2006 IEEE Symposium on Computational Intelligence and Games 2006
DOI: 10.1109/cig.2006.311687
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Using Wearable Sensors for Real-Time Recognition Tasks in Games of Martial Arts - An Initial Experiment

Abstract: 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 displac… Show more

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Cited by 79 publications
(35 citation statements)
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“…The accuracy of such a classifier depends on a variety of parameters including the classification algorithm, sensor node placement, types of features extracted from the signal, and number and type of actions/activities to be recognized. While many algorithms such as k-nearest neighbor (k-NN) [7], hidden Markov models (HMM) [8], Naive Bayes [9], and support vector machines [10] have been investigated, the k-NN and HMM are more common in action recognition in the wireless healthcare domain when motion sensors are generally used for information inference.…”
Section: Related Workmentioning
confidence: 99%
“…The accuracy of such a classifier depends on a variety of parameters including the classification algorithm, sensor node placement, types of features extracted from the signal, and number and type of actions/activities to be recognized. While many algorithms such as k-nearest neighbor (k-NN) [7], hidden Markov models (HMM) [8], Naive Bayes [9], and support vector machines [10] have been investigated, the k-NN and HMM are more common in action recognition in the wireless healthcare domain when motion sensors are generally used for information inference.…”
Section: Related Workmentioning
confidence: 99%
“…The variety of systems and applications in the literature, similar to those described above, show that posture tracking is a relatively well-covered research subject with a number of branches and applications: from activity detection [20,21] to position recognition [6,8,9], to real-time movement recognition tasks for martial arts [22] and manufacturing environments [23], added to gait measurement [24]. The systems reported, although by and large application specific, often share a common sensor placement on the body in order to accurately detect the subject's movement and limb positions [25][26][27] but require different degrees of movement sensing accuracy to fulfil the specific application.…”
Section: Related Workmentioning
confidence: 99%
“…It is discovered that exercises can be recognized by utilizing moderately few elements [4], [5], [9]. The studies have also been performed to see if using more components will produce better results [10], [11]. Table I display a comparative analysis of the earlier works performed, for detecting activities using phone sensors.…”
Section: Literature Reviewmentioning
confidence: 99%