scholarly journals Estimation of 3D Knee Joint Angles during Cycling Using Inertial Sensors: Accuracy of a Novel Sensor-to-Segment Calibration Procedure Based on Pedaling Motion

Sensors ◽  
2019 ◽  
Vol 19 (11) ◽  
pp. 2474 ◽  
Author(s):  
Sébastien Cordillet ◽  
Nicolas Bideau ◽  
Benoit Bideau ◽  
Guillaume Nicolas
Keyword(s):  
Knee Joint ◽  
Inertial Sensor ◽  
External Rotation ◽  
Calibration Method ◽  
Calibration Procedure ◽  
Angle Measurement ◽  
Measurement Unit ◽  
Joint Angles ◽  
Calibration Methods ◽  
Flexion Extension

This paper presents a novel sensor-to-segment calibration procedure for inertial sensor-based knee joint kinematics analysis during cycling. This procedure was designed to be feasible in-field, autonomously, and without any external operator or device. It combines a static standing up posture and a pedaling task. The main goal of this study was to assess the accuracy of the new sensor-to-segment calibration method (denoted as the ‘cycling’ method) by calculating errors in terms of body-segment orientations and 3D knee joint angles using inertial measurement unit (IMU)-based and optoelectronic-based motion capture. To do so, 14 participants were evaluated during pedaling motion at a workload of 100 W, which enabled comparisons of the cycling method with conventional calibration methods commonly employed in gait analysis. The accuracy of the cycling method was comparable to that of other methods concerning the knee flexion/extension angle, and did not exceed 3.8°. However, the cycling method presented the smallest errors for knee internal/external rotation (6.65 ± 1.94°) and abduction/adduction (5.92 ± 2.85°). This study demonstrated that a calibration method based on the completion of a pedaling task combined with a standing posture significantly improved the accuracy of 3D knee joint angle measurement when applied to cycling analysis.

A Standard Testing and Calibration Procedure for Low Cost MEMS Inertial Sensors and Units

2008 ◽  
Vol 61 (2) ◽  
pp. 323-336 ◽  
Author(s):  
P. Aggarwal ◽  
Z. Syed ◽  
X. Niu ◽  
N. El-Sheimy
Keyword(s):  
Moving Objects ◽  
Inertial Sensors ◽  
Low Cost ◽  
Calibration Method ◽  
Calibration Procedure ◽  
Measurement Unit ◽  
Navigation Systems ◽  
Integrated Navigation ◽  
Mems Sensors ◽  
Calibration Methods

Navigation involves the integration of methodologies and systems for estimating the time varying position and attitude of moving objects. Inertial Navigation Systems (INS) and the Global Positioning System (GPS) are among the most widely used navigation systems. The use of cost effective MEMS based inertial sensors has made GPS/INS integrated navigation systems more affordable. However MEMS sensors suffer from various errors that have to be calibrated and compensated to get acceptable navigation results. Moreover the performance characteristics of these sensors are highly dependent on the environmental conditions such as temperature variations. Hence there is a need for the development of accurate, reliable and efficient thermal models to reduce the effect of these errors that can potentially degrade the system performance. In this paper, the Allan variance method is used to characterize the noise in the MEMS sensors. A six-position calibration method is applied to estimate the deterministic sensor errors such as bias, scale factor, and non-orthogonality. An efficient thermal variation model is proposed and the effectiveness of the proposed calibration methods is investigated through a kinematic van test using integrated GPS and MEMS-based inertial measurement unit (IMU).

scholarly journals Concurrent Validation of 3D Joint Angles during Gymnastics Techniques Using Inertial Measurement Units

Electronics ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 1251
Author(s):  
Joana Barreto ◽  
César Peixoto ◽  
Sílvia Cabral ◽  
Andrew Mark Williams ◽  
Filipe Casanova ◽  
...  
Keyword(s):  
External Rotation ◽  
Ecological Validity ◽  
Biomechanical Analysis ◽  
Measurement Unit ◽  
Joint Angles ◽  
Optoelectronic System ◽  
Inertial Measurement ◽  
Flexion Extension ◽  
And Performance ◽  
Mean Square Errors

