Validation of a Device to Measure Knee Joint Angles for a Dynamic Movement

Abstract

Participation in sports has risen in the United States over the last few years, increasing the risk of injuries such as tears to the anterior cruciate ligament (ACL) in the knee. Previous studies have shown a correlation between knee kinematics when landing from a jump and this injury. The purpose of this study was to validate the ability of a commercially available inertial measurement units (IMUs) to accurately measure knee joint angles during a dynamic movement. Eight healthy subjects participated in the study. Validation was performed by comparing the angles measured by the wearable device to those obtained through the gold standard motion capture system when landing from a jump. Root mean square, linear regression analysis, and Bland–Altman plots were performed/constructed. The mean difference between the wearable device and the motion capture data was 8.4° (flexion/extension), 4.9° (ab/adduction), and 3.9° (rotation). In addition, the device was more accurate at smaller knee angles. In our study, a commercially available wearable IMU was able to perform fairly well under certain conditions and was less accurate in other conditions.

Validity of a New 3-D Motion Analysis Tool for the Assessment of Knee, Hip and Spine Joint Angles during the Single Leg Squat

“…Although these findings for the knee are comparable to our study, differences in hip findings could be due to the different sensor positions and performance tasks [17]. Another study compared IMU with OptiTrack measuring knee motion during a dynamic task as in our study [4]. They showed an error of measurement of 8 • for flexion/extension (0.5 • in our study) and poor correlation (Pearson's R = 0.58 against our Pearson's R = 0.94).…”

“…This study shows that easily accessible technology is likely to enter the market for a broad audience of professionals from different fields. The recent research interest from orthopedic and neurologic rehabilitation specialists in this type of technology shows that there is a loud call for quantification of many parameters in their specific patient populations [ 2 , 4 , 9 , 17 , 19 , 20 , 21 , 31 , 34 , 45 ]. Every movement related health problem would thus likely have its own clinical relevant movement parameters.…”

“…Kinematic parameters like the range of motion (ROM), velocity and acceleration are used to quantify so-called quality of movement [1]. Quality of movement is associated with injury risk in athletes, and is evaluated in clinical practice to determine exercise progression and assist in return to play decision making after injury [1,3,4]. In sports involving running, cutting and jumping, decreased spine, hip and knee flexion have been linked to the development of patellofemoral pain and increased strain of the anterior cruciate ligament (ACL) [5][6][7].…”

“…Movement quality is then often judged visually, thereby lacking quantitative data. A huge step forward in movement quality assessment would then be to track 3D movement outside the laboratory and in clinical settings with easy-to-use, low cost and time efficient systems [4]. Obtaining larger data sets is then made possible by the multi-site use of this technology [2].…”

“…A previous review on the reliability of motion capture systems reported the highest reliability for hip and knee sagittal and frontal plane measurements while it is lowest for the transverse plane measurements [ 16 ]. Reliability of wearable active sensor systems is moderate to excellent when compared to optical tracking systems with sagittal and frontal hip and knee measurement error between sagittal 8° and 1° [ 4 , 17 , 18 ]. Active sensors recently proved to be useful and reliable in the assessment of squatting, jumping and walking in patients after ACL reconstruction [ 19 ].…”