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Context: Single- and dual-task walking gait assessments have been used to identify persistent movement and cognitive dysfunction among athletes with concussions. However, it is unclear whether previous ankle sprain injuries confound these outcomes during baseline testing. The purpose of this study was to determine the effects of (1) ankle sprain history and (2) time since prior ankle sprain injury on single- and dual-task spatiotemporal gait outcomes and cognitive measures. Design: Cross- sectional study. Methods: We assessed 60 college Division-I athletes (31 with ankle sprain history; 13 females and 18 males, 19.3 [0.8] y; 29 with no ankle sprain history, 14 females and 15 males, 19.7 [0.9] y) who completed injury history forms and underwent concussion baseline testing. Athletes completed single- and dual-task gait assessments by walking back and forth along an 8-m walkway for 40 seconds. Athletes wore a smartphone with an associated mobile application on their lumbar spine to record spatiotemporal gait parameters and dual-task cognitive performance. Separate multivariate analyses of variance were used to assess the effects of ankle sprain injury history on spatiotemporal measures, gait variability, and cognitive performance. We performed a multivariate regression subanalysis on athletes who reported time since injury (n = 23) to assess temporal effects on gait and cognitive performance. Results: Athletes with and without a histoiy of ankle sprains had comparable spatiotemporal and gait variability outcomes during single- (P = .42; P = .13) and dual-task (P = .75; P = .55) conditions. Additionally, ankle sprain injury history did not significantly influence cognitive performance (P = .35). Finally, time since ankle sprain did not significantly affect single- (P = .75) and dual-task gait (P = .69), nor cognitive performance (P = 19). Conclusions: Ankle sprain injury history did not significantly alter spatiotemporal gait outcomes nor cognitive performance during this common clinical assessment. Future studies may consider including athletes with ankle sprain injury history during concussion assessments. [ABSTRACT FROM AUTHOR]

• Maternal immune challenge associated to perinatal anoxia and hindlimbs sensorimotor restriction in rats leads to musculoskeletal and brain damage observed in spastic Cerebral Palsy. • We show that one week exposure to environmental enrichment combined to 15 min daily treadmill training (EETT) from P21 to P28 improved gross locomotion with minor effects on gait parameters. • EETT decreased brain inflammation and astrogliosis, preserved myelination, without major effects on brain microstructure. • EETT upregulated BDNF signaling and modulated the expression of proteins involved in excitatory synaptic function in brain and spinal cord. Cerebral Palsy (CP) is a major cause of motor and cognitive disability in children due to injury to the developing brain. Early intensive sensorimotor rehabilitation has been shown to change brain structure and reduce CP symptoms severity. We combined environmental enrichment (EE) and treadmill training (TT) to observe the effects of a one-week program of sensorimotor stimulation (EETT) in animals exposed to a CP model and explored possible mechanisms involved in the functional recovery. Pregnant Wistar rats were injected with Lipopolysaccharide (LPS − 200 µg/kg) intraperitoneally at embryonic days 18 and 19. At P0, pups of both sexes were exposed to 20′ anoxia at 37 °C. From P2 to P21, hindlimbs were restricted for 16 h/day during the dark cycle. EETT lasted from P21 to P27. TT − 15 min/day at 7 cm/s. EE − 7 days in enriched cages with sensorimotor stimulus. Functional 3D kinematic gait analysis and locomotion were analyzed. At P28, brains were collected for e x-vivo MRI and histological assessment. Neurotrophins and key proteins involved in CNS function were assessed by western blotting. CP model caused gross and skilled locomotor disruption and altered CNS neurochemistry. EETT reversed locomotor dysfunction with minor effects over gait kinematics. EETT also decreased brain inflammation and glial activation, preserved myelination, upregulated BDNF signaling and modulated the expression of proteins involved in excitatory synaptic function in the brain and spinal cord. Using this translational approach based on intensive sensorimotor rehabilitation, we highlight pathways engaged in the early developmental processes improving neurological recovery observed in CP. [ABSTRACT FROM AUTHOR]