There are advantages in using inertial measurement unit systems (IMUS) for biomechanical analysis when compared to 2D/3D video-based analysis. The main advantage is the ability to analyze movement in the natural performance environment, preserving the ecological validity of the task. Coaches can access accurate and detailed data in real time and use it to optimize feedback and performance. Efforts are needed to validate the accuracy of IMUS. We assess the accuracy of the IMUS Xsens MVN Link system using an optoelectronic system (OS) as a reference when measuring 3D joint angles during the gymnastics round-off back handspring technique. We collected movement kinematics from 10 participants. The coefficient of multiple correlation (CMC) results showed very good and excellent values for the majority of the joint angles, except for neck flexion/extension (F/E). Root mean square errors (RMSE) were below/near 10°, with slightly higher values for shoulder (12.571°), ankle (11.068°), thorax-thigh F/E (21.416°), and thorax–thigh internal/external rotation (I/E) (16.312°). Significant SPM-1D {t} differences for thorax–thigh abduction/adduction (A/A), neck, thorax–thigh, knee, shoulder and ankle F/E were demonstrated during small temporal periods. Our findings suggest that the Xsens MVN Link system provides valid data that can be used to provide feedback in training.

scholarly journals Validation of Novel Relative Orientation and Inertial Sensor-to-Segment Alignment Algorithms for Estimating 3D Hip Joint Angles

Sensors ◽  
2019 ◽  
Vol 19 (23) ◽  
pp. 5143 ◽  
Author(s):  
Lukas Adamowicz ◽  
Reed Gurchiek ◽  
Jonathan Ferri ◽  
Anna Ursiny ◽  
Niccolo Fiorentino ◽  
...  
Keyword(s):  
Range Of Motion ◽  
Hip Joint ◽  
Inertial Sensor ◽  
Estimation Error ◽  
Relative Orientation ◽  
Joint Angles ◽  
Alignment Algorithms ◽  
Sensor Orientation ◽  
Flexion Extension ◽  
Optical Motion

Wearable sensor-based algorithms for estimating joint angles have seen great improvements in recent years. While the knee joint has garnered most of the attention in this area, algorithms for estimating hip joint angles are less available. Herein, we propose and validate a novel algorithm for this purpose with innovations in sensor-to-sensor orientation and sensor-to-segment alignment. The proposed approach is robust to sensor placement and does not require specific calibration motions. The accuracy of the proposed approach is established relative to optical motion capture and compared to existing methods for estimating relative orientation, hip joint angles, and range of motion (ROM) during a task designed to exercise the full hip range of motion (ROM) and fast walking using root mean square error (RMSE) and regression analysis. The RMSE of the proposed approach was less than that for existing methods when estimating sensor orientation ( 12 . 32 ∘ and 11 . 82 ∘ vs. 24 . 61 ∘ and 23 . 76 ∘ ) and flexion/extension joint angles ( 7 . 88 ∘ and 8 . 62 ∘ vs. 14 . 14 ∘ and 15 . 64 ∘ ). Also, ROM estimation error was less than 2 . 2 ∘ during the walking trial using the proposed method. These results suggest the proposed approach presents an improvement to existing methods and provides a promising technique for remote monitoring of hip joint angles.

scholarly journals Fluoroscopy-based laser projection system for surgical guidance and its calibration methods

10.29007/m1cq ◽  
2018 ◽  
Author(s):  
Sanghyun Joung ◽  
Hyunwoo Lee ◽  
Chul-Woo Park ◽  
Chnag-Wug Oh ◽  
Il-Hyung Park
Keyword(s):  
Experimental System ◽  
Ccd Camera ◽  
Calibration Method ◽  
Optical Tracking ◽  
Angular Error ◽  
Measurement Unit ◽  
Projection System ◽  
Calibration Phantom ◽  
Calibration Methods ◽  
Laser Module

We have developed a laser projection system, which can project laser on corresponding position to surgical planning drawn at a fluoroscopic image without an optical tracking system. In this paper, we introduce a spatial calibration method between a laser module and a fluoroscope for the laser projection and evaluate its accuracy with a mimic experimental system. The experimental system consists of a laser module, a distance measurement unit and a CCD camera. The laser modules can project arbitrary line on surface by reflecting a point source laser with two galvanometers. We designed a calibration phantom by combining a collimator for accurate laser pattern positioning and stainless steel ball arrays for calculation of an extrinsic parameter of a C-arm fluoroscopy. We set a projection plane having ruler in 400mm distance from the CCD camera, and set 54 points on the screen. The laser module projects points with respect to the set points, and a distance error between set points and projected points and angular error are calculated. The distance errors is 1.5±1.9 mm (average ± standard deviation). Maximum error was 7.5 mm. Angular error was smaller than 2 degrees. The laser projection system and its calibration method shows clinically acceptable accuracy and the clinical application is the next step.

