16,281 research outputs found
Identification of multiple U-turns using IMUs: Comparative assessment of three methods
No full textDaily life locomotion includes sequences of straight and turn walking bouts. Wearable inertial measurement units (IMU) allow to extend the traditional gait analysis to tasks including turns. In this context, the preliminary goal of any IMU-based methodology is the identification of turns, thus allowing the trial segmentation into straight and turn bouts. Various methods have been proposed to identify turns in walking trials with a known number of turns. The aim of this study was to verify the applicability of three published methods to gait trials with an unknown number of turns, and to patients with different kinds of pathologies affecting gait. Results show that none of the methods was 100% accurate in detecting turns
The identification of multiple U-turns in gait: Comparison of four trunk IMU-based methods
No full textThe identification of turns during walking allows for the segmentation into straight and turn walking bouts. Several IMU-based methods were developed to this purpose, however many of them were tested on specific subject population. In this study, we tested four methods for the identification of turns in walking tasks with multiple U-turns that did not exploit any a-priori knowledge of the turn occurrences. We evaluated their robustness by recording IMU data on healthy and pathological subjects (healthy elderly, stroke survivors, patients with Parkinson disease and choreic patients) walking at two different speeds along a closed loop formed by straight bouts and U-turns. Overall, all methods identified correctly the totality of the U-turns when elderly and Parkinsonian patients were analyzed. When stroke survivors and choreic patients were analyzed, U-turns were either missed or erroneously detected in a limited number of cases. The only method using the magnetometer signals was the best performing, highlighting the usefulness of the magnetometer when turns are being investigated
Foot clearance estimation during overground walking and vertical obstacle passing using shank-mounted MIMUs in healthy and pathological subjects
No full textA method for assessing maximum foot clearance (maxFCl) during overground walking and obstacle passing using magnetic and inertial measurement units (MIMUs) placed above the malleoli is proposed and validated. The method precision and accuracy were evaluated using a stereo-photogrammetric system as a gold standard. The proposed method was applied to the data obtained from the gait of both healthy subjects and patients with various abnormal gaits. First, an optimally filtered direct and reverse integration (OFDRI) was used for each gait cycle to determine the gait velocity. Then, the effect of an additional OFDRI or a simple DRI approach for obtaining vertical foot displacement was explored. The results showed that the mean absolute errors associated to the maxFCl estimates were about 10% of its range of variation for the healthy and pathological subjects during overground walking. An accurate estimate of the maxFCl during obstacle passing was reached (mean absolute errors less than 5%). Additional testing on gait at various gait speed and on a greater number of subjects should be carried out to fully validate the MIMU-based maxFCl estimates
Accuracy, sensitivity and robustness of five different methods for the estimation of gait temporal parameters using a single inertial sensor mounted on the lower trunk
No full textExtension of the rigid‐constraint method for the heuristic suboptimal parameter tuning to ten sensor fusion algorithms using inertial and magnetic sensing
No full textThe orientation of a magneto‐inertial measurement unit can be estimated using a sensor fusion algorithm (SFA). However, orientation accuracy is greatly affected by the choice of the SFA parameter values which represents one of the most critical steps. A commonly adopted approach is to fine‐tune parameter values to minimize the difference between estimated and true orientation. However, this can only be implemented within the laboratory setting by requiring the use of a concurrent gold‐standard technology. To overcome this limitation, a Rigid‐Constraint Method (RCM) was proposed to estimate suboptimal parameter values without relying on any orientation reference. The RCM method effectiveness was successfully tested on a single‐parameter SFA, with an average error increase with respect to the optimal of 1.5 deg. In this work, the applicability of the RCM was evaluated on 10 popular SFAs with multiple parameters under different experimental scenarios. The average residual between the optimal and suboptimal errors amounted to 0.6 deg with a maximum of 3.7 deg. These encouraging results suggest the possibility to properly tune a generic SFA on different scenarios without using any reference. The synchronized dataset also including the optical data and the SFA codes are available online
2-D kinematics of the shank and foot complex during stance using markerless segmentation and body-segment anatomical axes identification
