An Intelligent Recovery Progress Evaluation System for ACL Reconstructed Subjects Using Integrated 3-D Kinematics and EMG Features

An intelligent recovery evaluation system is presented for objective assessment and performance monitoring of anterior cruciate ligament reconstructed (ACL-R) subjects. The system acquires 3-D kinematics of tibiofemoral joint and electromyography (EMG) data from surrounding muscles during various ambulatory and balance testing activities through wireless body-mounted inertial and EMG sensors, respectively. An integrated feature set is generated based on different features extracted from data collected for each activity. The fuzzy clustering and adaptive neuro-fuzzy inference techniques are applied to these integrated feature sets in order to provide different recovery progress assessment indicators (e.g., current stage of recovery, percentage of recovery progress as compared to healthy group, etc.) for ACL-R subjects. The system was trained and tested on data collected from a group of healthy and ACL-R subjects. For recovery stage identification, the average testing accuracy of the system was found above 95% (95-99%) for ambulatory activities and above 80% (80-84%) for balance testing activities. The overall recovery evaluation performed by the proposed system was found consistent with the assessment made by the physiotherapists using standard subjective/objective scores. The validated system can potentially be used as a decision supporting tool by physiatrists, physiotherapists, and clinicians for quantitative rehabilitation analysis of ACL-R subjects in conjunction with the existing recovery monitoring systems.

[1]  A. C. Rencher.  Methods of multivariate analysis , 1995 .

[2]  D. Saris,et al.  Functional assessment and muscle strength before and after reconstruction of chronic anterior cruciate ligament lesions. , 2007, Arthroscopy : the journal of arthroscopic & related surgery : official publication of the Arthroscopy Association of North America and the International Arthroscopy Association.

[3]  Kate E Webster,et al.  Alterations in joint kinematics during walking following hamstring and patellar tendon anterior cruciate ligament reconstruction surgery. , 2011, Clinical biomechanics.

[4]  Mehran Jahed,et al.  A Neuro–Fuzzy Inference System for sEMG-Based Identification of Hand Motion Commands , 2011, IEEE Transactions on Industrial Electronics.

[5]  S. Simon.  Gait Analysis, Normal and Pathological Function. , 1993 .

[6]  W. Marsden.  I and J , 2012 .

[7]  Thompson Sarkodie-Gyan,et al.  Automatic classification of pathological gait patterns using ground reaction forces and machine learning algorithms , 2011, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[8]  James C. Bezdek,et al.  Pattern Recognition with Fuzzy Objective Function Algorithms , 1981, Advanced Applications in Pattern Recognition.

[9]  James J. Irrgang,et al.  Current Status of Measuring Clinical Outcomes After Anterior Cruciate Ligament Reconstruction: Are We Good Enough? , 2008 .

[10]  Gregory A. Brown,et al.  Treatment of Anterior Cruciate Ligament Injuries , 2016, The Journal of the American Academy of Orthopaedic Surgeons.

[11]  D. Theisen,et al.  Muscle strength and hop performance criteria prior to return to sports after ACL reconstruction , 2011, Knee Surgery, Sports Traumatology, Arthroscopy.

[12]  D. Massart,et al.  The Mahalanobis distance , 2000 .

[13]  Stefano Zaffagnini,et al.  Quantitative assessment of pivot-shift using inertial sensors , 2012, Knee Surgery, Sports Traumatology, Arthroscopy.

[14]  Hassan Ghasemzadeh,et al.  A Body Sensor Network With Electromyogram and Inertial Sensors: Multimodal Interpretation of Muscular Activities , 2010, IEEE Transactions on Information Technology in Biomedicine.

[15]  Ramprasad Papannagari,et al.  In Vivo Kinematics of the Knee after Anterior Cruciate Ligament Reconstruction , 2006, The American journal of sports medicine.

[16]  H J Hill,et al.  Relationship of leg muscle strength and knee function in the early period after anterior cruciate ligament reconstruction , 2004, Scandinavian journal of medicine & science in sports.

[17]  William F. Christensen,et al.  Methods of Multivariate Analysis: Rencher/Methods , 2012 .

[18]  William Carl Mostertz.  Quantifying antalgic gait knee function using inertial sensor technology , 2008 .

[19]  Marimuthu Palaniswami,et al.  Computational Intelligence in Gait Research: A Perspective on Current Applications and Future Challenges , 2009, IEEE Transactions on Information Technology in Biomedicine.

[20]  Johannes Peltola,et al.  Activity classification using realistic data from wearable sensors , 2006, IEEE Transactions on Information Technology in Biomedicine.