scholarly journals A three dimensional multiplane kinematic model for bilateral hind limb gait analysis in cats

2018 ◽  
Author(s):  
Nathan P. Brown ◽  
Gina E. Bertocci ◽  
Kimberly A. Cheffer ◽  
Dena R. Howland
Keyword(s):  
Gait Analysis ◽  
Hind Limb ◽  
Sagittal Plane ◽  
External Rotation ◽  
Kinematic Model ◽  
Three Dimensional ◽  
Joint Angles ◽  
Plane Model ◽  
Flexion Extension ◽  
Joint Flexion

AbstractBackground: Kinematic gait analysis is an important noninvasive technique used for quantitative evaluation and description of locomotion and other movements in healthy and injured populations. Three dimensional (3D) kinematic analysis offers additional outcome measures including internal-external rotation not characterized using sagittal plane analysis techniques.Methods: The objectives of this study were to 1) develop and evaluate a 3D hind limb multiplane kinematic model for gait analysis in cats using joint coordinate systems, 2) implement and compare two 3D stifle (knee) prediction techniques, and 3) compare flexion-extension determined using the multiplane model to a sagittal plane model. Walking gait was recorded in 3 female adult cats (age = 2.9 years, weight = 3.5 ± 0.2 kg). Kinematic outcomes included flexion-extension, internal-external rotation, and abduction-adduction of the hip, stifle, and tarsal (ankle) joints.Results: Each multiplane stifle prediction technique yielded similar findings. Joint angles determined using markers placed on skin above bony landmarks in vivo were similar to joint angles determined using a feline hind limb skeleton in which markers were placed directly on landmarks ex vivo. Differences in hip, stifle, and tarsal joint flexion-extension were demonstrated when comparing the multiplane model to the sagittal plane model.Conclusions: This multiplane cat kinematic model can predict joint rotational kinematics as a tool that can quantify frontal, transverse, and sagittal plane motion. This model has multiple advantages given its ability to characterize joint internal-external rotation and abduction-adduction. A further, important benefit is greater accuracy in representing joint flexion-extension movements.

A New Calibration Method and Device for Certified Flow Measurements With Laser Velocimetry

2012 ◽  
Author(s):  
Katsuaki Shirai ◽  
Lars Büttner ◽  
Jürgen Czarske ◽  
Carsten Kykal
Keyword(s):  
Positional Information ◽  
Calibration Method ◽  
Calibration Procedure ◽  
Uncertainty Budget ◽  
New Method ◽  
Direct Access ◽  
Flow Measurements ◽  
Laser Velocimetry ◽  
Traceability Chain ◽  
Calibration Methods

We aim to establish traceability at calibration and hence to enable a certified flow measurement with a calibrated measurement system. A new calibration method is presented for laser velocimetry. We develop a simple, unique method which establishes traceability of its uncertainty. The device is transportable and calibratable by any users for their own instruments on-site. Our new method requires only a rotating disk and a precision linear stage providing positional information. In former calibration methods, the uncertainty of the orbit radius of a scattering object was dominant due to the difficulty of accessing the true center of the rotation. The diffuculty was solved in our new method. The new method provides an accurate estimate of the orbit radius and hence the velocity of the calibration object through a linear regression. The calibration constant is obtained even without the need of direct access to the absolute value of the rotation radius. The uncertainty budget is examined throughout the calibration procedure. The traceability chain is established once the traceabilities are maintained to the translation stage and the motor used for rotating the calibration disk. The new method has been realized with three different calibration setups and their performances were investigated. We demonstrate that the new calibration method can achieve uncertainty down to 0.1%.

scholarly journals Assessment of Scapulothoracic, Glenohumeral, and Elbow Motion in Adhesive Capsulitis by Means of Inertial Sensor Technology: A Within-Session, Intra-Operator and Inter-Operator Reliability and Agreement Study

Sensors ◽  
2020 ◽  
Vol 20 (3) ◽  
pp. 876 ◽  
Author(s):  
Liesbet De Baets ◽  
Stefanie Vanbrabant ◽  
Carl Dierickx ◽  
Rob van der Straaten ◽  
Annick Timmermans
Keyword(s):  
Inertial Sensors ◽  
Inertial Sensor ◽  
External Rotation ◽  
Adhesive Capsulitis ◽  
Movement Analysis ◽  
Elbow Flexion ◽  
Sensor Technology ◽  
Flexion Extension ◽  
Agreement Study ◽  
Joint Range

