Kinematic Gait Parameters Research Articles

Inter-trial variability is higher in 3D markerless compared to marker-based motion capture: Implications for data post-processing and analysis

Markerless motion capture has recently attracted significant interest in clinical gait analysis and human movement science. Its ease of use and potential to streamline motion capture recordings bear great potential for out-of-the-laboratory measurements in large cohorts. While previous studies have shown that markerless systems can achieve acceptable accuracy and reliability for kinematic parameters of gait, they also noted higher inter-trial variability of markerless data. Since increased inter-trial variability can have important implications for data post-processing and analysis, this study compared the inter-trial variability of simultaneously recorded markerless and marker-based data. For this purpose, the data of 18 healthy volunteers were used who were instructed to simulate four different gait patterns: physiological, crouch, circumduction, and equinus gait. Gait analysis was performed using the smartphone-based markerless system OpenCap and a marker-based motion capture system. We compared the inter-trial variability of both systems and also evaluated if changes in inter-trial variability may depend on the analyzed gait pattern. Compared to the marker-based data, we observed an increase of inter-trial variability for the markerless system ranging from 6.6% to 22.0% for the different gait patterns. Our findings demonstrate that the markerless pose estimation pipelines can introduce additionally variability in the kinematic data across different gait patterns and levels of natural variability. We recommend using averaged waveforms rather than single ones to mitigate this problem. Further, caution is advised when using variability-based metrics in gait and human movement analysis based on markerless data as increased inter-trial variability can lead to misleading results.

Psychometric properties of portable devices used in kinematic gait assessment after stroke: a systematic review protocol

Background Portable devices comprising inertial sensors are an alternative for kinematic gait assessment in people after stroke. Nevertheless, there is limited knowledge regarding the psychometric properties of these devices, specifically their reliability and measurement error, in the context of post-stroke gait assessment. Our objective is to investigate the psychometric properties of these devices in evaluating kinematic gait parameters in people after stroke. We will also analyze the reliability and measurement error of these devices and identify portable devices that can assess changes in lower limb angular movements during gait in this population. Methods We will search for studies in English, without publication date restriction, that have evaluated psychometric properties of portable devices utilizing inertial sensors to assess kinematic gait parameters in people after stroke. Searches will be performed in the following electronic databases: Cochrane Central Registry of Controlled Trials (CENTRAL), Medline/PubMed, EMBASE Ovid, CINAHL EBSCO, PsycINFO Ovid, IEEE Xplore Digital Library (IEEE), and Physiotherapy Evidence Database (PEDro). Gray literature will also be searched, including published and unpublished studies (dissertations and theses). The Consensus-based Standards for the Selection of Health Measurement Instruments (COSMIN) risk of bias tool will be used to assess the quality of studies that analyzed reliability and measurement error of devices. Expected results This will be the first review to analyze reliability and measurement error of portable devices utilizing inertial sensors to evaluate kinematic gait parameters in people after stroke, using the COSMIN tool. Then, we hope to elucidate this topic and help the decision-making of clinicians regarding the use of these devices. Finally, we also hope to list the portable devices that assessed changes in angular lower limb movements during gait in this population. Registration The protocol was registered in Open Science Framework on May 11th 2023 (https://doi.org/10.17605/OSF.IO/7M6DA).

Does the Chêneau brace affect gait pattern and body balance of adolescents with idiopathic scoliosis?

Purpose This study evaluated changes in selected spatiotemporal and kinematic gait parameters and balance in girls with Adolescent idiopathic scoliosis (AIS) with and without the Chêneau brace. Methods 15 subjects with scoliosis wearing the Chêneau brace and an equal comparative control group underwent objective gait analysis with the 3D BTS motion caption system. Balance assessment was done with the Kistler platform. The analysis was performed at comparison of gait and balance parameters in patients with scoliosis in two conditions: with and without the Chêneau brace during the study. Results Statistically significant differences occurred in many spatiotemporal and kinematic parameters both for the AIS group with and without the Chêneau brace and in the AIS group with and without the Chêneau brace as compared to the control group. When comparing adolescents with AIS with and without the Chêneau brace, statistically significant differences were noted in the COP-X amplitude and in the path length in trials with closed eyes. Compared to the control group the following differences were statistically significant: the value of the the COP-Y amplitude during the trial with closed eyes, both with and without the Chêneau brace, and the Equivalent area of the COP during the trial with closed eyes with the Chêneau brace. Conclusions The Chêneau brace in patients with juvenile idiopathic scoliosis affects the level of selected balance and gait parameters.