Recycled manure solids has emerged as a promising alternative for animal bedding, owing to its economic feasibility, ready availability on farms, and soft, non-abrasive nature. This research aimed to assess the impact of recycled manure solids (RMS) bedding, combined with a conditioner containing 7.5% lime and 6% sodium hydrosulphate, on dairy cow welfare and gait kinematics over three months. Hock and knee injury scores, lameness incidence, and gait kinematic parameters were evaluated for animals housed on cement flooring (Control), RMS bedding (Treatment I), and conditioner-added RMS bedding (Treatment II) on days 0, 45, and 90 of the experiment with six crossbred cows in each group. The results revealed a significant reduction (p < 0.05) in lameness scores (5-point scale) for animals in both the RMS and conditioner-added RMS groups, with scores of 1.09 ± 0.05 and 1.04 ± 0.03, respectively, compared to those on cement floors. Moreover, a noteworthy decrease (p < 0.05) in knee and hock injury scores (4-point scale) was observed in the RMS groups, indicating a potentially positive impact on joint health. Gait kinematic analysis demonstrated that animals in the RMS (1.03 ± 0.04 m/s) and conditioner-added RMS (1.02 ± 0.06 m/s) groups exhibited higher walking speeds and increased step angles (158.59 ± 4.82° and 149.58 ± 3.85°) compared to their cement-floor counterparts. No significant changes (p > 0.05) were observed in stride length, step asymmetry, step length, and step width. The study concluded that the conditioner incorporated recycled manure solids resulting in a substantial decrease in lameness incidence and a reduction in hock and knee injuries among dairy cows. Additionally, the improved gait kinematics observed in non-lame animals suggest that this bedding combination positively influences overall animal well-being. These findings underscore the potential of sustainable bedding practices to enhance both physical health and locomotor behaviour in dairy cattle. [ABSTRACT FROM AUTHOR]

Introduction: Freezing of gait (FOG) is a paroxysmal motor phenomenon that increases in prevalence as Parkinson's disease (PD) progresses. It is associated with a reduced quality of life and an increased risk of falls in this population. Precision-based detection and classification of freezers are critical to developing tailored treatments rooted in kinematic assessments. Methods: This study analyzed instrumented stand-and-walk (SAW) trials from advanced PD patients with STN-DBS. Each patient performed two SAW trials in their OFF Medication--OFF DBS state. For each trial, gait summary statistics from wearable sensors were analyzed by machine learning classification algorithms. These algorithms include k-nearest neighbors, logistic regression, naïve Bayes, random forest, and support vector machines (SVM). Each of these models were selected for their high interpretability. Each algorithm was tasked with classifying patients whose SAW trials MDS-UPDRS FOG subscore was non-zero as assessed by a trained movement disorder specialist. These algorithms' performance was evaluated using stratified five-fold cross-validation. Results: A total of 21 PD subjects were evaluated (average age 64.24 years, 16 males, mean disease duration of 14 years). Fourteen subjects had freezing of gait in the OFF MED/OFF DBS. All machine learning models achieved statistically similar predictive performance (p < 0.05) with high accuracy. Analysis of random forests' feature estimation revealed the top-ten spatiotemporal predictive features utilized in the model: foot strike angle, coronal range of motion [trunk and lumbar], stride length, gait speed, lateral step variability, and toe-off angle. Conclusion: These results indicate that machine learning effectively classifies advanced PD patients as freezers or nonfreezers based on SAW trials in their non-medicated/non-stimulated condition. The machine learning models, specifically random forests, not only rely on but utilize salient spatial and temporal gait features for FOG classification. [ABSTRACT FROM AUTHOR]

The progress in markerless technologies is providing clinicians with tools to shorten the time of assessment rapidly, but raises questions about the potential trade-off in accuracy compared to traditional marker-based systems. This study evaluated the OpenCap system against a traditional marker-based system—Vicon. Our focus was on its performance in capturing walking both toward and away from two iPhone cameras in the same setting, which allowed capturing the Timed Up and Go (TUG) test. The performance of the OpenCap system was compared to that of a standard marker-based system by comparing spatial-temporal and kinematic parameters in 10 participants. The study focused on identifying potential discrepancies in accuracy and comparing results using correlation analysis. Case examples further explored our results. The OpenCap system demonstrated good accuracy in spatial-temporal parameters but faced challenges in accurately capturing kinematic parameters, especially in the walking direction facing away from the cameras. Notably, the two walking directions observed significant differences in pelvic obliquity, hip abduction, and ankle flexion. Our findings suggest areas for improvement in markerless technologies, highlighting their potential in clinical settings. [ABSTRACT FROM AUTHOR]

