entertain-compensate for various inaccuracies inherent in inexpensive ment systems feature ever-higher levels of immersive user-wearable sensor system. The inaccuracies result from the interaction. Today, this is mostly achieved by virtual (VR) and limited resolution and sampling rate of the sensors, variations augmented reality (AR) setups. On top of these, we envision to add ambient intelligence and context awareness to gaming in sensor placement, dynamic sensor displacement during applications in general and games of martial arts in particular. user motion, and other sources of noise (e.g., environmental To this end, we conducted an initial experiment with inexpensive magnetic fields or temperature-related sensor drift). The body-worn gyroscopes and acceleration sensors for the Chum challenge in algorithmic design is to find features that are Kiu motion sequence in Wing Tsun (a popular form of Kung sensitive to the relevant motion characteristics and at the Fu). The resulting data confirm the feasibility of our vision.. .s Fine-tuned adaptations of various thresholding and pattern-same time insensitive to the inaccuracies mentioned before. matching techniques known from the fields of computational As decribed in Section III, we conducted an initial experintelligence and signal processing should suffice to automate the iment capturing Wing Tsun movements with wearable gyroanalysis and recognition of important Wing Tsun movements scopes and acceleration sensors to test the feasibility of our in real time. Moreover, the data also seem to allow for the vision. Section IV discusses and analyzes the experimental possibility of automatically distinguishing between certain levels vision. Section IV discussesand ana es the erieon of expertise and quality in executing the movements.results, provilng to be very promsilng indeed. Based thereon, Keywords: Body-worn Sensors, Experiment, Games of it certainly seems worthwhile to continue in this direction Martial Arts, Kung Fu, Motion Analysis, Movement Recog-and try to automate at least some parts (if not all) of an nition, Wearable Computing, Wing Tsun expert analysis for many important Wing Tsun movements. Beside in sports and game play, martial arts from the I. INTRODUCTION Far East gain ever more popularity and importance in many Video analysis and motion capturing are standard tools in other areas as well. Tai Chi, for instance, is of special professional sports to monitor and improve athletic perfor-interest because clinical studies show that it helps to reduce mance by recognizing and fine-tuning the quality of move-the probability of falling, especially for the elderly [l] and ment. Cutting-edge systems with high-quality sensors hardly patients with chronic conditions [2]. suffice to fulfill these professionals' needs. Quite often, trainers and other experts still process the recorded data by II. RELATED WORK hand. The whole setup and procedure are not only expensive By now, many independent researchers have demonstrated and...