A60: Gait Kinematics Characteristics of the Overweight and Obese Elderly at Different Walking Speeds

Purpose: Gait is associated with falls. Overweight, obesity and falls are prominent problems affecting the healthy life of the elderly in China. The purpose of this study is to measure the gait kinematic parameters of the overweight and obese elderly using BTS SMART DX Motion Capture System, and to analyze the gait characteristics of the overweight and obese elderly when walking with different speeds, so as to provide reference for the prevention of falls in the overweight and obese elderly. Methods: A total of 42 healthy old women (overweight or obese group: N = 20, age = 67.36±6.11 yrs.; normal weight group: N = 22, age = 68.65±4.07 yrs.) were recruited in this study. The kinematic parameters of subjects at constant walking speed (1.05 m/s), fast walking speed (1.41 m/s) and rushed walking speed (1.74 m/s) were measured and analyzed by BTS SMART DX Motion Capture System. Results: Two-way Repeated Measures ANOVA indicated that the within-subjects effects of stride time, double support phase, cadence, stride length, step length, step width, and knee flex-extension in the moment of touching the ground, as well as hip flex-extension, ankle dorsi-plantarflex, knee rotation, and knee ab-adduction in the moment of leaving the ground had significant difference (F = 34.889, p = 0.000; F = 3.963, p = 0.029; F = 91.408, p = 0.000; F = 19.645, p = 0.000; F = 10.183, p = 0.000; F = 4.561, p = 0.015; F = 17.289, p = 0.000; F = 9.367, p = 0.000; F = 8.557, p = 0.001; F = 13.399, p = 0.000; F = 9.971, p = 0.000). The interaction effect of walking speed and body weight on step length was significantly different (F = 3.504, p = 0.037). The between-subjects effect of knee rotation had significant difference (F = 4.197, p = 0.049). Conclusion: The walking speed could significantly affect the spatial-temporal characteristics and the angle of the lower extremity joints of the elderly, especially the spatial position of the gait and the motion of the knee joint. Overweight and obese elderly women have a higher risk of falls in the moment of leaving the ground when rushed walking.

ASPEBI: A MATLAB Tool for Motion Analysis of Non-Specific Low Back Pain Patients

Low back pain is one of the most common health issues worldwide, and non-specific low back pain (NLBP), whose causes are unknown, represents 85% of these cases. Hamstring Extension in Bipedal Position (PEBI) is a clinical sign designed to discriminate the cause of the pain of NLBP as of muscular origin due to the stiffness of the hamstring. Currently, PEBI lacks quantitative assessment, which is required to be utilized in primary care. To support the process of getting such information, in this work, we present ASPEBI, a customized MATLAB® app developed to provide researchers and clinicians with a tool for the visualization of the kinematic and spatiotemporal gait parameters of patients examined with PEBI. This objective information is processed from data collected with the Xsens MTw Awinda system, which can be analyzed by the final users. Lastly, this tool is user-friendly with a modular design that allows integration of other physiological technologies to conduct multimodal analysis, and it could be utilized to explore issues related to older populations or populations with neurodegenerative diseases, among others.

Clinical reliability and validity of a video-based markerless gait evaluation method.

