Human Body Structure Calibration Using Wearable Inertial Sensors

This work proposes an inertial sensor-based human body structure parameters calibration methodology, aimed at being combined with a motion tracking and gesture recognition system in a virtual reality motion game context to reduce the player’s motion control learning time and improve the accuracy and ease of game operation. This proposed calibration protocol is based on the three-axis accelerometer outputs by wireless inertial sensors to calibrate user’s body parts length (including the forearm, upper arm, torso, shinbone, and whole leg) through four easy-to-perform static poses and a streamlined calibration procedure. Through this experiment, this calibration methodology proved to be a robust approach to calibrate physically normal users’ body parts length, with satisfactory calibration accuracy (overall 7.64% average calibration error rate). In addition, in order to make the calibration process more efficient, effective, and user-friendly, a calibration auxiliary system sample interface to facilitate users has been proposed in this thesis.

[1]  Juntao Ye,et al.  A calibration process for tracking upper limb motion with inertial sensors , 2011, 2011 IEEE International Conference on Mechatronics and Automation.

[2]  Parvaneh Saeedi,et al.  Vision-based 3-D trajectory tracking for unknown environments , 2006, IEEE Transactions on Robotics.

[3]  Peter H. Veltink,et al.  Ambulatory human motion tracking by fusion of inertial and magnetic sensing with adaptive actuation , 2009, Medical & Biological Engineering & Computing.

[4]  Anton Nijholt,et al.  Turning Shortcomings into Challenges: Brain-Computer Interfaces for Games , 2009, INTETAIN.

[5]  Roman Kamnik,et al.  An inertial and magnetic sensor based technique for joint angle measurement. , 2007, Journal of biomechanics.

[6]  Paul Anderson,et al.  Gesture-recognition with Non-referenced Tracking , 2006, 3D User Interfaces (3DUI'06).

[7]  Sangjin Hong,et al.  Acoustic Sensor-Based Multiple Object Tracking with Visual Information Association , 2010, EURASIP J. Adv. Signal Process..

[8]  Martin Buss,et al.  Visual tracking and control of a quadcopter using a stereo camera system and inertial sensors , 2009, 2009 International Conference on Mechatronics and Automation.

[9]  P H Veltink,et al.  Ambulatory measurement of arm orientation. , 2007, Journal of biomechanics.

[10]  Angelo M. Sabatini,et al.  Assessment of walking features from foot inertial sensing , 2005, IEEE Transactions on Biomedical Engineering.

[11]  Aurelio Cappozzo,et al.  Joint kinematics estimate using wearable inertial and magnetic sensing modules. , 2008, Gait & posture.

[12]  Kyoung-Ho Kang,et al.  Self-contained spatial input device for wearable computers , 2003, Seventh IEEE International Symposium on Wearable Computers, 2003. Proceedings..

[13]  Regan L. Mandryk,et al.  Biofeedback game design: using direct and indirect physiological control to enhance game interaction , 2011, CHI.

[14]  Eduardo Rocon,et al.  An IMU-to-Body Alignment Method Applied to Human Gait Analysis , 2016, Sensors.

[15]  Naser El-Sheimy,et al.  A new multi-position calibration method for MEMS inertial navigation systems , 2007 .

[16]  Rafiqul Zaman Khan,et al.  Comparative Study of Hand Gesture Recognition System , 2012 .

[17]  J. Verly,et al.  Development and validation of an accelerometer-based method for quantifying gait events. , 2015, Medical engineering & physics.

[18]  Björn Eskofier,et al.  Inertial Sensor-Based Stride Parameter Calculation From Gait Sequences in Geriatric Patients , 2015, IEEE Transactions on Biomedical Engineering.

[19]  D. Roetenberg,et al.  Xsens MVN: Full 6DOF Human Motion Tracking Using Miniature Inertial Sensors , 2009 .

[20]  Do Hyoung Shin,et al.  Utilization of ubiquitous computing for construction AR technology , 2009 .

[21]  Begonya Garcia-Zapirain,et al.  Gait Analysis Methods: An Overview of Wearable and Non-Wearable Systems, Highlighting Clinical Applications , 2014, Sensors.

[22]  K. Aminian,et al.  Ambulatory measurement of 3D knee joint angle. , 2008, Journal of biomechanics.

[23]  Shengli Zhou,et al.  Gesture recognition for interactive controllers using MEMS motion sensors , 2009, 2009 4th IEEE International Conference on Nano/Micro Engineered and Molecular Systems.

