Evaluation and calibration of an electromagnetic tracking device for biomechanical analysis of lifting tasks

Périé, Delphine; Tate, Andrew; Cheng, Pei Lai; Dumas, Geneviève

doi:10.1016/s0021-9290(01)00188-9

Cited by 36 publications

(20 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Use of these techniques reduced the error rate associated with sensor position and orientation in this study to levels similar to previous work. [29][30][31] Additionally, preliminary data have shown electromagnetic tracking as a reliable tool for use in the examination of pitching kinematics. 43 Second, although competition was simulated throughout this study, there have been differences observed in movement when performed in both a simulated competitive setting and an actual competitive setting.…”

Section: Discussionmentioning

confidence: 99%

“…29 Increases in instrumental sensitivity have reduced this error to near 2° following system calibration. 30 Therefore, before testing sessions, the current system was calibrated using previously established techniques. [29][30][31] Following calibration, the error associated with position and orientation of the electromagnetic sensors within the calibrated axes system was less than 0.02 m and 3°, respectively.…”

mentioning

confidence: 99%

See 1 more Smart Citation

Lower Body Predictors of Glenohumeral Compressive Force in High School Baseball Pitchers

Keeley¹,

Oliver

Dougherty³

et al. 2015

Journal of Applied Biomechanics

View full text Add to dashboard Cite

The purpose of this study was to better understand how lower body kinematics relate to peak glenohumeral compressive force and develop a regression model accounting for variability in peak glenohumeral compressive force. Data were collected for 34 pitchers. Average peak glenohumeral compressive force was 1.72% ± 33% body weight (1334.9 N ± 257.5). Correlation coefficients revealed 5 kinematic variables correlated to peak glenohumeral compressive force (P < .01, α = .025). Regression models indicated 78.5% of the variance in peak glenohumeral compressive force (R2 = .785, P < .01) was explained by stride length, lateral pelvis flexion at maximum external rotation, and axial pelvis rotation velocity at release. These results indicate peak glenohumeral compressive force increases with a combination of decreased stride length, increased pelvic tilt at maximum external rotation toward the throwing arm side, and increased pelvis axial rotation velocity at release. Thus, it may be possible to decrease peak glenohumeral compressive force by optimizing the movements of the lower body while pitching. Focus should be on both training and conditioning the lower extremity in an effort to increase stride length, increase pelvis tilt toward the glove hand side at maximum external rotation, and decrease pelvis axial rotation at release.

show abstract

Section: Discussionmentioning

confidence: 99%

mentioning

confidence: 99%

Lower Body Predictors of Glenohumeral Compressive Force in High School Baseball Pitchers

Keeley¹,

Oliver

Dougherty³

et al. 2015

Journal of Applied Biomechanics

View full text Add to dashboard Cite

show abstract

“…The error compensation can be performed online during the use of the tracking system, based on another independent [31,32] Combination of EM and optical tracking systems Birkfellner et al [17] Using discrete LUT Meskers et al [107] Measurements averaged over time at reference points Perie et al [136] LUT based on plexi phantom Day et al [26] Employing a calibration phantom Interpolation Raab et al [148] First polynomial fit Thormann et al [177] Online correction by Hardy's multiquadric method Himberg et al [57] Multi-sensor data collection with LEGO Ikits et al [62] 4 th order polynomial fit Bryson et al [21] 4 th order polynomial fit Hagedorn et al [50] Delaunay tetrahedralization for rotations Kindratenko et al [71] 3-5 th order polynomial fit Nakamoto et al [124] 0-4 th order polynomial fit Traub et al [181] Interpolation on the top of LUT Fischer [35] Thin-Plate Spline Interpolation, Bernstein-polynoms Kelemen [67] Delaunay tetrahedralization and polynomial fit Extrapolation Kelemen [67] Extrapolation based on global polynomial fit…”

Section: B Active Compensationmentioning

confidence: 99%

Electromagnetic Tracking in Medicine—A Review of Technology, Validation, and Applications

Franz

Haidegger

Birkfellner

et al. 2014

IEEE Trans. Med. Imaging

384

273

View full text Add to dashboard Cite

Abstract-Object tracking is a key enabling technology in the context of computer-assisted medical interventions. Allowing the continuous localization of medical instruments and patient anatomy, it is a prerequisite for providing instrument guidance to subsurface anatomical structures. The only widely used technique that enables real-time tracking of small objects without lineof-sight restrictions is electromagnetic (EM) tracking. While EM tracking has been the subject of many research efforts, clinical applications have been slow to emerge. The aim of this review paper is therefore to provide insight into the future potential and limitations of EM tracking for medical use. We describe the basic working principles of EM tracking systems, list the main sources of error, and summarize the published studies on tracking accuracy, precision and robustness along with the corresponding validation protocols proposed. State-of-the-art approaches to error compensation are also reviewed in depth. Finally, an overview of the clinical applications addressed with EM tracking is given. Throughout the paper, we report not only on scientific progress, but also provide a review on commercial systems. Given the continuous debate on the applicability of EM tracking in medicine, this paper provides a timely overview of the state-of-the-art in the field.

show abstract

“…Stereo-photogrammetric systems (SP) are very accurate, but their use is limited by their cost, time, space, and expertise requirements. Magnetic based motion capture systems suffer from interference of undesired magnetic fields in the measurement volume [5], [6]. Wearable inertial sensors are a valuable alternative, however the drift affecting their output signals limits the reliability of the estimation of the derived position and orientation [7]- [9].…”

Section: Introductionmentioning

confidence: 99%

Validation of a Method for Real Time Foot Position and Orientation Tracking With Microsoft Kinect Technology for Use in Virtual Reality and Treadmill Based Gait Training Programs

Paolini

Peruzzi

Mirelman

et al. 2014

IEEE Trans. Neural Syst. Rehabil. Eng.

View full text Add to dashboard Cite

The use of virtual reality for the provision of motor-cognitive gait training has been shown to be effective for a variety of patient populations. The interaction between the user and the virtual environment is achieved by tracking the motion of the body parts and replicating it in the virtual environment in real time. In this paper, we present the validation of a novel method for tracking foot position and orientation in real time, based on the Microsoft Kinect technology, to be used for gait training combined with virtual reality. The validation of the motion tracking method was performed by comparing the tracking performance of the new system against a stereo-photogrammetric system used as gold standard. Foot position errors were in the order of a few millimeters (average RMSD from 4.9 to 12.1 mm in the medio-lateral and vertical directions, from 19.4 to 26.5 mm in the anterior-posterior direction); the foot orientation errors were also small (average %RMSD from 5.6% to 8.8% in the medio-lateral and vertical directions, from 15.5% to 18.6% in the anterior-posterior direction). The results suggest that the proposed method can be effectively used to track feet motion in virtual reality and treadmill-based gait training programs.

show abstract

Evaluation and calibration of an electromagnetic tracking device for biomechanical analysis of lifting tasks

Cited by 36 publications

References 10 publications

Lower Body Predictors of Glenohumeral Compressive Force in High School Baseball Pitchers

Lower Body Predictors of Glenohumeral Compressive Force in High School Baseball Pitchers

Electromagnetic Tracking in Medicine—A Review of Technology, Validation, and Applications

Validation of a Method for Real Time Foot Position and Orientation Tracking With Microsoft Kinect Technology for Use in Virtual Reality and Treadmill Based Gait Training Programs

Contact Info

Product

Resources

About