To explore the reliability and validity of gait parameters obtained from gait assessment system software employing a human posture estimation algorithm based on markerless videos of children walking in clinical practice. Eighteen typical developmental (TD) children and ten children with developmental dysplasia of the hip (DDH) were recruited to walk along a designated sidewalk at a comfortable walking speed. A 3-dimensional gait analysis (3D GA) and a 2-dimensional markerless (2D ML) gait evaluation system were used to extract the gait kinematics parameters twice at an interval of 2 h. The two measurements of the children's kinematic gait parameters revealed no significant differences (P > 0.05). Intra-class correlation coefficients (ICC) were generally high (ICC >0.7), showing moderate to good relative reliability. The standard error of measurement (SEM) values of all gait parameters measured by the two walks were 1.26°-2.91°. The system software had good to excellent validity compared to the 3D GA, with ICC values between 0.835 and 0.957 and SEM values of 0.87°-1.71° for the gait parameters measured by both methods. The Bland-Altman plot analysis indicated no significant systematic errors. The feasibility of the markerless gait assessment method using the human posture estimation-based algorithm may provide reliable and valid gait analysis results for practical clinical applications.

Effect of Anterioposterior Weight-Shift Training with Visual Biofeedback in Patients with Step Length Asymmetry after Subacute Stroke.

Step length asymmetry is a characteristic feature of gait in post-stroke patients. A novel anterioposterior weight-shift training method with visual biofeedback (AP training) was developed to improve the forward progression of the trunk. This study aimed to investigate the effect of AP training on gait asymmetries, patterns, and gait-related function in subacute stroke patients. Forty-six subacute stroke patients were randomly assigned to the AP training group or the control group. The AP training group received conventional gait training and AP training five times per week for 4 weeks. The control group received the same intensity of conventional gait training with patient education for self-anterior weight shifting. Plantar pressure analysis, gait analysis, energy consumption, and gait-related behavioral parameters were assessed before and after training. The AP training group showed significant improvement in step length asymmetry, forefoot contact area and pressure, Berg balance scale score, and Fugl-Meyer assessment scale of lower extremity score compared to the control group (p < 0.05). However, there was no significant between-group difference with respect to energy cost and kinetic and kinematic gait parameters. In conclusion, AP training may help improve the asymmetric step length in stroke patients, and also improve anterior weight shifting, balance, and motor function in subacute stroke survivors.

Influence of Visual Augmented Feedback on Walking Speed Perception in Immersive Virtual Reality

Abstract In virtual reality (VR), established perception–action relationships break down because of conflicting and ambiguous sensorimotor inputs, inducing walking velocity underestimations. Here, we explore the effects of realigning perceptual sensory experiences with physical movements via augmented feedback on the estimation of virtual speed. We hypothesized that providing feedback about speed would lead to concurrent perceptual improvements and that these alterations would persist once the speedometer was removed. Ten young adults used immersive VR to view a virtual hallway translating at a series of fixed speeds. Participants were tasked with matching their walking speed on a self-paced treadmill to the optic flow in the environment. Information regarding walking speed accuracy was provided during augmented feedback trials via a real-time speedometer. We measured resulting walking velocity errors, as well as kinematic gait parameters. We found that the concordance between the virtual environment and gait speeds was higher when augmented feedback was provided during the trial. Furthermore, we observed retention effects beyond the intervention period via demonstrated smaller errors in speed perception accuracy and stronger concordance between perceived and actual speeds. Together, these results highlight a potential role for augmented feedback in guiding gait strategies that deviate away from predefined internal models of locomotion.

Modeling and Analysis of Foot Function in Human Gait Using a Two-Degrees-of-Freedom Inverted Pendulum Model with an Arced Foot.

Gait models are important for the design and control of lower limb exoskeletons. The inverted pendulum model has advantages in simplicity and computational efficiency, but it also has the limitations of oversimplification and lack of realism. This paper proposes a two-degrees-of-freedom (DOF) inverted pendulum walking model by considering the knee joints for describing the characteristics of human gait. A new parameter, roll factor, is defined to express foot function in the model, and the relationships between the roll factor and gait parameters are investigated. Experiments were conducted to verify the model by testing seven healthy adults at different walking speeds. The results demonstrate that the roll factor has a strong relationship with other gait kinematics parameters, so it can be used as a simple parameter for expressing gait kinematics. In addition, the roll factor can be used to identify walking styles with high accuracy, including small broken step walking at 99.57%, inefficient walking at 98.14%, and normal walking at 99.43%.

