Towards validation and standardization of automatic gait event identification algorithms for use in paediatric pathological populations

Visscher, Rosa M. S.; Sansgiri, Sailee; Freslier, Marie; Harlaar, Jaap; Brunner, Reinald; Taylor, William R.; Singh, Navrag B.

doi:10.1016/j.gaitpost.2021.02.031

Cited by 30 publications

(40 citation statements)

References 19 publications

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“…To our knowledge, this is the first study that has evaluated the impact of marker location on the accuracy of gait event timing estimation. Our results support the hypothesis in Visscher et al (2021) that event detection in pathologies could be improved through optimal selection of the marker set according to the study cohort pathology. For example, generally the HEE-marker with Hreljac approach is used for estimating IC.…”

Section: Discussionsupporting

confidence: 87%

“…Data pre-processing was performed within the VICON-NEXUS software (v1.8.5), filtering was done using the built-in Woltring filter (mean squared error set to 10 mm 2 ), marker gaps smaller than five frames were filled using the built-in gap filling functions. To extract gait events (IC, TO) using vGRFs, a force threshold of 20 N was applied to the vertical component of the ground reaction force signal collected through the force plates (Kistler, Switzerland, sampling frequency 1,500 Hz) embedded in the walkway ( Visscher et al, 2021 ). Post-processing analyses were performed in MATLAB (R2019a, The Mathworks, Natick, United States) using the open-source Biomechanical ToolKit package (BTK) ( Barre and Armand, 2014 ).…”

Section: Methodsmentioning

confidence: 99%

“…Over the years, numerous algorithms have been developed, based on various marker sets as input ( Stanhope et al, 1990 ; Bruening and Ridge, 2014 ) . Here, previous work has shown that adaptation of the markers’ locations could improve the estimation of gait event timing, especially in pathological populations such as children with cerebral palsy (CP) ( Visscher et al, 2021 ). Within the CP population, multiple types of pathological gait patterns are present such as True equinus, Jump knee, Apparent equinus, and Crouch gait ( Rodda and Graham, 2001 ).…”

Section: Introductionmentioning

confidence: 99%

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Impact of the Marker Set Configuration on the Accuracy of Gait Event Detection in Healthy and Pathological Subjects

Visscher

Freslier

Moissenet

et al. 2021

Front. Hum. Neurosci.

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For interpreting outcomes of clinical gait analysis, an accurate estimation of gait events, such as initial contact (IC) and toe-off (TO), is essential. Numerous algorithms to automatically identify timing of gait events have been developed based on various marker set configurations as input. However, a systematic overview of the effect of the marker selection on the accuracy of estimating gait event timing is lacking. Therefore, we aim to evaluate (1) if the marker selection influences the accuracy of kinematic algorithms for estimating gait event timings and (2) what the best marker location is to ensure the highest event timing accuracy across various gait patterns. 104 individuals with cerebral palsy (16.0 ± 8.6 years) and 31 typically developing controls (age 20.6 ± 7.8) performed clinical gait analysis, and were divided into two out of eight groups based on the orientation of their foot, in sagittal and frontal plane at mid-stance. 3D marker trajectories of 11 foot/ankle markers were used to estimate the gait event timings (IC, TO) using five commonly used kinematic algorithms. Heatmaps, for IC and TO timing per group were created showing the median detection error, compared to detection using vertical ground reaction forces, for each marker. Our findings indicate that median detection errors can be kept within 7 ms for IC and 13 ms for TO when optimizing the choice of marker and detection algorithm toward foot orientation in midstance. Our results highlight that the use of markers located on the midfoot is robust for detecting gait events across different gait patterns.

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Section: Discussionsupporting

confidence: 87%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Impact of the Marker Set Configuration on the Accuracy of Gait Event Detection in Healthy and Pathological Subjects

Visscher

Freslier

Moissenet

et al. 2021

Front. Hum. Neurosci.

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“…This study aimed to propose a method for marker-based gait event detections from motion capture data in complex motor tasks and demonstrate its applicability to gait assessment in different conditions. Using reference gait events detected with pressure insoles, several methods were initially compared with data collected from young healthy adults and the best results were achieved by combining a method based on the AP trajectories ( Zeni et al, 2008 ), largely used in the literature and already tested on different populations ( Zeni et al, 2008 ; Bruening and Ridge, 2014 ; Hendershot et al, 2016 ; Filtjens et al, 2020 ; Gonçalves et al, 2020 ; Lempereur et al, 2020 ; Visscher et al, 2021 ), with an innovative solution exploiting 3D foot velocities, which overcame previously reported issues associated with gait event anticipation. This method (M10) provided estimations with a virtually null bias for both initial and final contacts for all investigated variables, except for a 20 ms bias (2 frame anticipation) for the final contact detection during step negotiation.…”

Section: Discussionmentioning

confidence: 99%

An Algorithm for Accurate Marker-Based Gait Event Detection in Healthy and Pathological Populations During Complex Motor Tasks

Bonci

Salis

Scott

et al. 2022

Front. Bioeng. Biotechnol.

