skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.


Title: A Comparison of Inertial Measurement Unit and Motion Capture Measurements of Tibiofemoral Kinematics during Simulated Pivot Landings
Injuries are often associated with rapid body segment movements. We compared Certus motion capture and APDM inertial measurement unit (IMU) measurements of tibiofemoral angle and angular velocity changes during simulated pivot landings (i.e., ~70 ms peak) of nine cadaver knees dissected free of skin, subcutaneous fat, and muscle. Data from a total of 852 trials were compared using the Bland–Altman limits of agreement (LoAs): the Certus system was considered the gold standard measure for the angle change measurements, whereas the IMU was considered the gold standard for angular velocity changes. The results show that, although the mean peak IMU knee joint angle changes were slightly underestimated (2.1° for flexion, 0.2° for internal rotation, and 3.0° for valgus), the LoAs were large, ranging from 35.9% to 49.8%. In the case of the angular velocity changes, Certus had acceptable accuracy in the sagittal plane, with LoAs of ±54.9°/s and ±32.5°/s for the tibia and femur. For these rapid motions, we conclude that, even in the absence of soft tissues, the IMUs could not reliably measure these peak 3D knee angle changes; Certus measurements of peak tibiofemoral angular velocity changes depended on both the magnitude of the velocity and the plane of measurement.  more » « less
Award ID(s):
2003434
PAR ID:
10422325
Author(s) / Creator(s):
; ; ; ; ;
Date Published:
Journal Name:
Sensors
Volume:
22
Issue:
12
ISSN:
1424-8220
Page Range / eLocation ID:
4433
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. The ability to accurately measure tibiofemoral angles during various dynamic activities is of clinical interest. The purpose of this study was to determine if inertial measurement units (IMUs) can provide accurate and reliable angle estimates during dynamic actions. A tuned quaternion conversion (TQC) method tuned to dynamics actions was used to calculate Euler angles based on IMU data, and these calculated angles were compared to a motion capture system (our “gold” standard) and a commercially available sensor fusion algorithm. Nine healthy athletes were instrumented with APDM Opal IMUs and asked to perform nine dynamic actions; five participants were used in training the parameters of the TQC method, with the remaining four being used to test validity. Accuracy was based on the root mean square error (RMSE) and reliability was based on the Bland–Altman limits of agreement (LoA). Improvement across all three orthogonal angles was observed as the TQC method was able to more accurately (lower RMSE) and more reliably (smaller LoA) estimate an angle than the commercially available algorithm. No significant difference was observed between the TQC method and the motion capture system in any of the three angles (p < 0.05). It may be feasible to use this method to track tibiofemoral angles with higher accuracy and reliability than the commercially available sensor fusion algorithm. 
    more » « less
  2. Tibiofemoral compression forces present during locomotion can result in high stress and risk damage to the knee. Powered assistance using a knee exoskeleton may reduce the knee load by reducing the work required by the muscles. However, the exact effect of assistance on the tibiofemoral force is unknown. The goal of this study was to investigate the effect of knee extension assistance during the early stance phase on the tibiofemoral force. Nine able-bodied adults walked on an inclined treadmill with a bilateral knee exoskeleton with assistance and with no assistance. Using an EMG-informed neuromusculoskeletal model, muscle forces were estimated, then utilized to estimate the tibiofemoral contact force. Results showed a 28% reduction in the knee moment, which resulted in approximately a 15% decrease in knee extensor muscle activation and a 20% reduction in subsequent muscle force, leading to a significant 10% reduction in peak and 9% reduction in average tibiofemoral contact force during the early stance phase (p < 0.05). The results indicate the tibiofemoral force is highly dependent on the knee kinetics and quadricep muscle activation due to their influence on knee extensor muscle forces, the primary contributor to the knee load. 
    more » « less
  3. Inertial kinetics and kinematics have substantial influences on human biomechanical function. A new algorithm for Inertial Measurement Unit (IMU)-based motion tracking is presented in this work. The primary aims of this paper are to combine recent developments in improved biosensor technology with mainstream motion-tracking hardware to measure the overall performance of human movement based on joint axis-angle representations of limb rotation. This work describes an alternative approach to representing three-dimensional rotations using a normalized vector around which an identified joint angle defines the overall rotation, rather than a traditional Euler angle approach. Furthermore, IMUs allow for the direct measurement of joint angular velocities, offering the opportunity to increase the accuracy of instantaneous axis of rotation estimations. Although the axis-angle representation requires vector quotient algebra (quaternions) to define rotation, this approach may be preferred for many graphics, vision, and virtual reality software applications. The analytical method was validated with laboratory data gathered from an infant dummy leg’s flexion and extension knee movements and applied to a living subject’s upper limb movement. The results showed that the novel approach could reasonably handle a simple case and provide a detailed analysis of axis-angle migration. The described algorithm could play a notable role in the biomechanical analysis of human joints and offers a harbinger of IMU-based biosensors that may detect pathological patterns of joint disease and injury. 
    more » « less
  4. null (Ed.)
    The objective of this study was to test the feasibility of using a pair of wearable inertial measurement unit (IMU) sensors to accurately capture dynamic joint motion data during simulated occupational conditions. Eleven subjects (5 males and 6 females) performed repetitive neck, low-back, and shoulder motions simulating low- and high-difficulty occupational tasks in a laboratory setting. Kinematics for each of the 3 joints were measured via IMU sensors in addition to a “gold standard” passivemarker optical motion capture system. The IMU accuracy was benchmarked relative to the optical motion capture system, and IMU sensitivity to low- and high-difficulty tasks was evaluated. The accuracy of the IMU sensors was found to be very good on average, but significant positional drift was observed in some trials. In addition, IMU measurements were shown to be sensitive to differences in task difficulty in all 3 joints (P < .05). These results demonstrate the feasibility for using wearable IMU sensors to capture kinematic exposures as potential indicators of occupational injury risk. Velocities and accelerations demonstrate the most potential for developing risk metrics since they are sensitive to task difficulty and less sensitive to drift than rotational position measurements. 
    more » « less
  5. Abstract We compared the ability of seven machine learning algorithms to use wearable inertial measurement unit (IMU) data to identify the severe knee loading cycles known to induce microdamage associated with anterior cruciate ligament rupture. Sixteen cadaveric knee specimens, dissected free of skin and muscle, were mounted in a rig simulating standardized jump landings. One IMU was located above and the other below the knee, the applied three-dimensional action and reaction loads were measured via six-axis load cells, and the three-dimensional knee kinematics were also recorded by a laboratory motion capture system. Machine learning algorithms were used to predict the knee moments and the tibial and femur vertical forces; 13 knees were utilized for training each model, while three were used for testing its accuracy (i.e., normalized root-mean-square error) and reliability (Bland–Altman limits of agreement). The results showed the models predicted force and knee moment values with acceptable levels of error and, although several models exhibited some form of bias, acceptable reliability. Further research will be needed to determine whether these types of models can be modified to attenuate the inevitable in vivo soft tissue motion artifact associated with highly dynamic activities like jump landings. 
    more » « less