Method of synchronization and data processing from differents inertial sensors kits sources for the human gait analysis
Aleksandra Goźdź
koliczyna@gmail.comInstitute of Computer Science, Lublin University of Technology, Nadbystrzycka 36B, 20-618 Lublin, Poland (Poland)
Maciej Kalinowski
Institute of Computer Science, Lublin University of Technology, Nadbystrzycka 36B, 20-618 Lublin, Poland (Poland)
Piotr Kopniak
Institute of Computer Science, Lublin University of Technology, Nadbystrzycka 36B, 20-618 Lublin, Poland (Poland)
Abstract
The article talks about results of data synchronization measurements sourced from two recording gait systems for human gait analyses. Two systems are Xsens sensor kits: MT Awinda, Xbus Kit. The article cover file format used to save data and synchronization method for sensor measurement from above mentioned kits. On the basis of the studies carried out, sensor measurement from different places on human body are unify to a common frame of reference. The discussed method provides also progressive data processing for angles range from -180° to 180° conversion to the absolute angle value from initial sensor settings.
Keywords:
motion capture; inertial sensors; measurement synchronization; data processing; Xsens; JavaReferences
[1] Haddas R., Ju K. L., Belanger T., Lieberman I. H., The use of gait analysis in the assessment of patients afflicted with spinal disorders, European Spine Journal, 2018
[2] Schlachetzki J. C. M., Barth J., Marxreiter F., Gossler J., Kohl Z., Reinfelder S. i inni, Wearable sensors objectively measure gait parameters in Parkinson’s disease, Plos One, 2017
[3] Margiotta N., Avitabile G., Coviello G., A Wearable Wireless System for Gait Analysis for Early Diagnosis of Alzheimer and Parkinson Disease, IEEE, 2016
[4] Chen W., Xu Y., Wang J., Zhang J., Kinematic Analysis of Human Gait Based on Wearable Sensor System for Gait Rehabilitation, Journal of Medical and Biological Engineering, 2016
[5] Kopniak P., Kamiński M., Natural interface for robotic arm controlling based on inertial motion capture, IEEE, 2016
[6] Kopniak P., Kamiński M., Żyła K., Zdalne sterowanie ramieniem robota z wykorzystaniem inercyjnych czujników rejestracji ruchu, Logistyka, 2014
[7] Sacha E., Metody trójwymiarowej analizy ruchu człowieka, Aktualne Problemy Biomechaniki, 2008
[8] Kopniak P., Java wrapper for Xsens motion capture system, IEEE, 2014
[9] Bannach D., Amft O., Lukowicz P., Automatic Event-Based Synchronization of Multimodal Data Streams from Wearable and Ambient Sensors, Springer, 2009
[10] Lukac M., Davis P., Clayton R., Estrin D., Recovering temporal integrity with data driven time synchronization, IEEE, 2009
[11] Xsens 3D motion tracking, https://www.xsens.com, 18.06.2018
[12] Unnamed Systems Technology, https://www.unmannedsystemstechnology.com/2018/07/whitepaper-understanding-xsens-mems-based-motion-trackers/,18.06.2018
[2] Schlachetzki J. C. M., Barth J., Marxreiter F., Gossler J., Kohl Z., Reinfelder S. i inni, Wearable sensors objectively measure gait parameters in Parkinson’s disease, Plos One, 2017
[3] Margiotta N., Avitabile G., Coviello G., A Wearable Wireless System for Gait Analysis for Early Diagnosis of Alzheimer and Parkinson Disease, IEEE, 2016
[4] Chen W., Xu Y., Wang J., Zhang J., Kinematic Analysis of Human Gait Based on Wearable Sensor System for Gait Rehabilitation, Journal of Medical and Biological Engineering, 2016
[5] Kopniak P., Kamiński M., Natural interface for robotic arm controlling based on inertial motion capture, IEEE, 2016
[6] Kopniak P., Kamiński M., Żyła K., Zdalne sterowanie ramieniem robota z wykorzystaniem inercyjnych czujników rejestracji ruchu, Logistyka, 2014
[7] Sacha E., Metody trójwymiarowej analizy ruchu człowieka, Aktualne Problemy Biomechaniki, 2008
[8] Kopniak P., Java wrapper for Xsens motion capture system, IEEE, 2014
[9] Bannach D., Amft O., Lukowicz P., Automatic Event-Based Synchronization of Multimodal Data Streams from Wearable and Ambient Sensors, Springer, 2009
[10] Lukac M., Davis P., Clayton R., Estrin D., Recovering temporal integrity with data driven time synchronization, IEEE, 2009
[11] Xsens 3D motion tracking, https://www.xsens.com, 18.06.2018
[12] Unnamed Systems Technology, https://www.unmannedsystemstechnology.com/2018/07/whitepaper-understanding-xsens-mems-based-motion-trackers/,18.06.2018
Goźdź, A., Kalinowski, M., & Kopniak, P. (2018). Method of synchronization and data processing from differents inertial sensors kits sources for the human gait analysis. Journal of Computer Sciences Institute, 9, 345–349. https://doi.org/10.35784/jcsi.708
Authors
Aleksandra Goźdźkoliczyna@gmail.com
Institute of Computer Science, Lublin University of Technology, Nadbystrzycka 36B, 20-618 Lublin, Poland Poland
Authors
Maciej KalinowskiInstitute of Computer Science, Lublin University of Technology, Nadbystrzycka 36B, 20-618 Lublin, Poland Poland
Authors
Piotr KopniakInstitute of Computer Science, Lublin University of Technology, Nadbystrzycka 36B, 20-618 Lublin, Poland Poland
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