AbstractTank farm workers involved in nuclear cleanup activities perform physically demanding tasks, typically while wearing heavy personal protective equipment (PPE). Exoskeleton devices have the potential to bring considerable benefit to this industry but have not been thoroughly studied in the context of nuclear cleanup. In this paper, we examine the performance of exoskeletons during a series of tasks emulating jobs performed on tank farms while participants wore PPE commonly deployed by tank farm workers. The goal of this study was to evaluate the effects of commercially available lower-body exoskeletons on a user’s gait kinematics and user perceptions. Three participants each tested three lower-body exoskeletons in a 70-min protocol consisting of level treadmill walking, incline treadmill walking, weighted treadmill walking, a weight lifting session, and a hand tool dexterity task. Results were compared to a no exoskeleton baseline condition and evaluated as individual case studies. The three participants showed a wide spectrum of user preferences and adaptations toward the devices. Individual case studies revealed that some users quickly adapted to select devices for certain tasks while others remained hesitant to use the devices. Temporal effects on gait change and perception were also observed for select participants in device usage over the course of the device session. Device benefit varied between tasks, but no conclusive aggregate trends were observed across devices for all tasks. Evidence suggests that device benefits observed for specific tasks may have been overshadowed by the wide array of tasks used in the protocol. [ABSTRACT FROM AUTHOR]

IntroductionFreezing of gait (FOG) is a paroxysmal motor phenomenon that increases in prevalence as Parkinson’s disease (PD) progresses. It is associated with a reduced quality of life and an increased risk of falls in this population. Precision-based detection and classification of freezers are critical to developing tailored treatments rooted in kinematic assessments.MethodsThis study analyzed instrumented stand-and-walk (SAW) trials from advanced PD patients with STN-DBS. Each patient performed two SAW trials in their OFF Medication—OFF DBS state. For each trial, gait summary statistics from wearable sensors were analyzed by machine learning classification algorithms. These algorithms include k-nearest neighbors, logistic regression, naïve Bayes, random forest, and support vector machines (SVM). Each of these models were selected for their high interpretability. Each algorithm was tasked with classifying patients whose SAW trials MDS-UPDRS FOG subscore was non-zero as assessed by a trained movement disorder specialist. These algorithms’ performance was evaluated using stratified five-fold cross-validation.ResultsA total of 21 PD subjects were evaluated (average age 64.24 years, 16 males, mean disease duration of 14 years). Fourteen subjects had freezing of gait in the OFF MED/OFF DBS. All machine learning models achieved statistically similar predictive performance (p < 0.05) with high accuracy. Analysis of random forests’ feature estimation revealed the top-ten spatiotemporal predictive features utilized in the model: foot strike angle, coronal range of motion [trunk and lumbar], stride length, gait speed, lateral step variability, and toe-off angle.ConclusionThese results indicate that machine learning effectively classifies advanced PD patients as freezers or nonfreezers based on SAW trials in their non-medicated/non-stimulated condition. The machine learning models, specifically random forests, not only rely on but utilize salient spatial and temporal gait features for FOG classification.

The dynamic behavior of pedestrians causes a misalignment problem between the sensor orientation and the walking direction, which hinders the performance of pedestrian dead reckoning (PDR) systems. Pedestrians wearing smartwatches are constantly faced with this problem when running. In this paper, we propose a novel kinematic modeling of arm swing that segments arm swing motion from the movement of the center of mass of the body. The proposed decomposition method allows for effective negation of the sensor outputs due to the redundant motion that obstructs the estimation of the true walking direction. The correct direction vector is computed by deducting the direction vector of the arm swing from that of the entire motion, which are both derived from performing two separate principal component analyses (PCA). The performance of the proposed method was evaluated through several experiments. In the running track experiment, the proposed method demonstrates the best performance, with 57% – 70% performance improvement compared to the existing methods. In the general scenario involving both walking and running, the proposed method outperforms the baseline method by 56%, improving the generality of the PCA-based methods.