Acute effects of robot-assisted body weight unloading on biomechanical movement patterns during overground walking

Body weight unloading (BWU) is used in rehabilitation/training settings to reduce kinetic requirements, however different BWU methods may be unequally capable of preserving biomechanical movement patterns. Biomechanical analysis of both kinetic and kinematic movement trajectories rather than discrete variables has not previously been performed to describe the effect of BWU on gait patterns during horizontal walking. The aim of the present study was to investigate how robot-assisted BWU producing an dynamic unloading force on the body centre of mass, affects kinematic, kinetic, and spatiotemporal gait parameters in healthy young adults by use of time-continuous analysis. Twenty participants walked overground in a 3-D motion-capture lab at 0, 10, 20, 30, 40, and 50 % BWU at a self-selected speed. Vertical and anterior-posterior ground reaction forces (GRFs) and lower limb internal joint moments were obtained during the stance phase, while joint angles were obtained during entire strides. Time-continuous data were analysed using Statistical Parametric Mapping (SPM) and discrete data using conventional statistics to compare different BWU conditions by means of One-Way Repeated Measures Anova. With increasing BWU, corresponding reductions were observed for GRFs, internal joint moments, joint angles, walking speed, stride/step length and cadence. Observed effects were partially caused by decreased walking speed and increased BWU. While amplitude reductions were observed for kinetic and kinematic variables, trajectory shapes were largely preserved. In conclusion, dynamic robot-assisted BWU enables reduced kinetic requirements without distorting biomechanically normal gait patterns during overground walking in young healthy adults.

Two-dimensional analysis of gait parameters in schizophrenia – an observational study

Background. Gait analysis is a systematic study of human locomotion that involves evaluating body motions, body mechanics, and muscle activity Objective. To analyze spatiotemporal and kinematics variables in schizophrenia. Methodology. Non-Experimental study, convenient sampling, sample size was 15. Both men and women with 18 to 45 years of age were included in the study. Procedure. subjects were selected based on inclusion and exclusion criteria for analyzing the kinematic and spatio temporal parameters of gait in schizophrenia. Outcome measures. Spatiotemporal and kinematics variables were assessed by using 2D gait analysis with software from Auptimo technologies. Results. Gait analysis of schizophrenia shows significant increase in ankle plantar flexion p &lt; 0.05, significant increase in knee flexion p &lt; 0.05, and significant increase in hip flexion p &lt; 0.05 shows in lateral view and in anterior view significant increase in knee abduction/ adduction p &lt; 0.05, and in posterior view significant increase in contralateral pelvic drop p &lt; 0.05, and significant increase in rear foot angle eversion p &lt; 0.05. In spatiotemporal parameters of schizophrenia shows non significant changes in cadence p &gt; 0.05, and shows significant changes in right and lest stance time, right and left swing, and gait cycle time p &lt; 0.05. Conclusion. This study concluded that schizophrenia shows marked kinematic changes in ankle, knee and hip joint, in anterior view knee abduction and adduction shows notable changes, and in posterior view, significant changes in pelvic drop and rear foot angle, and spatio temporal parameters no apparent changes noted in cadence, and significant increases in stance phase time, swing phase time and gait cycle time.

Gait and strength assessment following surgical repair by intramedullary nailing of isolated tibial shaft fracture.