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There is growing interest in the quantification of gait as part of complex motor tasks. This requires gait events (GEs) to be detected under conditions different from straight walking. This study aimed to propose and validate a new marker-based GE detection method, which is also suitable for curvilinear walking and step negotiation. The method was first tested against existing algorithms using data from healthy young adults (YA, n = 20) and then assessed in data from 10 individuals from the following five cohorts: older adults, chronic obstructive pulmonary disease, multiple sclerosis, Parkinson’s disease, and proximal femur fracture. The propagation of the errors associated with GE detection on the calculation of stride length, duration, speed, and stance/swing durations was investigated. All participants performed a variety of motor tasks including curvilinear walking and step negotiation, while reference GEs were identified using a validated methodology exploiting pressure insole signals. Sensitivity, positive predictive values (PPV), F1-score, bias, precision, and accuracy were calculated. Absolute agreement [intraclass correlation coefficient (ICC2,1)] between marker-based and pressure insole stride parameters was also tested. In the YA cohort, the proposed method outperformed the existing ones, with sensitivity, PPV, and F1 scores ≥ 99% for both GEs and conditions, with a virtually null bias (<10 ms). Overall, temporal inaccuracies minimally impacted stride duration, length, and speed (median absolute errors ≤1%). Similar algorithm performances were obtained for all the other five cohorts in GE detection and propagation to the stride parameters, where an excellent absolute agreement with the pressure insoles was also found (ICC2,1=0.817− 0.999). In conclusion, the proposed method accurately detects GE from marker data under different walking conditions and for a variety of gait impairments.

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“…Yet, only two devices [111,114] We consider that joint or body segment kinematic metrics (used in 41.8 % of the exoskeletons for all the pathologies, 36.8 % for stroke, and 40.0 % for CP) might be more reliable metrics in human-robot synchronization algorithms when detecting events with brain-injured people [216], as higher homogeneity in kinematic metrics can be found among people with hemiplegic gait [217,218]. In particular, the shank absolute angle and angular velocity in the sagittal plane have been shown to be especially robust metrics to detect gait events in people with hemiplegic gait [219].…”

mentioning

confidence: 99%

Control strategies used in lower limb exoskeletons for gait rehabilitation after brain injury: a systematic review and analysis of clinical effectiveness

Miguel-Fernández

Lobo-Prat²,

Prinsen

et al. 2022

Preprint

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BackgroundIn the past decade, there has been substantial progress in the development of robotic controllers that specify how lower-limb exoskeletons should interact with brain-injured patients. However, it is still an open question which exoskeleton control strategies can more effectively stimulate motor function recovery. Within this review, we aim to complement previous literature surveys on the topic of exoskeleton control for gait rehabilitation by: (1) Providing an updated structured framework of current control strategies, (2) Analyzing the methodology of clinical validations used in the robotic interventions, and (3) Reporting the potential relation between the employed control strategies and clinical outcomes. MethodsFour databases were searched using database-specific search terms from 2000 to September 2020. We identified 1648 articles, of which 159 were included and evaluated in full-text. We included studies that clinically evaluated the effectiveness of the exoskeleton on impaired participants, and which clearly explained or referenced the implemented control strategy. Results(1) We found that adaptive assistive control (100 \% of exoskeletons) that followed rule-based algorithms (72 \%) based on ground reaction force thresholds (63 \%) in conjunction with trajectory-tracking control (97 \%) were the most implemented control strategies. (2) Regarding the clinical validations used in the robotic interventions, we found high variability on the experimental protocols and outcome metrics selected. (3) With moderate grade of evidence, associated to the high heterogeneity in the experimental protocol and low number of studies, we found that adaptive control strategies, which followed threshold-based or adaptive oscillator algorithms together with trajectory-tracking control, resulted in the highest improvements on clinical outcomes for people with stroke. ConclusionsDespite the efforts to develop novel more effective controllers for gait neurorehabilitation, the current level of evidence on the effectiveness of the different control strategies on clinical outcomes is still low. There is a clear lack of standardization in the experimental protocols leading to high levels of heterogeneity. Standardized comparisons among control strategies analyzing the relation between control parameters and biomechanical metrics will fill this gap to better guide future technical developments. The most promising controllers seem to be those that adapt to key biomechanical descriptors based on the patients' specific pathology.

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Towards validation and standardization of automatic gait event identification algorithms for use in paediatric pathological populations

Cited by 30 publications

References 19 publications

Impact of the Marker Set Configuration on the Accuracy of Gait Event Detection in Healthy and Pathological Subjects

Impact of the Marker Set Configuration on the Accuracy of Gait Event Detection in Healthy and Pathological Subjects

An Algorithm for Accurate Marker-Based Gait Event Detection in Healthy and Pathological Populations During Complex Motor Tasks

Control strategies used in lower limb exoskeletons for gait rehabilitation after brain injury: a systematic review and analysis of clinical effectiveness

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