Lower-limb gait training (GT) exoskeletons have been successfully used in rehabilitation programs to overcome the burden of locomotor impairment. However, providing suitable net interaction torques to assist patient movements is still a challenge. Previous transparent operation approaches have been tested in treadmill-based GT exoskeletons to improve user-robot interaction. However, it is not yet clear how a transparent lower-limb GT system affects user’s gait kinematics during overground walking, which unlike treadmill-based systems, requires active participation of the subjects to maintain stability. In this study, we implemented a transparent operation strategy on the ExoRoboWalker, an overground GT exoskeleton, to investigate its effect on the user’s gait. The approach employs a feedback zero-torque controller with feedforward compensation for the exoskeleton’s dynamics and actuators’ impedance. We analyzed the data of five healthy subjects walking overground with the exoskeleton in transparent mode (ExoTransp) and non-transparent mode (ExoOff) and walking without exoskeleton (NoExo). The transparent controller reduced the user-robot interaction torque and improved the user’s gait kinematics relative to ExoOff. No significant difference in stride length is observed between ExoTransp and NoExo (p = 0.129). However, the subjects showed a significant difference in cadence between ExoTransp (50.9± 1.1 steps/min) and NoExo (93.7 ± 8.7 steps/min) (p = 0.015), but not between ExoTransp and ExoOff (p = 0.644). Results suggest that subjects wearing the exoskeleton adjust their gait as in an attention-demanding task changing the spatiotemporal gait characteristics likely to improve gait balance.

Individuals with lower limb loss often walk with altered/asymmetric movement mechanics, postulated as a catalyst for development of low back and knee pain. Here, the authors simultaneously investigated trunk-pelvic movement patterns and lower limb joint kinematics and kinetics among 38 males with traumatic, unilateral lower limb loss (23 transtibial and 15 transfemoral), and 15 males without limb loss, at a self-selected and 2 standardized (1.0 and 1.6 m/s) speeds. Individuals with versus without lower limb loss walked with greater trunk range of motion in the frontal and transverse planes at all speeds (despite ∼10% slower self-selected speeds). At all speeds, individuals with versus without limb loss exhibited +29% larger medial ground reaction forces, and at 1.6 m/s also exhibited +50% to 110% larger vertical hip power generation, +27% to 80% larger vertical hip power absorption, and +21% to 90% larger medial–lateral hip power absorption. Moreover, pervasive biomechanical differences between transtibial versus transfemoral limb loss identify amputation-level movement strategies. Overall, greater demands on the musculoskeletal system across walking speeds, particularly at the hip, knee, and low back, highlight potential risk factors for the development/recurrence of prevalent secondary musculoskeletal conditions (eg, joint degeneration and pain) following limb loss. [ABSTRACT FROM AUTHOR]

Purpose: We conducted muscle synergy and gait analyses in a monoplegic patient whose gait function improved through training, to explore the possibility of using these parameters as indicators of training. Case presentation: A 49-year-old male had monoplegia of the right lower limb caused by infarction of the left paracentral lobule. After 2 months of training, he was able to walk and returned to work. Methods: Consecutive analyses were done after admission. Muscle synergy analysis: during walking, surface electromyograms of gluteus maximus, quadriceps femoris, adductor femoris, hamstrings, tibialis anterior, medial/lateral gastrocnemius, and soleus on both sides were recorded and processed for non-negative matrix factorization (NNMF) analysis. Gait analysis: markers were placed at foot, and walking movements were video recorded as changes in position of the markers. Results: Compared with three muscle synergies detected on the non-paretic side, two muscle synergies were extracted on the paretic side at admission, and the number increased to three and then four with progress in rehabilitation training. Changes in weighting and activity of the muscle synergies were greater on the non-paretic side than on the paretic side. With training, the knee joint flexor and the ankle dorsiflexor activities on the paretic side and the gluteus maximus activity on the non-paretic side increased during swing phase as shown by weight changes of muscle synergies, and gait analysis showed increased knee joint flexion and ankle joint dorsiflexion during swing phase in the paretic limb. On the non-paretic side, however, variability of muscle activity was observed, and three or four muscle synergies were extracted depending on the number of strides analyzed. Conclusion: The number of muscle synergies is considered to contribute to motor control. Rehabilitation training improves gait by increasing the number of muscle synergies on the paretic side and changing the weights of the muscles constituting the muscle synergies. From the changes on the non-paretic side, we propose the existence of compensatory mechanisms also on the nonparetic side. In muscle synergy analysis, in addition to the filters, the number of strides used in each analysis set has to be examined. This report highlights the issues of NNMF as analytical methods in gait training for stroke patients. [ABSTRACT FROM AUTHOR]

