An Infrared Sensor-Based Instrumented Shoe for Gait Events Detection on Different Terrains and Transitions

This paper presents a low-cost wireless gait event detection system that incorporates infra-red range sensors mounted laterally at a specific anatomical location on the shoe. This system uses foot clearance information to extract heel strike (HS) and toe-off (TO) events. A subject-specific algorithm based on signature curve matching was developed to estimate the HS and TO in six able-bodied subjects and three transfemoral amputees. The data were acquired in a real-life environment while the subject walked on level ground and ramp terrains, including the transitions. The HS and TO in the level ground were detected with an accuracy of 22.87± 9.93 ms and 10.42± 6.70 ms, respectively, in able-bodied participants. The accuracy of 37.91± 12.36 ms and 20.41± 11.23 ms in HS and TO, respectively, was observed in amputees during level ground walking. Further, within the ramp terrain, the HS and TO were detected with an accuracy of 23.33± 11.20 ms and 13.36± 9.5 ms respectively in able-bodied subjects and 40.35± 12.64 ms and 47.51± 19.23 ms in amputees. This method reports comparable accuracy, with minimal standard deviation, to other existing methods based on accelerometer, gyroscope, electromyography, and force myography. This system is robust, easy to operate, and avoids direct contact with the body. The developed system offers a movable sensor platform in two degrees of freedom that facilitates the adaptability of the proposed system for different heel height and shoe sizes.

[1]  Sneh Anand,et al.  Locomotion mode classification using force myography , 2017, 2017 IEEE Life Sciences Conference (LSC).

[2]  Billur Barshan,et al.  Activity Recognition Invariant to Sensor Orientation with Wearable Motion Sensors , 2017, Sensors.

[3]  Long Wang,et al.  Locomotion Mode Classification Using a Wearable Capacitive Sensing System , 2013, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

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

[5]  Siddhartha Khandelwal,et al.  Gait Event Detection in Real-World Environment for Long-Term Applications: Incorporating Domain Knowledge Into Time-Frequency Analysis , 2016, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[6]  Xuesong Ye,et al.  Real-time gait event detection in a real-world environment using a laser-ranging sensor and gyroscope fusion method , 2018, Physiological measurement.

[7]  Paola Catalfamo,et al.  Gait Event Detection on Level Ground and Incline Walking Using a Rate Gyroscope , 2010, Sensors.

[8]  Kamiar Aminian,et al.  Gait and Foot Clearance Parameters Obtained Using Shoe-Worn Inertial Sensors in a Large-Population Sample of Older Adults , 2013, Sensors.

[9]  Angelo M. Sabatini,et al.  Online Decoding of Hidden Markov Models for Gait Event Detection Using Foot-Mounted Gyroscopes , 2014, IEEE Journal of Biomedical and Health Informatics.

[10]  Elissa D. Ledoux Inertial Sensing for Gait Event Detection and Transfemoral Prosthesis Control Strategy , 2018, IEEE Transactions on Biomedical Engineering.

[11]  Deepak Joshi,et al.  Terrain and Direction Classification of Locomotion Transitions Using Neuromuscular and Mechanical Input , 2015, Annals of Biomedical Engineering.

[12]  Deok-Hwan Kim,et al.  Real-time gait subphase detection using an EMG signal graph matching (ESGM) algorithm based on EMG signals , 2017, Expert Syst. Appl..

[13]  Shiwei Mo,et al.  Accuracy of three methods in gait event detection during overground running. , 2018, Gait & posture.

[14]  Zaccaria Del Prete,et al.  Measuring Gait Quality in Parkinson’s Disease through Real-Time Gait Phase Recognition , 2018, Sensors.

[15]  Simona Crea,et al.  Time-Discrete Vibrotactile Feedback Contributes to Improved Gait Symmetry in Patients With Lower Limb Amputations: Case Series , 2017, Physical therapy.

[16]  R Williamson,et al.  Gait event detection for FES using accelerometers and supervised machine learning. , 2000, IEEE transactions on rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society.

[17]  Marcus Fraga Vieira,et al.  Effects of inclined surfaces on gait variability and stability in unilateral lower limb amputees , 2019, Medical & Biological Engineering & Computing.

[18]  Roger N Gunn,et al.  Gait in Mild Alzheimer's Disease: Feasibility of Multi-Center Measurement in the Clinic and Home with Body-Worn Sensors: A Pilot Study. , 2018, Journal of Alzheimer's disease : JAD.

[19]  Samuel J. Reinfelder,et al.  Wearable sensors objectively measure gait parameters in Parkinson’s disease , 2017, PloS one.

[20]  Brook Galna,et al.  Obstacle crossing in people with Parkinson's disease: foot clearance and spatiotemporal deficits. , 2010, Human movement science.

[21]  Paul J. M. Havinga,et al.  A Survey of Online Activity Recognition Using Mobile Phones , 2015, Sensors.

[22]  Deepak Joshi,et al.  An Affordable Insole-Sensor-Based Trans-Femoral Prosthesis for Normal Gait , 2018, Sensors.

[23]  Eduardo Palermo,et al.  Gait Partitioning Methods: A Systematic Review , 2016, Sensors.

[24]  Lynn Rochester,et al.  Gait and cognition: Mapping the global and discrete relationships in ageing and neurodegenerative disease , 2016, Neuroscience & Biobehavioral Reviews.

[25]  He Huang,et al.  A Strategy for Identifying Locomotion Modes Using Surface Electromyography , 2009, IEEE Transactions on Biomedical Engineering.

