Dataset Open Access

Dataset of Survey of Motion Tracking Methods Based on Inertial Sensors: A Focus on Upper Limb Human Motion

Filippeschi, Alessandro; Ruffaldi, Emanuele


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    "description": "<p>MATLAB Dataset for the paper.\u00a0</p>\n\n<p>Paper Abstract:</p>\n\n<p>Motion tracking based on commercial inertial measurements units (IMUs) has been widely studied in the latter years as it is a cost-effective enabling technology for those applications in which motion tracking based on optical technologies is unsuitable. This measurement method has a high impact in human performance assessment and human-robot interaction. IMU motion tracking systems are indeed self-contained and wearable, allowing for long-lasting tracking of the user motion in situated environments. After a survey on IMU-based human tracking, five techniques for motion reconstruction were selected and compared to reconstruct a human arm motion. IMU based estimation was matched against motion tracking based on the Vicon marker-based motion tracking system considered as ground truth. Results show that all but one of the selected models perform similarly (about 35 mm average position estimation error).</p>", 
    "license": {
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    "title": "Dataset of Survey of Motion Tracking Methods Based on Inertial Sensors: A Focus on Upper Limb Human Motion", 
    "journal": {
      "volume": "17", 
      "issue": "6", 
      "title": "Sensors"
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    "references": [
      "Filippeschi, A.; Schmitz, N.; Miezal, M.; Bleser, G.; Ruffaldi, E.; Stricker, D.\tSurvey of Motion Tracking Methods Based on Inertial Sensors: A Focus on Upper Limb Human Motion. Sensors 2017, 17, 1257."
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    "keywords": [
      "imu", 
      "inertial", 
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    "publication_date": "2017-06-01", 
    "creators": [
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        "affiliation": "Scuola Superiore Sant'Anna", 
        "name": "Filippeschi, Alessandro"
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        "affiliation": "Scuola Superiore Sant'Anna", 
        "name": "Ruffaldi, Emanuele"
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Views 539
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Data volume 6.9 GB
Unique views 507
Unique downloads 84

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