Accuracy of Wearable Sensors for Estimating Joint Reactions

2017 ◽  
Vol 12 (4) ◽  
Author(s):  
Ryan S. McGinnis ◽  
Jessandra Hough ◽  
Noel C. Perkins
Keyword(s):  
Degrees Of Freedom ◽  
Wearable Sensors ◽  
Three Dimensional ◽  
Correlation Coefficients ◽  
Human Motion ◽  
Load Cell ◽  
Great Promise ◽  
Human Motion Analysis ◽  
Double Pendulum ◽  
Inverse Dynamic

Miniature wireless inertial measurement units (IMUs) hold great promise for measuring and analyzing multibody system dynamics. This relatively inexpensive technology enables noninvasive motion tracking in broad applications, including human motion analysis. This paper advances the use of an array of IMUs to estimate the joint reactions (forces and moments) in multibody systems via inverse dynamic modeling. In particular, this paper reports a benchmark experiment on a double-pendulum that reveals the accuracy of IMU-informed estimates of joint reactions. The estimated reactions are compared to those measured by high-precision miniature (6 degrees-of-freedom) load cells. Results from ten trials demonstrate that IMU-informed estimates of the three-dimensional reaction forces remain within 5.0% RMS of the load cell measurements and with correlation coefficients greater than 0.95 on average. Similarly, the IMU-informed estimates of the three-dimensional reaction moments remain within 5.9% RMS of the load cell measurements and with correlation coefficients greater than 0.88 on average. The sensitivity of these estimates to mass center location is discussed. Looking ahead, this benchmarking study supports the promising and broad use of this technology for estimating joint reactions in human motion applications.

Benchmarking the Accuracy of Inertial Measurement Units for Estimating Joint Reactions

2013 ◽  
Author(s):  
Ryan S. McGinnis ◽  
Jessandra Hough ◽  
N. C. Perkins
Keyword(s):  
Three Dimensional ◽  
Correlation Coefficients ◽  
Human Motion ◽  
Load Cell ◽  
Great Promise ◽  
Human Motion Analysis ◽  
Double Pendulum ◽  
Inertial Measurement Units ◽  
Inertial Measurement ◽  
Measurement Units

Newly developed miniature wireless inertial measurement units (IMUs) hold great promise for measuring and analyzing multibody system dynamics. This relatively inexpensive technology enables non-invasive motion tracking in broad applications, including human motion analysis. The second part of this two-part paper advances the use of an array of IMUs to estimate the joint reactions (forces and moments) in multibody systems via inverse dynamic modeling. In particular, this paper reports a benchmark experiment on a double-pendulum that reveals the accuracy of IMU-informed estimates of joint reactions. The estimated reactions are compared to those measured by high precision miniature (6 dof) load cells. Results from ten trials demonstrate that IMU-informed estimates of the three dimensional reaction forces remain within 5.0% RMS of the load cell measurements and with correlation coefficients greater than 0.95 on average. Similarly, the IMU-informed estimates of the three dimensional reaction moments remain within 5.9% RMS of the load cell measurements and with correlation coefficients greater than 0.88 on average. The sensitivity of these estimates to mass center location is discussed. Looking ahead, this benchmarking study supports the promising and broad use of this technology for estimating joint reactions in human motion applications.

scholarly journals Automatic anatomical calibration for IMU-based elbow angle measurement in disturbed magnetic fields

2017 ◽  
Vol 3 (2) ◽  
pp. 167-170 ◽  
Author(s):  
Daniel Laidig ◽  
Philipp Müller ◽  
Thomas Seel
Keyword(s):  
Motion Analysis ◽  
Degrees Of Freedom ◽  
Homogeneous Magnetic Field ◽  
Calibration Method ◽  
Angle Measurement ◽  
Human Motion ◽  
Human Motion Analysis ◽  
Indoor Environments ◽  
Sensor Orientation ◽  
Optical Motion

AbstractInertial Measurement Units (IMUs) are increasingly used for human motion analysis. However, two major challenges remain: First, one must know precisely in which orientation the sensor is attached to the respective body segment. This is commonly achieved by accurate manual placement of the sensors or by letting the subject perform tedious calibration movements. Second, standard methods for inertial motion analysis rely on a homogeneous magnetic field, which is rarely found in indoor environments. To address both challenges, we introduce an automatic calibration method for joints with two degrees of freedom such as the combined radioulnar and elbow joint. While the user performs arbitrary movements, the method automatically identifies the sensor-to-segment orientations by exploiting the kinematic constraints of the joint. Simultaneously, the method identifies and compensates the influence of magnetic disturbances on the sensor orientation quaternions and the joint angles. In experimental trials, we obtain angles that agree well with reference values from optical motion capture. We conclude that the proposed method overcomes mounting and calibration restrictions and improves measurement accuracy in indoor environments. It therefore improves the practical usability of IMUs for many medical applications.