Improving independent mobility in people with various gait abnormalities is a major goal of rehabilitation therapy. While quantitative gait assessment is crucial to provide meaningful feedback on each treatment, many gait wearables have been validated with the standard method. However, none of the studies focused on validation of gait characterization in different classes of the pathological population compared with the control population. Hence, a novel wearable device called Gait Watch, worn on both the lower limbs, to estimate spatiotemporal and kinematic parameters of heterogeneous gait-impaired groups has been evaluated and its outcomes have been statistically analyzed. This article presents a statistical validation of gait dynamics of the control group and patients diagnosed with cerebral vascular accident, traumatic brain injury, peripheral nervous system, psychiatric issues, and seizures. Using the preliminary analysis results, a set of descriptive variables that allow for disease differentiation was selected to provide appropriate treatment to patients with various ailments and enhance their gait quality. The extraction of clinically significant gait parameters of interest using proposed Gait Watch would ascertain various neurological conditions as well as accurately quantify the extent of the difference in various gait parameters in subjects with different gait conditions when compared with the control group. [ABSTRACT FROM AUTHOR]

Abstract Background Lower limb malalignment is associated with gait kinematics, but there is limited information on the relationship between gait kinematics and tibial torsion in individuals with knee osteoarthritis (OA). This study aimed to investigate possible associations between tibial torsion and early stance kinematics during gait in people with mild and moderate medial knee OA. Methods Forty-seven participants (age: 62.1 ± 6.0 years; female/male: 37/10) diagnosed with medial knee OA were recruited from a regional hospital. Thirty of them had mild and seventeen had moderate knee OA. Lower limb alignment including tibial torsion and valgus/varus alignment were assessed by an EOS biplaner X-ray system with participants in weight-bearing position. Lower limb kinematics during gait was captured using the Vicon motion analysis system. The associations were estimated by partial Pearson correlation coefficient test. Results Our results indicated that external tibial torsion was related to early stance knee flexion excursion in participants with moderate knee OA (r = -0.58, p = 0.048), but not in participants with mild knee OA (r = 0.34, p = 0.102). External tibial torsion was associated with external foot progression angle (r = 0.48, p = 0.001), and knee varus/valgus alignment was associated with knee flexion excursion (r = -0.39, p = 0.010) in all participants. Conclusions Both horizontal and frontal lower limb alignments were associated with knee flexion excursion at early stance of gait cycle in participants with medial knee OA. The distal rotational profile of lower limb would likely affect knee motion in sagittal plane. It implies that people with moderate knee OA could possibly benefit from correction of rotational alignment of lower limb.

The progress in markerless technologies is providing clinicians with tools to shorten the time of assessment rapidly, but raises questions about the potential trade-off in accuracy compared to traditional marker-based systems. This study evaluated the OpenCap system against a traditional marker-based system—Vicon. Our focus was on its performance in capturing walking both toward and away from two iPhone cameras in the same setting, which allowed capturing the Timed Up and Go (TUG) test. The performance of the OpenCap system was compared to that of a standard marker-based system by comparing spatial-temporal and kinematic parameters in 10 participants. The study focused on identifying potential discrepancies in accuracy and comparing results using correlation analysis. Case examples further explored our results. The OpenCap system demonstrated good accuracy in spatial-temporal parameters but faced challenges in accurately capturing kinematic parameters, especially in the walking direction facing away from the cameras. Notably, the two walking directions observed significant differences in pelvic obliquity, hip abduction, and ankle flexion. Our findings suggest areas for improvement in markerless technologies, highlighting their potential in clinical settings.

