A Complementary Filter Design on SE(3) to Identify Micro-Motions during 3D Motion Tracking

Phan, Gia Hoang; Hansen, Clint; Tommasino, Paolo; Hussain, Asif; Formica, Domenico; Campolo, Domenico

doi:10.3390/s20205864

Cited by 7 publications

(4 citation statements)

References 28 publications

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“…Portable solutions such as inertial measurement units (IMUs) allow measurements outside of the laboratory in real world situations. IMUs usually contain accelerometers, gyroscopes and magnetometers, and the subsequent extraction of spatiotemporal gait parameters [ 4 , 5 ] is often based on sensor fusion algorithms [ 6 , 7 ]. While the validity of marker-based motion capture is rarely questioned [ 8 ], the reliability and validity of IMU-based motion capture is under constant evaluation [ 9 ] and the reliability of IMU-based gait parameters is rarely reported.…”

Section: Introductionmentioning

confidence: 99%

Reliability of IMU-Derived Temporal Gait Parameters in Neurological Diseases

Hansen

Ortlieb

Romijnders

et al. 2022

Sensors

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Evaluating gait is part of every neurological movement disorder assessment. Generally, the physician assesses the patient based on their experience, but nowadays inertial measurement units (IMUs) are also often integrated in the assessment. Instrumented gait analysis has a longstanding tradition and temporal parameters are used to compare patient groups or trace disease progression over time. However, the day-to-day variability needs to be considered especially in specific patient cohorts. The aim of the study was to examine day-to-day variability of temporal gait parameters of two experimental conditions in a cohort of neurogeriatric patients using data extracted from a lower back-worn IMU. We recruited 49 participants (24 women (age: 78 years ± 6 years, BMI = 25.1 kg/m2 and 25 men (age: 77 years ± 6 years, BMI = 26.5 kg/m2)) from the neurogeriatric ward. Two gait distances (4 m and 20 m) were performed during the first session and repeated the following day. To evaluate reliability, the Intraclass Correlation Coefficient (ICC2,k) and minimal detectable change (MDC) were calculated for the number of steps, step time, stride time, stance time, swing time, double limb support time, double limb support time variability, stride time variability and stride time asymmetry. The temporal gait parameters showed poor to moderate reliability with mean ICC and mean MDC95% values of 0.57 ± 0.18 and 52% ± 53%, respectively. Overall, only four out of the nine computed temporal gait parameters showed high relative reliability and good absolute reliability values. The reliability increased with walking distance. When only investigating steady-state walking during the 20 m walking condition, the relative and absolute reliability improved again. The most reliable parameters were swing time, stride time, step time and stance time. Study results demonstrate that reliability is an important factor to consider when working with IMU derived gait parameters in specific patient cohorts. This advocates for a careful parameter selection as not all parameters seem to be suitable when assessing gait in neurogeriatric patients.

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Section: Introductionmentioning

confidence: 99%

Reliability of IMU-Derived Temporal Gait Parameters in Neurological Diseases

Hansen

Ortlieb

Romijnders

et al. 2022

Sensors

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“…This is supported by findings from [31] who showed that in comparison with non-fallers, fallers exhibited a longer stance phase and a shorter swing phase which could mean that they maintain gait stability by increasing the stance phase. In a study with healthy adults [33] consciously altered the double-support percentage of the gait cycle without changing walking speed. The gait alterations are shown in larger double-limb support times, reduced single support, and a decreased joint range of motion, underlining the current results.…”

Section: Discussionmentioning

confidence: 99%

Changes in Coordination and Its Variability with an Increase in Functional Performance of the Lower Extremities

et al. 2023

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Clinical gait analysis has a long-standing tradition in biomechanics. However, the use of kinematic data or segment coordination has not been reported based on wearable sensors in “real-life” environments. In this work, the skeletal kinematics of 21 healthy and 24 neurogeriatric participants was collected in a magnetically disturbed environment with inertial measurement units (IMUs) using an accelerometer-based functional calibration method. The system consists of seven IMUs attached to the lower back, the thighs, the shanks, and the feet to acquire and process the raw sensor data. The Short Physical Performance Battery (SPPB) test was performed to relate joint kinematics and segment coordination to the overall SPPB score. Participants were then divided into three subgroups based on low (0–6), moderate (7–9), or high (10–12) SPPB scores. The main finding of this study is that most IMU-based parameters significantly correlated with the SPPB score and the parameters significantly differed between the SPPB subgroups. Lower limb range of motion and joint segment coordination correlated positively with the SPPB score, and the segment coordination variability correlated negatively. The results suggest that segment coordination impairments become more pronounced with a decreasing SPPB score, indicating that participants with low overall SPPB scores produce a peculiar inconsistent walking pattern to counteract lower extremity impairment in strength, balance, and mobility. Our findings confirm the usefulness of SPPB through objectively measured parameters, which may be relevant for the design of future studies and clinical routines.

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“…Ultimately, for the working of the proposed framework, the pose of the haptic stylus is needed. For more details, the reader is referred to [51] The rotation R obtained from the pose is used to compute the forces sensed by the loadcell in space frame, which is the actual force feedback F to be used for refining the geometric features in the proposed framework.…”

Section: Experimental Protocolmentioning

confidence: 99%

Haptic Manipulation of 3D Scans for Geometric Feature Enhancement

Turlapati

Accoto

Campolo

2021

Sensors

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Localisation of geometric features like holes, edges, slots, etc. is vital to robotic planning in industrial automation settings. Low-cost 3D scanners are crucial in terms of improving accessibility, but pose a practical challenge to feature localisation because of poorer resolution and consequently affect robotic planning. In this work, we address the possibility of enhancing the quality of a 3D scan by a manual ’touch-up’ of task-relevant features, to ensure their automatic detection prior to automation. We propose a framework whereby the operator (i) has access to both the actual work-piece and its 3D scan; (ii) evaluates the missing salient features from the scan; (iii) uses a haptic stylus to physically interact with the actual work-piece, around such specific features; (iv) interactively updates the scan using the position and force information from the haptic stylus. The contribution of this work is the use of haptic mismatch for geometric update. Specifically, the geometry from the 3D scan is used to predict haptic feedback at a point on the work-piece surface. The haptic mismatch is derived as a measure of error between this prediction and the real interaction forces from physical contact at that point on the work-piece. The geometric update is driven until the haptic mismatch is minimised. Convergence of the proposed algorithm is first numerically verified on an analytical surface with simulated physical interaction. Error analysis of the surface position and orientations were also plotted. Experiments were conducted using a motion capture system providing sub-mm accuracy in position and a 6 axis F/T sensor. Missing features are successfully detected after the update of the scan using the proposed method in an experiment.

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A Complementary Filter Design on SE(3) to Identify Micro-Motions during 3D Motion Tracking

Cited by 7 publications

References 28 publications

Reliability of IMU-Derived Temporal Gait Parameters in Neurological Diseases

Reliability of IMU-Derived Temporal Gait Parameters in Neurological Diseases

Changes in Coordination and Its Variability with an Increase in Functional Performance of the Lower Extremities

Haptic Manipulation of 3D Scans for Geometric Feature Enhancement

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