Human tracking and identification using a sensitive floor and wearable accelerometers
M Sousa, A Techmer, A Steinhage… - 2013 IEEE …, 2013 - ieeexplore.ieee.org
M Sousa, A Techmer, A Steinhage, C Lauterbach, P Lukowicz
2013 IEEE International Conference on Pervasive Computing and …, 2013•ieeexplore.ieee.orgWe describe a method for user tracking and localization based on textile capacitive sensor
arrays placed under the floor. The sensor array is a commercial product (SensFloor®) that
can be installed under any standard floor type (from carpet to stone) and is able to detect
objects (including the user's foot) being placed on it. The challenges addressed in this paper
are (1) how to map sequences of such signals onto user trajectories and (2) how to correlate
the steps detected by the SensFloor system with the step detection based on a wearable …
arrays placed under the floor. The sensor array is a commercial product (SensFloor®) that
can be installed under any standard floor type (from carpet to stone) and is able to detect
objects (including the user's foot) being placed on it. The challenges addressed in this paper
are (1) how to map sequences of such signals onto user trajectories and (2) how to correlate
the steps detected by the SensFloor system with the step detection based on a wearable …
We describe a method for user tracking and localization based on textile capacitive sensor arrays placed under the floor. The sensor array is a commercial product (SensFloor®) that can be installed under any standard floor type (from carpet to stone) and is able to detect objects (including the user's foot) being placed on it. The challenges addressed in this paper are (1) how to map sequences of such signals onto user trajectories and (2) how to correlate the steps detected by the SensFloor system with the step detection based on a wearable accelerometer as means of user identification. Footstep detection is performed online on the devices, which are seamlessly integrated with the floor's wireless sensor network. Initial experiments performed over a week in a real life office environment show the ability to track multiple humans and to identify up to three users walking in a narrow corridor at the same time.
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