Toward Real-Time Automated Detection of Turns during Gait Using Wearable Inertial Measurement Units

Previous studies have presented algorithms for detection of turns during gait using wearable sensors, but those algorithms were not built for real-time use. This paper therefore investigates the optimal approach for real-time detection of planned turns during gait using wearable inertial measurement units. Several different sensor positions (head, back and legs) and three different detection criteria (orientation, angular velocity and both) are compared with regard to their ability to correctly detect turn onset. Furthermore, the different sensor positions are compared with regard to their ability to predict the turn direction and amplitude. The evaluation was performed on ten healthy subjects who performed left/right turns at three amplitudes (22, 45 and 90 degrees). Results showed that turn onset can be most accurately detected with sensors on the back and using a combination of orientation and angular velocity. The same setup also gives the best prediction of turn direction and amplitude. Preliminary measurements with a single amputee were also performed and highlighted important differences such as slower turning that need to be taken into account.

[1]  P H Veltink,et al.  Detection of the onset of gait initiation using kinematic sensors and EMG in transfemoral amputees. , 2014, Gait & posture.

[2]  Sakineh B Akram,et al.  Effect of walking velocity on segment coordination during pre-planned turns in healthy older adults. , 2010, Gait & posture.

[3]  Kamiar Aminian,et al.  On-Shoe Wearable Sensors for Gait and Turning Assessment of Patients With Parkinson's Disease , 2013, IEEE Transactions on Biomedical Engineering.

[4]  Ozkan Bebek,et al.  Personal Navigation via High-Resolution Gait-Corrected Inertial Measurement Units , 2010, IEEE Transactions on Instrumentation and Measurement.

[5]  Antonio M. López,et al.  Pedestrian Navigation Based on a Waist-Worn Inertial Sensor , 2012, Sensors.

[6]  Toshiyo Tamura,et al.  Detection of anticipatory postural adjustments prior to gait initiation using inertial wearable sensors , 2011, Journal of NeuroEngineering and Rehabilitation.

[7]  Roman Kamnik,et al.  Kinematics based sensory fusion for wearable motion assessment in human walking , 2014, Comput. Methods Programs Biomed..

[8]  Tao Liu,et al.  A Wearable Ground Reaction Force Sensor System and Its Application to the Measurement of Extrinsic Gait Variability , 2010, Sensors.

[9]  Sean Pearson,et al.  Continuous Monitoring of Turning in Patients with Movement Disability , 2013, Sensors.

[10]  J. Frank,et al.  Coordination of segments reorientation during on-the-spot turns in healthy older adults in eyes-open and eyes-closed conditions. , 2010, Gait & posture.

[11]  Marko Munih,et al.  Development and validation of a wearable inertial measurement system for use with lower limb exoskeletons , 2011, 2011 11th IEEE-RAS International Conference on Humanoid Robots.

[12]  Barbara Caputo,et al.  Improving Control of Dexterous Hand Prostheses Using Adaptive Learning , 2013, IEEE Transactions on Robotics.

[13]  P Cappa,et al.  Experimental evaluation of indoor magnetic distortion effects on gait analysis performed with wearable inertial sensors , 2014, Physiological measurement.

[14]  Peter H Veltink,et al.  Ambulatory estimation of foot placement during walking using inertial sensors. , 2010, Journal of biomechanics.

[15]  Xavier Crevoisier,et al.  Quantitative estimation of foot-flat and stance phase of gait using foot-worn inertial sensors. , 2013, Gait & posture.

[16]  Nicola Vitiello,et al.  Automated detection of gait initiation and termination using wearable sensors. , 2013, Medical engineering & physics.

[17]  Michael Goldfarb,et al.  Standing Stability Enhancement With an Intelligent Powered Transfemoral Prosthesis , 2011, IEEE Transactions on Biomedical Engineering.

[18]  Guido Pasquini,et al.  Online Phase Detection Using Wearable Sensors for Walking with a Robotic Prosthesis , 2014, Sensors.

[19]  Simona Crea,et al.  A Wireless Flexible Sensorized Insole for Gait Analysis , 2014, Sensors.

[20]  Gammon M Earhart,et al.  A Kinematic and Electromyographic Analysis of Turning in People With Parkinson Disease , 2009, Neurorehabilitation and neural repair.

[21]  Michael Goldfarb,et al.  Multiclass Real-Time Intent Recognition of a Powered Lower Limb Prosthesis , 2010, IEEE Transactions on Biomedical Engineering.

[22]  Leia Stirling,et al.  Examining anticipatory turn signaling in typically developing 4- and 5-year-old children for applications in active orthotic devices. , 2013, Gait & posture.

[23]  Anne-Hélène Olivier,et al.  Curvature–velocity analysis to identify turning steps while walking , 2009 .

[24]  Yoshiyuki Sankai,et al.  Wearable Gait Measurement System with an Instrumented Cane for Exoskeleton Control , 2014, Sensors.

[25]  Jung-Keun Lee,et al.  Quasi real-time gait event detection using shank-attached gyroscopes , 2011, Medical & Biological Engineering & Computing.

[26]  Lori Ann Vallis,et al.  Strategies used by older adults to change travel direction. , 2007, Gait & posture.

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

[28]  Eduardo Palermo,et al.  A Novel HMM Distributed Classifier for the Detection of Gait Phases by Means of a Wearable Inertial Sensor Network , 2014, Sensors.

[29]  R.F. Weir,et al.  The Optimal Controller Delay for Myoelectric Prostheses , 2007, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[30]  Tao Liu,et al.  Development of a wearable sensor system for quantitative gait analysis , 2009 .

[31]  Roger Gassert,et al.  Low-power sensor module for long-term activity monitoring , 2011, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.