The objective of the study was to evaluate the long-term strength and gait outcomes after intramedullary nailing of isolated tibial diaphyseal fractures. This retrospective cohort study was conducted at an academic Level I trauma center. Fifteen participants with isolated tibial diaphyseal fractures (OTA/AO 42) at least 2 years postoperative from intramedullary nailing (IMN) provided informed consent. The average age was 40 ± 14 (range, 24-69); there were nine men and six women. Knee flexion-extension strength data were collected. Temporal-spatial, kinematic, and kinetic gait parameters were measured and compared to historic control data. Participants completed the SF-36 and shortened musculoskeletal function assessment questionnaires. The mean length of follow-up between surgery and gait analysis was 6 ± 2 years. The fractured limb demonstrated deficits in quadriceps strength between 9.8% and 23.4% compared to the unaffected limb. Temporal-spatial parameters revealed slower walking speed, shorter stride length, decreased cadence, and shorter single-limb support time in the fractured limb. Altered kinematic and kinetic findings included a knee extension shift during stance, with an increased knee flexor moment demand and decreased total knee power during loading and midstance. These findings represent deficits in concentric and eccentric knee extensor activity. Additionally, the fractured limb demonstrated decreased ankle dorsiflexion during stance and diminished ankle push-off power. Long-term outcomes after IMN of tibial diaphyseal fractures demonstrate decreased quadriceps strength and altered gait parameters that may have implications to the high incidence of knee and ankle pain in the fractured limb.

Biomechanical investigation of tasks concerning manual materials handling using response surface methodology

In typical manual material handling, the variations in walking pattern are decided by various factors, such as load being handled, frequency of handling, walking surface, etc. Traditional gait analysis protocols commonly evaluate individual factor within specified ranges associated with particular activities or pathologies. However, existing literature underscores the concurrent impact of multiple factors on gait. This study identifies five pivotal factors—walking speed, surface slope, load carried, carrying method, and footwear—as contributors to gait alterations. To address risk factors in manual material handling activities, we propose a unique design-of-experiment-based approach for multi-task gait analysis. Unraveling the relationship between manual handling attributes and human gait holds paramount importance in formulating effective intervention strategies. We optimized the five input factors across a cohort of 15 healthy male participants by employing a face-centered central composite design experimentation. A total of 29 input factor combinations were tested, yielding a comprehensive dataset encompassing 18 kinematic gait parameters (such as cadence, step length etc., measured using inertial measurement system), the isolated impacts of factors, and the interplay of two-factor interactions with corresponding responses. The results illuminate the optimal scenarios of input factors that enhance individual gait performance—these include wearing appropriate footwear, employing a backpack for load carriage, and maintaining a moderate walking pace on a medium slope with minimal load. The study identifies walking speed and load magnitude as primary influencers of gait mechanics, followed by the chosen carrying method. In consequence, the insights gained advocate for the refinement of manual material handling tasks based on the outcomes, effectively mitigating the risk of musculoskeletal disorders by suggesting the interventions for posture correction.

Spatiotemporal gait parameter fluctuations in older adults affected by mild cognitive impairment: comparisons among three cognitive dual-task tests

BackgroundsGait disorder is associated with cognitive functional impairment, and this disturbance is more pronouncedly when performing additional cognitive tasks. Our study aimed to characterize gait disorders in mild cognitive impairment (MCI) under three dual tasks and determine the association between gait performance and cognitive function.MethodsA total of 260 participants were enrolled in this cross-sectional study and divided into MCI and cognitively normal control. Spatiotemporal and kinematic gait parameters (31 items) in single task and three dual tasks (serial 100-7, naming animals and words recall) were measured using a wearable sensor. Baseline characteristics of the two groups were balanced using propensity score matching. Important gait features were filtered using random forest method and LASSO regression and further described using logistic analysis.ResultsAfter matching, 106 participants with MCI and 106 normal controls were recruited. Top 5 gait features in random forest and 4 ~ 6 important features in LASSO regression were selected. Robust variables associating with cognitive function were temporal gait parameters. Participants with MCI exhibited decreased swing time and terminal swing, increased mid stance and variability of stride length compared with normal control. Subjects walked slower when performing an extra dual cognitive task. In the three dual tasks, words recall test exhibited more pronounced impact on gait regularity, velocity, and dual task cost than the other two cognitive tests.ConclusionGait assessment under dual task conditions, particularly in words recall test, using portable sensors could be useful as a complementary strategy for early detection of MCI.

Accuracy of Video-Based Gait Analysis Using Pose Estimation During Treadmill Walking Versus Overground Walking in Persons After Stroke.