Objective: The spatiotemporal gait changes in advanced Parkinson's disease (PD) remain a treatment challenge and have variable responses to L-dopa and subthalamic deep brain stimulation (STN-DBS). The purpose of this study was to determine whether low-frequency STN-DBS (LFS; 60Hz) elicits a differential response to high-frequency STN-DBS (HFS; 180Hz) in spatiotemporal gait kinematics. Methods: Advanced PD subjects with chronic STN-DBS were evaluated in both theOFF andONmedication states with LFS and HFS stimulation. Randomization of electrode contact pairs and frequency conditions was conducted. Instrumented Stand and Walk assessments were carried out for every stimulation/medication condition. LM-ANOVA was employed for analysis. Results: Twenty-two PD subjects participated in the study, with a mean age (SD) of 63.9 years. Significant interactions between frequency (both LFS and HFS) and electrode contact pairs (particularly ventrally located contacts) were observed for both spatial (foot elevation, toe-off angle, stride length) and temporal (foot speed, stance, single limb support (SLS) and foot swing) gait parameters. A synergistic effect was also demonstrated with L-dopa and both HFS and LFS for right SLS, left stance, left foot swing, right toe-off angle, and left arm range of motion. HFS produced significant improvement in trunk and lumbar range of motion compared to LFS. Conclusion: The study provides evidence of synergismof L-dopa and STN-DBS on lower limb spatial and temporal measures in advanced PD. HFS and LFS STN-DBS produced equivalent effects among all other tested lower limb gait features. HFS produced significant trunk and lumbar kinematic improvements. [ABSTRACT FROM AUTHOR]

Semi‐arboreal mammals must routinely cope with the differing biomechanical challenges of terrestrial versus arboreal locomotion; however, it is not clear to what extent semi‐arboreal mammals adjust footfall patterns when moving on different substrates. We opportunistically filmed quadrupedal locomotion (n = 132 walking strides) of semi‐arboreal red pandas (Ailurus fulgens; n = 3) housed at Cleveland Metroparks Zoo and examined the effects of substrate type on spatiotemporal gait kinematic variables using linear mixed models. We further investigated the effects of substrate diameter and orientation on arboreal gait kinematics. Red pandas exclusively used lateral sequence (LS) gaits and most frequently utilized LS lateral couplet gaits across terrestrial and arboreal substrates. Red pandas moved significantly slower (p < 0.001), and controlling for speed, had significantly greater relative stride length (p < 0.001), mean stride duration (p = 0.002), mean duty factor (p < 0.001), and mean number of supporting limbs (p < 0.001) during arboreal locomotion. Arboreal strides on inclined substrates were characterized by significantly faster relative speeds and increased limb phase values compared with those horizontal and declined substrates. These kinematics adjustments help to reduce substrate oscillations thereby promoting stability on potentially precarious arboreal substrates. Red panda limb phase values are similar to those of (primarily terrestrial) Carnivora examined to date. Despite the similarity in footfall patterns during arboreal and terrestrial locomotion, flexibility in other kinematic variables is important for semi‐arboreal red pandas that must navigate disparate biomechanical challenges inherent to arboreal versus terrestrial locomotion. [ABSTRACT FROM AUTHOR]