[24]  Hee-Jun Kang,et al.  A DCM Based Orientation Estimation Algorithm with an Inertial Measurement Unit and a Magnetic Compass , 2009, J. Univers. Comput. Sci..

[25]  Ruize Xu,et al.  MEMS Accelerometer Based Nonspecific-User Hand Gesture Recognition , 2012, IEEE Sensors Journal.

[26]  Greg Welch,et al.  Welch & Bishop , An Introduction to the Kalman Filter 2 1 The Discrete Kalman Filter In 1960 , 1994 .

[27]  William T. Freeman,et al.  Television control by hand gestures , 1994 .

[28]  Mao Li,et al.  A Cubic 3-Axis Magnetic Sensor Array for Wirelessly Tracking Magnet Position and Orientation , 2010, IEEE Sensors Journal.

[29]  Yunhui Liu,et al.  Hand-Writing Motion Tracking with Vision-Inertial Sensor Fusion: Calibration and Error Correction , 2014, Sensors.

[30]  Fernando Torres,et al.  Kalman Filtering for Sensor Fusion in a Human Tracking System , 2010 .

[31]  Adriano Ferrari,et al.  ‘Outwalk’: a protocol for clinical gait analysis based on inertial and magnetic sensors , 2009, Medical & Biological Engineering & Computing.

[32]  Thomas Seel,et al.  IMU-Based Joint Angle Measurement for Gait Analysis , 2014, Sensors.

[33]  J. Pineda,et al.  Learning to control brain rhythms: making a brain-computer interface possible , 2003, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[34]  Donald E. Gustafson,et al.  Miniature Inertial and Augmentation Sensors for Integrated Inertial/GPS Based Navigation Applications , 2010 .

[35]  Didier Stricker,et al.  Advanced tracking through efficient image processing and visual-inertial sensor fusion , 2008, 2008 IEEE Virtual Reality Conference.

[36]  F. V. D. van der Helm,et al.  Magnetic distortion in motion labs, implications for validating inertial magnetic sensors. , 2009, Gait & posture.

[37]  B M Jolles,et al.  Functional calibration procedure for 3D knee joint angle description using inertial sensors. , 2009, Journal of biomechanics.

[38]  W. H. Baird.  An introduction to inertial navigation , 2009 .

[39]  R. Chellappa,et al.  Recursive 3-D motion estimation from a monocular image sequence , 1990 .

[40]  Makoto Hashizume,et al.  Objective Skill Evaluation for Laparoscopic Training Based on Motion Analysis , 2013, IEEE Transactions on Biomedical Engineering.

[41]  Federico Pedersini,et al.  Autocalibration of MEMS Accelerometers , 2009, IEEE Transactions on Instrumentation and Measurement.

[42]  Sun Young Kim,et al.  Improvement of a Low Cost MEMS Inertial-GPS Integrated System Using Wavelet Denoising Techniques , 2011 .

[43]  Gernot R. Müller-Putz,et al.  Game-like Training to Learn Single Switch Operated Neuroprosthetic Control , 2007 .

[44]  Jeen-Shing Wang,et al.  An Accelerometer-Based Digital Pen With a Trajectory Recognition Algorithm for Handwritten Digit and Gesture Recognition , 2012, IEEE Transactions on Industrial Electronics.

[45]  Bobby Bodenheimer,et al.  Stepping off a ledge in an HMD-based immersive virtual environment , 2013, SAP.

[46]  José Eugenio Naranjo,et al.  GPS and Inertial Systems for High Precision Positioning on Motorways , 2009, Journal of Navigation.

[47]  Dennis Arsenault,et al.  A Quaternion-Based Motion Tracking and Gesture Recognition System Using Wireless Inertial Sensors , 2014 .

[48]  Marko Turpeinen,et al.  The influence of implicit and explicit biofeedback in first-person shooter games , 2010, CHI.

[49]  Eduardo Palermo,et al.  Experimental evaluation of accuracy and repeatability of a novel body-to-sensor calibration procedure for inertial sensor-based gait analysis , 2014 .

[50]  Guang-Zhong Yang,et al.  Wearable Sensing for Solid Biomechanics: A Review , 2015, IEEE Sensors Journal.

[51]  Guang-Zhong Yang,et al.  Deformable structure from motion by fusing visual and inertial measurement data , 2012, 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[52]  Greg Welch,et al.  Motion Tracking: No Silver Bullet, but a Respectable Arsenal , 2002, IEEE Computer Graphics and Applications.

[53]  Bertram Taetz,et al.  On Inertial Body Tracking in the Presence of Model Calibration Errors , 2016, Sensors.

