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      • Department of Electrical and Electronics Engineering
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      Pedestrian dead reckoning employing simultaneous activity recognition cues

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      Author
      Altun, K.
      Barshan, B.
      Date
      2012-01-11
      Source Title
      Measurement Science and Technology
      Print ISSN
      0957-0233
      Publisher
      Institute of Physics Publishing
      Volume
      23
      Issue
      2
      Pages
      025103-1 - 025103-20
      Language
      English
      Type
      Article
      Item Usage Stats
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      120
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      Abstract
      We consider the human localization problem using body-worn inertial/magnetic sensor units. Inertial sensors are characterized by a drift error caused by the integration of their rate output to obtain position information. Because of this drift, the position and orientation data obtained from inertial sensors are reliable over only short periods of time. Therefore, position updates from externally referenced sensors are essential. However, if the map of the environment is known, the activity context of the user can provide information about his position. In particular, the switches in the activity context correspond to discrete locations on the map. By performing localization simultaneously with activity recognition, we detect the activity context switches and use the corresponding position information as position updates in a localization filter. The localization filter also involves a smoother that combines the two estimates obtained by running the zero-velocity update algorithm both forward and backward in time. We performed experiments with eight subjects in indoor and outdoor environments involving walking, turning and standing activities. Using a spatial error criterion, we show that the position errors can be decreased by about 85% on the average. We also present the results of two 3D experiments performed in realistic indoor environments and demonstrate that it is possible to achieve over 90% error reduction in position by performing localization simultaneously with activity recognition.
      Keywords
      Human activity recognition
      Human localization
      Inertial sensing
      Pedestrian dead reckoning
      Wearable computing
      Dead reckoning
      Human activity recognition
      Human localization
      Inertial sensing
      Wearable computing
      Experiments
      Inertial navigation systems
      Navigation
      Wearable computers
      Sensors
      Permalink
      http://hdl.handle.net/11693/21600
      Published Version (Please cite this version)
      http://dx.doi.org/10.1088/0957-0233/23/2/025103
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      • Department of Electrical and Electronics Engineering 3613
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