Adhesive capsulitis (AC) is a glenohumeral (GH) joint condition, characterized by decreased GH joint range of motion (ROM) and compensatory ROM in the elbow and scapulothoracic (ST) joint. To evaluate AC progression in clinical settings, objective movement analysis by available systems would be valuable. This study aimed to assess within-session and intra- and inter-operator reliability/agreement of such a motion capture system. The MVN-Awinda® system from Xsens Technologies (Enschede, The Netherlands) was used to assess ST, GH, and elbow ROM during four tasks (GH external rotation, combing hair, grasping a seatbelt, placing a cup on a shelf) in 10 AC patients (mean age = 54 (±6), 7 females), on two test occasions (accompanied by different operators on second occasion). Standard error of measurements (SEMs) were below 1.5° for ST pro-retraction and 4.6° for GH in-external rotation during GH external rotation; below 6.6° for ST tilt, 6.4° for GH flexion-extension, 7.1° for elbow flexion-extension during combing hair; below 4.4° for GH ab-adduction, 13° for GH in-external rotation, 6.8° for elbow flexion-extension during grasping the seatbelt; below 11° for all ST and GH joint rotations during placing a cup on a shelf. Therefore, to evaluate AC progression, inertial sensors systems can be applied during the execution of functional tasks.

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

Sensors ◽  
2020 ◽  
Vol 20 (6) ◽  
pp. 1747 ◽  
Author(s):  
Mirel Ajdaroski ◽  
Ruchika Tadakala ◽  
Lorraine Nichols ◽  
Amanda Esquivel
Keyword(s):  
Knee Joint ◽  
Motion Capture ◽  
Cruciate Ligament ◽  
Linear Regression Analysis ◽  
Knee Kinematics ◽  
The United States ◽  
Wearable Device ◽  
Joint Angles ◽  
Dynamic Movement ◽  
Flexion Extension

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.

scholarly journals Monitoring of Hip and Knee Joint Angles Using a Single Inertial Measurement Unit During Lower Limb Rehabilitation

2016 ◽  
Vol 16 (6) ◽  
pp. 1557-1564 ◽  
Author(s):  
Vincent Bonnet ◽  
Vladimir Joukov ◽  
Dana Kulic ◽  
Philippe Fraisse ◽  
Nacim Ramdani ◽  
...  
Keyword(s):  
Knee Joint ◽  
Lower Limb ◽  
Inertial Measurement Unit ◽  
Measurement Unit ◽  
Joint Angles ◽  
Inertial Measurement ◽  
Limb Rehabilitation ◽  
Lower Limb Rehabilitation

scholarly journals Online IMU Self-Calibration for Visual-Inertial Systems

Sensors ◽  
2019 ◽  
Vol 19 (7) ◽  
pp. 1624 ◽  
Author(s):  
Yao Xiao ◽  
Xiaogang Ruan ◽  
Jie Chai ◽  
Xiaoping Zhang ◽  
Xiaoqing Zhu
Keyword(s):  
Inertial Sensor ◽  
Low Cost ◽  
Optimization Methods ◽  
Calibration Method ◽  
Measurement Unit ◽  
Intrinsic Parameters ◽  
Self Calibration ◽  
Calibration Problem ◽  
System States ◽  
Inertial Systems

Low-cost microelectro mechanical systems (MEMS)-based inertial measurement unit (IMU) measurements are usually affected by inaccurate scale factors, axis misalignments, and g-sensitivity errors. These errors may significantly influence the performance of visual-inertial methods. In this paper, we propose an online IMU self-calibration method for visual-inertial systems equipped with a low-cost inertial sensor. The goal of our method is to concurrently perform 3D pose estimation and online IMU calibration based on optimization methods in unknown environments without any external equipment. To achieve this goal, we firstly develop a novel preintegration method that can handle the IMU intrinsic parameters error propagation. Then, we frame IMU calibration problem into general factors so that we can easily integrate the factors into the current graph-based visual-inertial frameworks and jointly optimize the IMU intrinsic parameters as well as the system states in a big bundle. We evaluate the proposed method with a publicly available dataset. Experimental results verify that the proposed approach is able to accurately calibrate all the considered parameters in real time, leading to significant improvement of estimation precision of visual-inertial system (VINS) compared with the estimation results with offline precalibrated IMU measurements.

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