Video-based pose estimation is an emerging technology that shows significant promise for improving clinical gait analysis by enabling quantitative movement analysis with little costs of money, time, or effort. The objective of this study is to determine the accuracy of pose estimation-based gait analysis when video recordings are constrained to 3 common clinical or in-home settings (ie, frontal and sagittal views of overground walking and sagittal views of treadmill walking). Simultaneous video and motion capture recordings were collected from 30 persons after stroke during overground and treadmill walking. Spatiotemporal and kinematic gait parameters were calculated from videos using an open-source human pose estimation algorithm and from motion capture data using traditional gait analysis. Repeated-measures analyses of variance were then used to assess the accuracy of the pose estimation-based gait analysis across the different settings, and the authors examined Pearson and intraclass correlations with ground-truth motion capture data. Sagittal videos of overground and treadmill walking led to more accurate measurements of spatiotemporal gait parameters versus frontal videos of overground walking. Sagittal videos of overground walking resulted in the strongest correlations between video-based and motion capture measurements of lower extremity joint kinematics. Video-based measurements of hip and knee kinematics showed stronger correlations with motion capture versus ankle kinematics for both overground and treadmill walking. Video-based gait analysis using pose estimation provides accurate measurements of step length, step time, and hip and knee kinematics during overground and treadmill walking in persons after stroke. Generally, sagittal videos of overground gait provide the most accurate results. Many clinicians lack access to expensive gait analysis tools that can help identify patient-specific gait deviations and guide therapy decisions. These findings show that video-based methods that require only common household devices provide accurate measurements of a variety of gait parameters in persons after stroke and could make quantitative gait analysis significantly more accessible.

Kinematic Gait Analysis in People with Mild-Disability Multiple Sclerosis Using Statistical Parametric Mapping: A Cross-Sectional Study.

Multiple sclerosis (MS) is a chronic autoimmune disease that affects the central nervous system. Gait abnormalities, such as altered joint kinematics, are common in people with MS (pwMS). Traditional clinical gait assessments may not detect subtle kinematic alterations, but advances in motion capture technology and analysis methods, such as statistical parametric mapping (SPM), offer more detailed assessments. The aim of this study was to compare the lower-limb joint kinematics during gait between pwMS and healthy controls using SPM analysis. Methods: A cross-sectional study was conducted involving pwMS and healthy controls. A three-dimensional motion capture system was used to obtain the kinematic parameters of the more affected lower limb (MALL) and less affected lower limb (LALL), which were compared using the SPM analysis. Results: The study included 10 pwMS with mild disability (EDSS ≤ 3) and 10 healthy controls. The results showed no differences in spatiotemporal parameters. However, significant differences were observed in the kinematics of the lower-limb joints using SPM. In pwMS, compared to healthy controls, there was a higher anterior pelvis tilt (MALL, p = 0.047), reduced pelvis elevation (MALL, p = 0.024; LALL, p = 0.044), reduced pelvis descent (MALL, p = 0.033; LALL, p = 0.022), reduced hip extension during pre-swing (MALL, p = 0.049), increased hip flexion during terminal swing (MALL, p = 0.046), reduced knee flexion (MALL, p = 0.04; LALL, p < 0.001), and reduced range of motion in ankle plantarflexion (MALL, p = 0.048). Conclusions: pwMS with mild disability exhibit specific kinematic abnormalities during gait. SPM analysis can detect alterations in the kinematic parameters of gait in pwMS with mild disability.

Biomechanical analysis of barefoot walking and three different sports footwear in children aged between 4 and 6 years old.

The technological transformation and advertising utilized in the footwear industry significantly impact purchasing decisions. The gait properties, barefoot and with shoes, change depending on the footwear structure. The aim of this work is the biomechanical analysis of walking barefoot and with different sports shoes in a controlled group of 12 children between 4 and 6 years old. Kinematic and spatiotemporal variables were analyzed using a BTS motion capture analysis system with the Helen Hayes protocol. Previously, a survey was carried out with 262 families with children between 4 and 6 years old to justify the choice of footwear for this study. No significant differences were found between any of the measured conditions. The kinematic results showed significant differences in the ankle (right sagittal plane p = 0.04, left p < 0.01; right frontal plane p < 0.01, left p < 0.01), knee (right and left sagittal plane p < 0.01) and hip (right sagittal plane p < 0.01, left p = 0.04; right frontal plane p = 0.03). Additionally, the post hoc analysis revealed significant differences between barefoot gait and different footwear. The footwear used for this study and each one's various characteristics are not preponderant in the spatiotemporal and kinematic parameters of the children's gait. Thus, the footwear purchase may be conditioned by its design or composition and other properties may not be relevant.

