Validation of a Novel Device for the Knee Monitoring of Orthopaedic Patients

Fast-track surgery is becoming increasingly popular, whereas the monitoring of postoperative rehabilitation remains a matter of considerable debate. The aim of this study was to validate a newly developed wearable system intended to monitor knee function and mobility. A sensor system with a nine-degree-of-freedom (DOF) inertial measurement unit (IMU) was developed. Thirteen healthy volunteers performed five 10-meter walking trials with simultaneous sensor and motion capture data collection. The obtained kinematic waveforms were analysed using root mean square error (RMSE) and correlation coefficient (CC) calculations. The Bland–Altman method was used for the agreement of discrete parameters consisting of peak knee angles between systems. To test the reliability, 10 other subjects with sensors walked a track of 10 metres on two consecutive days. The Pearson CC was excellent for the walking data set between both systems (r = 0.96) and very good (r = 0.95) within the sensor system. The RMSE during walking was 5.17° between systems and 6.82° within sensor measurements. No significant differences were detected between the mean values observed, except for the extension angle during the stance phase (E1). Similar results were obtained for the repeatability test. Intra-class correlation coefficients (ICCs) between systems were excellent for the flexion angle during the swing phase (F1); good for the flexion angle during the stance phase (F2) and the re-extension angle, which was calculated by subtracting the extension angle at swing phase (E2) from F2; and moderate for the extension angle during the stance phase (E1), E2 and the range of motion (ROM). ICCs within the sensor measurements were good for the ROM, F2 and re-extension, and moderate for F1, E1 and E2. The study shows that the novel sensor system can record sagittal knee kinematics during walking in healthy subjects comparable to those of a motion capture system.

[1]  Kun-Hui Chen,et al.  Wearable Sensor-Based Rehabilitation Exercise Assessment for Knee Osteoarthritis , 2015, Sensors.

[2]  Karl M Newell,et al.  Intra-individual gait patterns across different time-scales as revealed by means of a supervised learning model using kernel-based discriminant regression , 2017, PloS one.

[3]  F. Awiszus,et al.  Funktionelle Veränderungen des Quadriceps Femoris Muskels bei Patienten mit Varusgonarthrose , 2000, Zeitschrift für Rheumatologie.

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

[5]  Brian Caulfield,et al.  Rehabilitation exercise assessment using inertial sensors: a cross-sectional analytical study , 2014, Journal of NeuroEngineering and Rehabilitation.

[6]  Matjaz B. Juric,et al.  Inertial Sensor-Based Gait Recognition: A Review , 2015, Sensors.

[7]  William R Taylor,et al.  The SCoRE residual: a quality index to assess the accuracy of joint estimations. , 2011, Journal of biomechanics.

[8]  Yunus Msayib,et al.  An Intelligent Remote Monitoring System for Total Knee Arthroplasty Patients , 2017, Journal of Medical Systems.

[9]  F. Vogenberg,et al.  Healthcare Trends for 2018. , 2018, American health & drug benefits.

[10]  Kun-Hui Chen,et al.  Data Collection and Analysis Using Wearable Sensors for Monitoring Knee Range of Motion after Total Knee Arthroplasty , 2017, Sensors.

[11]  M. Nozaki,et al.  Comparison of quantitative evaluation between cutaneous and transosseous inertial sensors in anterior cruciate ligament deficient knee: A cadaveric study. , 2017, Journal of orthopaedic science : official journal of the Japanese Orthopaedic Association.

[12]  Michael A. Mont,et al.  The Role of Virtual Rehabilitation in Total and Unicompartmental Knee Arthroplasty , 2018, The Journal of Knee Surgery.

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

[14]  Michael Marschollek,et al.  Clinical Evaluation of a Mobile Sensor-Based Gait Analysis Method for Outcome Measurement after Knee Arthroplasty , 2014, Sensors.

[15]  Ryo Tanaka,et al.  Validity of time series kinematical data as measured by a markerless motion capture system on a flatland for gait assessment. , 2018, Journal of biomechanics.

[16]  L. Miller,et al.  Quality of Life in Patients with Knee Osteoarthritis: A Commentary on Nonsurgical and Surgical Treatments , 2013, The open orthopaedics journal.

[17]  Benno M. Nigg,et al.  Daily changes of individual gait patterns identified by means of support vector machines. , 2016, Gait & posture.

[18]  J. G. C. Júnior,et al.  Qualidade de vida após artroplastia total do joelho: revisão sistemática , 2014, Revista Científica Hospital Santa Izabel.

[19]  Corina Nüesch,et al.  Measuring joint kinematics of treadmill walking and running: Comparison between an inertial sensor based system and a camera-based system. , 2017, Journal of biomechanics.

[20]  William R Taylor,et al.  A survey of formal methods for determining functional joint axes. , 2007, Journal of biomechanics.

[21]  Moataz Eltoukhy,et al.  Improved kinect-based spatiotemporal and kinematic treadmill gait assessment. , 2017, Gait & posture.

[22]  M O Heller,et al.  Effective marker placement for functional identification of the centre of rotation at the hip. , 2012, Gait & posture.

[23]  Björn Eskofier,et al.  Estimation of the Knee Flexion-Extension Angle During Dynamic Sport Motions Using Body-worn Inertial Sensors , 2013, BODYNETS.

[24]  M. Hirschmann,et al.  Fast track and outpatient surgery in total knee arthroplasty: beneficial for patients, doctors and hospitals , 2017, Knee Surgery, Sports Traumatology, Arthroscopy.

[25]  A. Saxena,et al.  Intermediate and long-term quality of life after total knee replacement: a systematic review and meta-analysis. , 2015, The Journal of bone and joint surgery. American volume.

[26]  M. Matos,et al.  Quality of life after total knee arthroplasty: systematic review☆☆☆ , 2014, Revista brasileira de ortopedia.

[27]  K. Saleh,et al.  Outpatient Total Knee Arthroplasty: Are We There Yet? (Part 1). , 2018, The Orthopedic clinics of North America.

[28]  Antonio I Cuesta-Vargas,et al.  The use of inertial sensors system for human motion analysis , 2010, Physical therapy reviews : PTR.

[29]  M O Heller,et al.  Repeatability and reproducibility of OSSCA, a functional approach for assessing the kinematics of the lower limb. , 2010, Gait & posture.

[30]  Diana Hodgins,et al.  Inertial sensor-based knee flexion/extension angle estimation. , 2009, Journal of biomechanics.

[31]  Michael Marschollek,et al.  Development and clinical validation of an unobtrusive ambulatory knee function monitoring system with inertial 9DoF sensors , 2012, 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[32]  S A A N Bolink,et al.  Patient-reported outcome measures versus inertial performance-based outcome measures: A prospective study in patients undergoing primary total knee arthroplasty. , 2015, The Knee.

[33]  I. Heyligers,et al.  Physical activity after outpatient surgery and enhanced recovery for total knee arthroplasty , 2017, Knee Surgery, Sports Traumatology, Arthroscopy.