[21]  Lynn Snyder-Mackler,et al.  Current concepts for anterior cruciate ligament reconstruction: a criterion-based rehabilitation progression. , 2012, The Journal of orthopaedic and sports physical therapy.

[22]  Mohamad Parnianpour,et al.  Adaptive Neuro-Fuzzy Inference System for Classification of ACL-Ruptured Knees Using Arthrometric Data , 2008, Annals of Biomedical Engineering.

[23]  Kevin R Ford,et al.  The Relationship of Hamstrings and Quadriceps Strength to Anterior Cruciate Ligament Injury in Female Athletes , 2009, Clinical journal of sport medicine : official journal of the Canadian Academy of Sport Medicine.

[24]  B. Freriks,et al.  Development of recommendations for SEMG sensors and sensor placement procedures. , 2000, Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology.

[25]  Abdulhamit Subasi,et al.  Classification of EMG signals using combined features and soft computing techniques , 2012, Appl. Soft Comput..

[26]  Nigel H. Lovell,et al.  Implementation of a real-time human movement classifier using a triaxial accelerometer for ambulatory monitoring , 2006, IEEE Transactions on Information Technology in Biomedicine.

[27]  Hartmut Witte,et al.  ISB recommendation on definitions of joint coordinate system of various joints for the reporting of human joint motion--part I: ankle, hip, and spine. International Society of Biomechanics. , 2002, Journal of biomechanics.

[28]  Gregory D. Myer,et al.  Current Concepts for Injury Prevention in Athletes After Anterior Cruciate Ligament Reconstruction , 2013, The American journal of sports medicine.

[29]  A. A. Gopalai,et al.  A Wearable Real-Time Intelligent Posture Corrective System Using Vibrotactile Feedback , 2011, IEEE/ASME Transactions on Mechatronics.

[30]  Ian T. Jolliffe,et al.  Principal Component Analysis , 2002, International Encyclopedia of Statistical Science.

[31]  Chusak Limsakul,et al.  Feature Extraction and Reduction of Wavelet Transform Coefficients for EMG Pattern Classification , 2012 .

[32]  Braden C. Fleming,et al.  Treatment of Anterior Cruciate Ligament Injuries, Part I , 2005, The American journal of sports medicine.

[33]  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.

[34]  B. Prabhakaran,et al.  Analyzing and Visualizing Jump Performance Using Wireless Body Sensors , 2012, TECS.

[35]  Thomas P Andriacchi,et al.  Differences in tibial rotation during walking in ACL reconstructed and healthy contralateral knees. , 2010, Journal of biomechanics.

[36]  Sebastian O. H. Madgwick,et al.  An efficient orientation filter for inertial and inertial / magnetic sensor arrays , 2010 .

[37]  S. M. N. Arosha Senanayake,et al.  3-D kinematics and neuromuscular signals' integration for post ACL reconstruction recovery assessment , 2013, 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[38]  M. Sugeno,et al.  An interpretation of fuzzy measures and the Choquet integral as an integral with respect to a fuzzy , 1989 .

[39]  M. Axe,et al.  The effect of insufficient quadriceps strength on gait after anterior cruciate ligament reconstruction. , 2002, Clinical biomechanics.

[40]  Kevin R Ford,et al.  Rehabilitation after anterior cruciate ligament reconstruction: criteria-based progression through the return-to-sport phase. , 2006, The Journal of orthopaedic and sports physical therapy.

[41]  Jurandir Nadal,et al.  Classification of gait kinematics of anterior cruciate ligament reconstructed subjects using principal component analysis and regressions modelling , 2012, 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[42]  Hongyin Lau,et al.  The reliability of using accelerometer and gyroscope for gait event identification on persons with dropped foot. , 2008, Gait & posture.

[43]  Vladimir Medved,et al.  Standards for Reporting EMG Data , 2000, Journal of Electromyography and Kinesiology.

[44]  L. Engebretsen,et al.  Knee osteoarthritis after anterior cruciate ligament injury: a systematic review. , 2009, The American journal of sports medicine.

[45]  N. Zheng,et al.  Alterations in three-dimensional joint kinematics of anterior cruciate ligament-deficient and -reconstructed knees during walking. , 2010, Clinical biomechanics.

[46]  Abbey C. Thomas,et al.  Lower extremity muscle strength after anterior cruciate ligament injury and reconstruction. , 2013, Journal of athletic training.

[47]  Jyh-Shing Roger Jang,et al.  ANFIS: adaptive-network-based fuzzy inference system , 1993, IEEE Trans. Syst. Man Cybern..