Symmetry Function in Trans-Tibial Amputees Gait Supplied with the New Concept of Affordable Dynamic Foot Prosthesis—Case Study

The development of modern technologies has made it much easier to regain the ability to walk after losing a lower limb. The variety of prosthetic feet available on the market allows for optimal choice and appropriate adjustment of the foot prosthesis to the trans-tibial amputee patient’s needs. Unfortunately, the best solutions are often not available to everyone due to their high prices. This study compares the gait patterns of patients using the new concept of an affordable dynamic foot with those of other commonly available but much more expensive foot prostheses. The kinematic and spatio-temporal parameters of gait obtained using the motion capture system were analyzed. For a clear picture of changes in bilateral deficits during gait for the pelvis, hip, knee, and ankle joints, the symmetry function was used. The results indicate that the new and cheaper concept of foot prostheses offers a very similar level of gait quality to that provided by more expensive and popular solutions. The authors suggest that the use of symmetry function thresholds of 10% does not work for amputees.

Convolutional Neural Network for Estimating Spatiotemporal and Kinematic Gait Parameters using a Single Inertial Sensor.

Lower limb disability severely impacts gait, thus requiring clinical interventions. Inertial sensor systems offer the potential for objective monitoring and assessment of gait in and out of the clinic. However, it is imperative such systems are capable of measuring important gait parameters while being minimally obtrusive (requiring few sensors). This work used convolutional neural networks to estimate a set of six spatiotemporal and kinematic gait parameters based on raw inertial sensor data. This differs from previous work which either was limited to spatiotemporal parameters or required conventional strap-down integration techniques to estimate kinematic parameters. Additionally, we investigated a data segmentation method which does not rely on gait event detection, further supporting its applicability in real-world settings.Preliminary results demonstrate our model achieved high accuracy on a mix of spatiotemporal and kinematic gait parameters, either meeting or exceeding benchmarks based on literature. We achieved 0.04 ± 0.03 mean absolute error for stance-time symmetry ratio and an absolute error of 4.78 ± 4.78, 4.50 ± 4.33, and 6.47 ± 7.37cm for right and left step length and stride length, respectively. Lastly, errors for knee and hip ranges of motion were 2.31 ± 4.20 and 1.73 ± 1.93°, respectively. The results suggest that machine learning can be a useful tool for long-term monitoring of gait using a single inertial sensor to estimate measures of gait quality.

Estimation of Spatiotemporal Gait Parameters in Walking on a Photoelectric System: Validation on Healthy Children by Standard Gait Analysis.

The use of stereophotogrammetry systems is challenging when targeting children's gait analysis due to the time required and the need to keep physical markers in place. For this reason, marker-less photoelectric systems appear to be a solution for accurate and fast gait analysis in youth. The aim of this study is to validate a photoelectric system and its configurations (LED filter setting) on healthy children, comparing the kinematic gait parameters with those obtained from a three-dimensional stereophotogrammetry system. Twenty-seven healthy children were enrolled. Three LED filter settings for the OptoGait were compared to the BTS P6000. The analysis included the non-parametric 80% limits of agreement and the intraclass correlation coefficient (ICC). Additionally, normalised limits of agreement and bias (NLoAs and Nbias) were compared to the clinical experience of physical therapists (i.e., assuming an error lower than 5% is acceptable). ICCs showed excellent consistency for most of the parameters and filter settings; NLoAs varied between 1.39% and 12.62%. An inverse association between the number of LEDs for filter setting and the bias values was also observed. Observations confirm the validity of the OptoGait system for the evaluation of spatiotemporal gait parameters in children.