[26]  Kara K. Patterson,et al.  Evaluation of gait symmetry after stroke: a comparison of current methods and recommendations for standardization. , 2010, Gait & posture.

[27]  Uttama Lahiri,et al.  Design of Instrumented Shoes for Gait Characterization: A Usability Study With Healthy and Post-stroke Hemiplegic Individuals , 2018, Front. Neurosci..

[28]  J. Allum,et al.  Gait event detection using linear accelerometers or angular velocity transducers in able-bodied and spinal-cord injured individuals. , 2006, Gait & posture.

[29]  A. A. Dehghani-Sanij,et al.  A Real-Time Gait Event Detection for Lower Limb Prosthesis Control and Evaluation , 2017, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[30]  Robert D. Gregg,et al.  A Haptic Feedback System for Phase-Based Sensory Restoration in Above-Knee Prosthetic Leg Users , 2016, IEEE Transactions on Haptics.

[31]  Cheong Boon Soh,et al.  Assessment of Foot Trajectory for Human Gait Phase Detection Using Wireless Ultrasonic Sensor Network , 2016, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[32]  Suzanne B. Finucane,et al.  Online adaptive neural control of a robotic lower limb prosthesis , 2018, Journal of neural engineering.

[33]  Tianjian Ji,et al.  FREQUENCY AND VELOCITY OF PEOPLE WALKING , 2005 .

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

[35]  Todd A. Kuiken,et al.  The Effects of Electrode Size and Orientation on the Sensitivity of Myoelectric Pattern Recognition Systems to Electrode Shift , 2011, IEEE Transactions on Biomedical Engineering.

[36]  L. Göeken,et al.  Factors related to successful job reintegration of people with a lower limb amputation. , 2001, Archives of physical medicine and rehabilitation.

[37]  M.R. Popovic,et al.  A reliable gait phase detection system , 2001, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[38]  Edward Sazonov,et al.  Automatic Detection of Temporal Gait Parameters in Poststroke Individuals , 2011, IEEE Transactions on Information Technology in Biomedicine.

[39]  Jill M van der Meulen,et al.  Free-living and laboratory gait characteristics in patients with multiple sclerosis , 2018, PloS one.

[40]  D. Elliott,et al.  Peripheral visual cues affect minimum-foot-clearance during overground locomotion. , 2009, Gait & posture.

[41]  Deepak Joshi,et al.  A Novel Approach for Toe Off Estimation During Locomotion and Transitions on Ramps and Level Ground , 2016, IEEE Journal of Biomedical and Health Informatics.

[42]  Jacqueline S. Hebert,et al.  Maintaining stable transfemoral amputee gait on level, sloped and simulated uneven conditions in a virtual environment , 2019, Disability and rehabilitation. Assistive technology.

[43]  Joris De Schutter,et al.  Real-Time Gait Event Detection Based on Kinematic Data Coupled to a Biomechanical Model , 2017, Sensors.

[44]  Uriel Martinez-Hernandez,et al.  A Practical Gait Feedback Method Based on Wearable Inertial Sensors for a Drop Foot Assistance Device , 2019, IEEE Sensors Journal.

[45]  Kamiar Aminian,et al.  An Accurate Wearable Foot Clearance Estimation System: Toward a Real-Time Measurement System , 2017, IEEE Sensors Journal.

[46]  Nicholas Wickström,et al.  A Symbol-Based Approach to Gait Analysis From Acceleration Signals: Identification and Detection of Gait Events and a New Measure of Gait Symmetry , 2010, IEEE Transactions on Information Technology in Biomedicine.

[47]  Alan Godfrey,et al.  Detecting free-living steps and walking bouts: validating an algorithm for macro gait analysis , 2017, Physiological measurement.

[48]  R. Lipton,et al.  Quantitative gait markers and incident fall risk in older adults. , 2009, The journals of gerontology. Series A, Biological sciences and medical sciences.

[49]  Adrian D. C. Chan,et al.  Surface electromyographic signals using a dry electrode , 2011, 2010 IEEE International Workshop on Medical Measurements and Applications.

[50]  Cristina P. Santos,et al.  Gait Event Detection in Controlled and Real-Life Situations: Repeated Measures From Healthy Subjects , 2018, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[51]  B. Galna,et al.  Free-living gait characteristics in ageing and Parkinson’s disease: impact of environment and ambulatory bout length , 2016, Journal of NeuroEngineering and Rehabilitation.

[52]  Hafiz Farhan Maqbool,et al.  Heuristic Real-Time Detection of Temporal Gait Events for Lower Limb Amputees , 2019, IEEE Sensors Journal.

[53]  Deepak Joshi,et al.  A Force Myography-Based System for Gait Event Detection in Overground and Ramp Walking , 2018, IEEE Transactions on Instrumentation and Measurement.

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

[55]  Deepak Joshi,et al.  High energy spectrogram with integrated prior knowledge for EMG-based locomotion classification. , 2015, Medical engineering & physics.

[56]  J. R. Landis,et al.  The measurement of observer agreement for categorical data. , 1977, Biometrics.

[57]  T. Lu,et al.  Biomechanics of human movement and its clinical applications , 2012, The Kaohsiung journal of medical sciences.

[58]  Shiv Dutt Joshi,et al.  Force Myography Based Novel Strategy for Locomotion Classification , 2018, IEEE Transactions on Human-Machine Systems.