Analysis of Hand-Arm Coordinate Motion on Constraint Tasks

1991 ◽  
Vol 3 (6) ◽  
pp. 497-505
Author(s):  
Shigeki Sugano ◽  
◽  
Hideyo Namimoto ◽  
Ichiro Kato
Keyword(s):  
Control Strategy ◽  
Force Control ◽  
Degrees Of Freedom ◽  
Control Mechanism ◽  
Human Motion ◽  
Degree Of Freedom ◽  
Human Hand ◽  
Human Motion Analysis ◽  
Manipulator Control ◽  
Arm Coordination

This research was conducted to study the control strategy of manipulator based on clarifying the force control mechanism of the human hand-arm by analyzing human constraint tasks with respect to biomechanism. In this paper; we describe an investigation of hand-arm function share. In addition, we apply hand-arm coordination to manipulator control using experimental results of analyzing the human tasks of moving bead balls on a shaft, which is an example of a constraint task with one degree of freedom (d.o.f.). In the human motion analysis, 6 axes of force on the task object are measured and compared in the case of constraining the hands degree of freedom and making hand free as well as in the case of with or without forced displacement along the translational direction during motion. As a result, we found that human work was performed smoothly through absorption of rotational force using hand d.o.f. and translational force using arm d.o.f. Also, it was found that there are the direction of motion and the posture easily absorbable translational force. Finally, we propose to apply the human hand-arm coordination compliance control strategy setting translational compliance by arms and rotational compliance by hands, to manipulator with more than 7 degrees of freedom. Thus, the setting of optional compliance applicable to circumstance and the resulting force control due to this become possible.

QUANTIFICATION OF THREE-DIMENSIONAL MOVEMENT OF SKIN MARKERS RELATIVE TO THE UNDERLYING BONES DURING FUNCTIONAL ACTIVITIES

2009 ◽  
Vol 21 (03) ◽  
pp. 223-232 ◽  
Author(s):  
Tsung-Yuan Tsai ◽  
Tung-Wu Lu ◽  
Mei-Ying Kuo ◽  
Horng-Chaung Hsu
Keyword(s):  
Motion Analysis ◽  
Three Dimensional ◽  
Normal Subjects ◽  
Human Motion ◽  
Human Motion Analysis ◽  
Location Selection ◽  
Functional Activities ◽  
Skin Marker ◽  
Compensation Approach

Skin marker-based stereophotogrammetry has been widely used in the in vivo, noninvasive measurement of three-dimensional (3D) joint kinematics in many clinical applications. However, the measured poses of body segments are subject to errors called soft tissue artifacts (STA). No study has reported the unrestricted STA of markers on the thigh and shank in normal subjects during functional activities. The purpose of this study was to assess the 3D movement of skin markers relative to the underlying bones in normal subjects during functional activities using a noninvasive method based on the integration of 3D fluoroscopy and stereophotogrammetry. Generally, thigh markers had greater STA than shank ones and the STA of the markers were in nonlinear relationships with knee flexion angles. The STA of a marker also appeared to vary among subjects and were affected by activities. This suggests that correction of STA in human motion analysis may have to consider the multijoint nature of functional activities such as using a global compensation approach with individual anthropometric data. The results of the current study may be helpful for establishing guidelines of marker location selection and for developing STA compensation methods in human motion analysis.

scholarly journals Three Dimensional Monocular Human Motion Analysis in End-Effector Space

2009 ◽  
pp. 235-248 ◽  
Author(s):  
Søren Hauberg ◽  
Jerome Lapuyade ◽  
Morten Engell-Nørregård ◽  
Kenny Erleben ◽  
Kim Steenstrup Pedersen
Keyword(s):  
Motion Analysis ◽  
Three Dimensional ◽  
Human Motion ◽  
Human Motion Analysis ◽  
End Effector

Three-Dimensional Coordinate Data Processing in Human Motion Analysis

1979 ◽  
Vol 101 (4) ◽  
pp. 279-283 ◽  
Author(s):  
T. P. Andriacchi ◽  
S. J. Hampton ◽  
A. B. Schultz ◽  
J. O. Galante
Keyword(s):  
Data Processing ◽  
Gait Analysis ◽  
Three Dimensional ◽  
Human Motion ◽  
Human Gait ◽  
Human Motion Analysis ◽  
Coordinate Processing ◽  
Three Dimensional Coordinate ◽  
Human Gait Analysis ◽  
Coordinate Data

A method for three-dimensional coordinate processing of human motion is presented. The method is well suited for use with opto-electronic data acquisition equipment. A resolution of one part in 500 was achieved over a viewing field of 2.4 m. This resolution was found to be adequate for human gait analysis studies.

