Upper Limbs Kinematics Estimation Using Affordable Visual-Inertial Sensors

Mallat, Randa; Bonnet, Vincent; Khalil, Mohamad; Mohammed, Samer

doi:10.1109/tase.2020.3024033

Cited by 9 publications

(9 citation statements)

References 36 publications

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“…We have shown in a recent study that EKF approach was able to cope efficiently with such short occlusion [22]. Thus we can conclude that the proposed method is not very sensitive to occlusion with the current setup.…”

Section: Discussionmentioning

confidence: 57%

“…1, and is based on the simultaneous use of affordable IMUs, incorporating only 3D accelerometers and gyroscopes sensors, i.e., no magnetometers, and a set of AR markers tracked with two affordable RGB cameras. The raw data collected from both IMUs and AR markers require a prior and unique calibration procedure that is based on a process detailed in our previous study [22] and briefly described in section II.B. A set of three AR markers is mounted on the top of each IMU sensor to form a so-called VIMU (see Fig.…”

Section: Methodsmentioning

confidence: 99%

“…However, the joint kinematics were not assessed in this study. Moreover, it is worthy noting that MKO and EKF were alternatively used with IMU [10] and AR markers [18], [22] (as well as with SS markers [23]). Both methods seem to provide similar results however the MKO can hardly be implemented in real-time [24].…”

Section: A Related Workmentioning

confidence: 99%

“…Proper sensor-to-segment calibration and EKF parameters tuning are also essential to provide accurate joint kinematics estimation. Our group has already proposed such an approach in a recent study [22] but it was dealing with simple arm tasks. Moreover, it required one sensor module per investigated segment.…”

Section: A Related Workmentioning

confidence: 99%

“…The gyroscope and accelerometer were calibrated, without the use of any external device, as proposed by Tedaldi et al to take into account inaccuracies in scaling factors, misalignment and non-orthogonality of axes, and non-zero biases [27]. Moreover, as shown in our previous study [22], the coordinate systems of the IMU and of the central AR markers were aligned thanks to a dynamic calibration step making use of centripetal acceleration, to calculate the rotation matrix R (3 × 3). Two rigid transformations also exist between the side coordinate systems of the AR markers and of the central one:…”

Section: ) Vimu Calibrationmentioning

confidence: 99%

See 4 more Smart Citations

Sparse Visual-Inertial Measurement Units Placement for Gait Kinematics Assessment

Mallat

Bonnet

Dumas

et al. 2021

IEEE Trans. Neural Syst. Rehabil. Eng.

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This study investigates the possibility of estimating lower-limb joint kinematics and meaningful performance indexes for physiotherapists, during gait on a treadmill based on data collected from a sparse placement of new Visual Inertial Measurement Units (VIMU) and the use of an Extended Kalman Filter (EKF). The proposed EKF takes advantage of the biomechanics of the human body and of the investigated task to reduce sensor inaccuracies. Two state-vector formulations, one based on the use of constant acceleration model and one based on Fourier series, and the tuning of their corresponding parameters were analyzed. The constant acceleration model, due to its inherent inconsistency for human motion, required a cumbersome optimisation process and needed the a-priori knowledge of reference joint trajectories for EKF parameters tuning. On the other hand, the Fourier series formulation could be used without a specific parameters tuning process. In both cases, the average root mean square difference and correlation coefficient between the estimated joint angles and those reconstructed with a reference stereophotogrammetric system was 3.5deg and 0.70, respectively. Moreover, the stride lengths were estimated with a normalized root mean square difference inferior to 2% when using the forward kinematics model receiving as input the estimated joint angles. The popular gait deviation index was also estimated and showed similar results very close to 100, using both the proposed method and the reference stereophotogrammetric system. Such consistency was obtained using only three wireless and affordable VIMU located at the pelvis and both heels and tracked using two affordable RGB cameras. Being further easy-to-use and suitable for applications taking place outside of the laboratory, the proposed method thus represents a good compromise between accurate reference stereophotogrammetric systems and markerless ones for which accuracy is still under debate.

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Section: Discussionmentioning

confidence: 57%

Section: Methodsmentioning

confidence: 99%