[54]  Xiaoji Niu,et al.  Analysis and Modeling of Inertial Sensors Using Allan Variance , 2008, IEEE Transactions on Instrumentation and Measurement.

[55]  Alan J. Dix,et al.  Affective Videogames and Modes of Affective Gaming: Assist Me, Challenge Me, Emote Me (ACE) , 2005, DiGRA Conference.

[56]  Salvatore Sessa,et al.  Anatomical Calibration through Post-Processing of Standard Motion Tests Data , 2016, Sensors.

[57]  Keiji Hashimoto,et al.  Ability for Basic Movement as an Early Predictor of Functioning Related to Activities of Daily Living in Stroke Patients , 2007, Neurorehabilitation and neural repair.

[58]  Domenico Formica,et al.  A New Calibration Methodology for Thorax and Upper Limbs Motion Capture in Children Using Magneto and Inertial Sensors , 2014, Sensors.

[59]  F. Seco,et al.  A comparison of Pedestrian Dead-Reckoning algorithms using a low-cost MEMS IMU , 2009, 2009 IEEE International Symposium on Intelligent Signal Processing.

[60]  Tao Liu,et al.  Gait Analysis Using Wearable Sensors , 2012, Sensors.

[61]  Ronald Azuma,et al.  Hybrid inertial and vision tracking for augmented reality registration , 1999, Proceedings IEEE Virtual Reality (Cat. No. 99CB36316).

[62]  Junichi Hoshino,et al.  A fitness game reflecting heart rate , 2006, ACE '06.

[63]  Luis Mejías Alvarez,et al.  Error analysis and attitude observability of a monocular GPS/visual odometry integrated navigation filter , 2012, Int. J. Robotics Res..

[64]  Valentina Camomilla,et al.  Countermovement jump performance assessment using a wearable 3D inertial measurement unit , 2011, Journal of sports sciences.

[65]  Huosheng Hu,et al.  Human motion tracking for rehabilitation - A survey , 2008, Biomed. Signal Process. Control..

[66]  S. Mitra,et al.  Gesture Recognition: A Survey , 2007, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[67]  Yudan Yi,et al.  On improving the accuracy and reliability of GPS/INS-based direct sensor georeferencing , 2007 .

[68]  Jeroen D. Hol,et al.  Sensor Fusion and Calibration of Inertial Sensors, Vision, Ultra-Wideband and GPS , 2011 .

[69]  S. Gordon,et al.  Waging war on modern chronic diseases: primary prevention through exercise biology , 2000, Journal of applied physiology.

[70]  Diana Trojaniello,et al.  Accurately measuring human movement using magneto-inertial sensors: techniques and challenges , 2015, 2015 IEEE International Symposium on Inertial Sensors and Systems (ISISS) Proceedings.

[71]  Gustaf Hendeby,et al.  Using optical flow for filling the gaps in visual-inertial tracking , 2010, 2010 18th European Signal Processing Conference.

[72]  Josien C. van den Noort,et al.  Reliability and precision of 3D wireless measurement of scapular kinematics , 2014, Medical & Biological Engineering & Computing.

[73]  K. Fox,et al.  Dance, Dance Evolution: Accelerometer Sensor Networks as Input to Video Games , 2007, 2007 IEEE International Workshop on Haptic, Audio and Visual Environments and Games.

[74]  Athanasios V. Vasilakos,et al.  Body Area Networks: A Survey , 2010, Mob. Networks Appl..

[75]  Young-Kee Jung,et al.  Gesture Recognition Based on Motion Inertial Sensors for Ubiquitous Interactive Game Contents , 2010 .

[76]  David Swapp,et al.  An ‘In the Wild’ Experiment on Presence and Embodiment using Consumer Virtual Reality Equipment , 2016, IEEE Transactions on Visualization and Computer Graphics.

[77]  Marie-Odile Berger,et al.  Use of inertial sensors to support video tracking , 2007, Comput. Animat. Virtual Worlds.

[78]  Jörg F. Wagner.  Adapting the Principle of Integrated Navigation Systems to Measuring the Motion of Rigid Multibody Systems , 2004 .

[79]  Hideo Saito,et al.  3-D drawing system via hand motion recognition from two cameras , 2000, Smc 2000 conference proceedings. 2000 ieee international conference on systems, man and cybernetics. 'cybernetics evolving to systems, humans, organizations, and their complex interactions' (cat. no.0.

[80]  Yunhui Liu,et al.  2D Human Gesture Tracking and Recognition by the Fusion of MEMS Inertial and Vision Sensors , 2014, IEEE Sensors Journal.