scholarly journals Analysis Choices Impact Movement Evaluation: A Multi-Aspect Inferential Method Applied to Kinematic Curves of Vertical Hops in Knee-Injured and Asymptomatic Persons

2021 ◽  
Vol 9 ◽  
Author(s):  
Johan Strandberg ◽  
Alessia Pini ◽  
Charlotte K. Häger ◽  
Lina Schelin
Keyword(s):  
Statistical Methods ◽  
Functional Data ◽  
Cruciate Ligament ◽  
Knee Injuries ◽  
Three Dimensional ◽  
Human Motion ◽  
Outcome Variable ◽  
Group Differences ◽  
Human Motion Analysis ◽  
Significant Group

Three-dimensional human motion analysis provides in-depth understanding in order to optimize sports performance or rehabilitation following disease or injury. Recent developments of statistical methods for functional data allow for novel ways to analyze often complex biomechanical data. Even so, for such methods as well as for traditional well-established statistical methods, the interpretations of the results may be influenced by analysis choices made prior to the analysis. We evaluated the consequences of three such choices when comparing one-leg vertical hop (OLVH) performance in individuals who had ruptured their anterior cruciate ligament (ACL), to that of asymptomatic controls, and also athletes. Kinematic data were analyzed using a statistical approach for functional data, targeting entire curve data. This was done not only for one joint at a time but also for multiple lower limb joints and movement planes simultaneously using a multi-aspect methodology, testing for group differences while also accounting for covariates. We present the results of when an individual representative curve out of three available was either: (1) a mean curve (Mean), (2) a curve from the highest hop (Max), or (3) a curve describing the variability (Var), as a representation of performance stability. We also evaluated choice of sample leg comparison; e.g., ACL-injured leg compared to either the dominant or non-dominant leg of asymptomatic groups. Finally, we explored potential outcome effects of different combinations of included joints. There were slightly more pronounced group differences when using Mean compared to Max, while the specifics of the observed differences depended on the outcome variable. For Var there were less significant group differences. Generally, there were more disparities throughout the hop movement when comparing the injured leg to the dominant leg of controls, resulting in e.g., group differences for trunk and ankle kinematics, for both Mean and Max. When the injured leg was instead compared to the non-dominant leg of controls, there were trunk, hip and knee joint differences. For a more stringent comparison, we suggest considering to compare the injured leg to the non-dominant leg. Finally, the multiple-joint analyses were coherent with the single-joint analyses. The direct effects of analysis choices can be explored interactively by the reader in the Supplementary Material. To summarize, the choices definitively have an impact on the interpretation of a hop test results commonly used in rehabilitation following knee injuries. We therefore strongly recommend well-documented methodological analysis choices with regards to comparisons and representative values of the measures of interests.

Estimation of Muscle Response Using Three-Dimensional Musculoskeletal Models Before Impact Situation: A Simulation Study

2010 ◽  
Vol 132 (12) ◽  
Author(s):  
Tae Soo Bae ◽  
Peter Loan ◽  
Kuiwon Choi ◽  
Daehie Hong ◽  
Mu Seong Mun
Keyword(s):  
Degrees Of Freedom ◽  
Motion Tracking ◽  
Tracking System ◽  
Three Dimensional ◽  
Dynamic Simulations ◽  
Inverse Dynamic ◽  
Low Speed ◽  
Car Crash ◽  
Musculoskeletal Models ◽  
Ankle Joints

When car crash experiments are performed using cadavers or dummies, the active muscles’ reaction on crash situations cannot be observed. The aim of this study is to estimate muscles’ response of the major muscle groups using three-dimensional musculoskeletal model by dynamic simulations of low-speed sled-impact. The three-dimensional musculoskeletal models of eight subjects were developed, including 241 degrees of freedom and 86 muscles. The muscle parameters considering limb lengths and the force-generating properties of the muscles were redefined by optimization to fit for each subject. Kinematic data and external forces measured by motion tracking system and dynamometer were then input as boundary conditions. Through a least-squares optimization algorithm, active muscles’ responses were calculated during inverse dynamic analysis tracking the motion of each subject. Electromyography for major muscles at elbow, knee, and ankle joints was measured to validate each model. For low-speed sled-impact crash, experiment and simulation with optimized and unoptimized muscle parameters were performed at 9.4 m/h and 10 m/h and muscle activities were compared among them. The muscle activities with optimized parameters were closer to experimental measurements than the results without optimization. In addition, the extensor muscle activities at knee, ankle, and elbow joint were found considerably at impact time, unlike previous studies using cadaver or dummies. This study demonstrated the need to optimize the muscle parameters to predict impact situation correctly in computational studies using musculoskeletal models. And to improve accuracy of analysis for car crash injury using humanlike dummies, muscle reflex function, major extensor muscles’ response at elbow, knee, and ankle joints, should be considered.

Sign in / Sign up

Export Citation Format

Share Document