No full textIn this work, a markerless motion capture method is proposed for the 2-D description of the movement of the shank and foot complex. The video sequences of subjects walking wearing socks or barefoot, were segmented isolating the moving regions from the background. Anatomical axes of a three-segment model of the shank and foot complex were identified using two different methods applied to the segmented images: 1) skeletonization and line detection and 2) cross-correlation of selected image regions. The axes identified were used to determine the kinematics on the sagittal plane of the two joints included in the model. Results from the segmentation of the images are independent from the presence of the socks, allowing the definition of more flexible acquisition protocols. Joint kinematics estimation with both methods appeared to be comparable to that obtained with more traditional marker-based methods. The cross-correlation method, which includes the calibration of the anatomy of the body-segments, may provide more robust solutions for the extension to a 3-D analysis of the shank and foot complex kinematics compared to the other proposed method
An optimal procedure for stride length estimation using foot-mounted magneto-inertial measurement units
No full textStride length is often used to quantitatively evaluate human locomotion performance. Stride by stride estimation can be conveniently obtained from the signals recorded using miniaturized inertial sensors attached to the feet and appropriate algorithms for data fusion and integration. To reduce the detrimental drift effect, different algorithmic solutions can be implemented. However, the overall method accuracy is supposed to depend on the optimal selection of the parameters which are required to be set. This study aimed at evaluating the influence of the main parameters involved in well-established methods for stride length estimation. An optimization process was conducted to improve methods' performance and preferable values for the considered parameters according to different walking speed ranges are suggested. A parametric solution is also proposed to target the methods on specific subjects' gait characteristics. The stride length estimates were obtained from straight walking trials of five healthy volunteers and were compared with those obtained from a stereo-photogrammetric system. After parameters tuning, percentage errors for stride length were 1.9%, 2.5% and 2.6% for comfortable, slow, and fast walking conditions, respectively
2-D Lower limb joint kinematics using a hybrid markerless approach applied to video camcorder acquisitions
No full textA hybrid markerless technique is presented
and applied to estimate the 2-D lower limb joint
kinematics from acquisitions recorded using a video
camcorder. The proposed methodology is defined as
hybrid since it uses garments as “segmental markers”,
specifically high-cut underwear which contributes in
defining the pelvis segment and ankle socks for the
definition of the foot segment. The method was applied to
video sequences acquired with a video camcorder and was
validated by using a stereophotogrammetric markerbased
system. Results show that the proposed technique
can be considered as an easy-to-configure and affordable
alternative to marker-based photogrammetric systems
Analysis of the accuracy of ten algorithms for orientation estimation using inertial and magnetic sensing under optimal conditions: One size does not fit all
No full textThe orientation of a magneto and inertial measurement unit (MIMU) is estimated by means of sensor fusion algorithms (SFAs) thus enabling human motion tracking. However, despite several SFAs implementations proposed over the last decades, there is still a lack of consensus about the best performing SFAs and their accuracy. As suggested by recent literature, the filter parameters play a central role in determining the orientation errors. The aim of this work is to analyze the accuracy of ten SFAs while running under the best possible conditions (i.e., their parameter values are set using the orientation reference) in nine experimental scenarios including three rotation rates and three commercial products. The main finding is that parameter values must be specific for each SFA according to the experimental scenario to avoid errors comparable to those obtained when the de-fault parameter values are used. Overall, when optimally tuned, no statistically significant differ-ences are observed among the different SFAs in all tested experimental scenarios and the absolute errors are included between 3.8 deg and 7.1 deg. Increasing the rotation rate generally leads to a significant performance worsening. Errors are also influenced by the MIMU commercial model. SFA MATLAB implementations have been made available online
A two-dimensional clinical gait analysis protocol based on markerless recordings from a single RGB-Depth camera
No full textThis work presents a two-dimensional markerless clinical gait analysis protocol to estimate the sagittal lower limb joint kinematics from the markerless recordings of a single RGB-Depth camera. The proposed method includes a subject separation from the background, the definition of a multi-segmental model of the lower limb and the estimation of the relevant joint kinematics. The segmentation algorithm performance was assessed by measuring the similarity between the computer-obtained segmentations and manual tracings (ground-truth). The estimated joint angles were compared to those obtained using a reference optoelectronic marker-based clinical protocol. The offset between the mean waveforms and the RMS value of the waveforms difference after removing their offset were computed. The segmentation accuracy resulted to be higher than 0.92 and very repeatable (STD of JI about 0.01). The RMSD values of the ankle kinematics (3.4° on average) are lower than those of other joints (4.9° for the hip joint and 6.2° for the knee joint, on average). Overall, given the good agreement between our results and those of marker-based method, we propose to use it to develop a new generation of low-cost movement analysis systems
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