Background: Lower limb malalignment is associated with gait kinematics, but there is limited information on the relationship between gait kinematics and tibial torsion in individuals with knee osteoarthritis (OA). This study aimed to investigate possible associations between tibial torsion and early stance kinematics during gait in people with mild and moderate medial knee OA. Methods: Forty-seven participants (age: 62.1 ± 6.0 years; female/male: 37/10) diagnosed with medial knee OA were recruited from a regional hospital. Thirty of them had mild and seventeen had moderate knee OA. Lower limb alignment including tibial torsion and valgus/varus alignment were assessed by an EOS biplaner X-ray system with participants in weight-bearing position. Lower limb kinematics during gait was captured using the Vicon motion analysis system. The associations were estimated by partial Pearson correlation coefficient test. Results: Our results indicated that external tibial torsion was related to early stance knee flexion excursion in participants with moderate knee OA (r = -0.58, p = 0.048), but not in participants with mild knee OA (r = 0.34, p = 0.102). External tibial torsion was associated with external foot progression angle (r = 0.48, p = 0.001), and knee varus/valgus alignment was associated with knee flexion excursion (r = -0.39, p = 0.010) in all participants. Conclusions: Both horizontal and frontal lower limb alignments were associated with knee flexion excursion at early stance of gait cycle in participants with medial knee OA. The distal rotational profile of lower limb would likely affect knee motion in sagittal plane. It implies that people with moderate knee OA could possibly benefit from correction of rotational alignment of lower limb. [ABSTRACT FROM AUTHOR]

Three-dimensional (3D) cameras used for gait assessment obviate the need for bodily markers or sensors, making them particularly interesting for clinical applications. Due to their limited field of view, their application has predominantly focused on evaluating gait patterns within short walking distances. However, assessment of gait consistency requires testing over a longer walking distance. The aim of this study is to validate the accuracy for gait assessment of a previously developed method that determines walking spatiotemporal parameters and kinematics measured with a 3D camera mounted on a mobile robot base (ROBOGait). Walking parameters measured with this system were compared with measurements with Xsens IMUs. The experiments were performed on a non-linear corridor of approximately 50 m, resembling the environment of a conventional rehabilitation facility. Eleven individuals exhibiting normal motor function were recruited to walk and to simulate gait patterns representative of common neurological conditions: Cerebral Palsy, Multiple Sclerosis, and Cerebellar Ataxia. Generalized estimating equations were used to determine statistical differences between the measurement systems and between walking conditions. When comparing walking parameters between paired measures of the systems, significant differences were found for eight out of 18 descriptors: range of motion (ROM) of trunk and pelvis tilt, maximum knee flexion in loading response, knee position at toe-off, stride length, step time, cadence; and stance duration. When analyzing how ROBOGait can distinguish simulated pathological gait from physiological gait, a mean accuracy of 70.4%, a sensitivity of 49.3%, and a specificity of 74.4% were found when compared with the Xsens system. The most important gait abnormalities related to the clinical conditions were successfully detected by ROBOGait. The descriptors that best distinguished simulated pathological walking from normal walking in both systems were step width and stride length. This study underscores the promising potential of 3D cameras and encourages exploring their use in clinical gait analysis. [ABSTRACT FROM AUTHOR]

ObjectiveThe spatiotemporal gait changes in advanced Parkinson's disease (PD) remain a treatment challenge and have variable responses to L-dopa and subthalamic deep brain stimulation (STN-DBS). The purpose of this study was to determine whether low-frequency STN-DBS (LFS; 60 Hz) elicits a differential response to high-frequency STN-DBS (HFS; 180 Hz) in spatiotemporal gait kinematics.MethodsAdvanced PD subjects with chronic STN-DBS were evaluated in both the OFF and ON medication states with LFS and HFS stimulation. Randomization of electrode contact pairs and frequency conditions was conducted. Instrumented Stand and Walk assessments were carried out for every stimulation/medication condition. LM-ANOVA was employed for analysis.ResultsTwenty-two PD subjects participated in the study, with a mean age (SD) of 63.9 years. Significant interactions between frequency (both LFS and HFS) and electrode contact pairs (particularly ventrally located contacts) were observed for both spatial (foot elevation, toe-off angle, stride length) and temporal (foot speed, stance, single limb support (SLS) and foot swing) gait parameters. A synergistic effect was also demonstrated with L-dopa and both HFS and LFS for right SLS, left stance, left foot swing, right toe-off angle, and left arm range of motion. HFS produced significant improvement in trunk and lumbar range of motion compared to LFS.ConclusionThe study provides evidence of synergism of L-dopa and STN-DBS on lower limb spatial and temporal measures in advanced PD. HFS and LFS STN-DBS produced equivalent effects among all other tested lower limb gait features. HFS produced significant trunk and lumbar kinematic improvements.

This study aimed to assess whether the Teslasuit, a wearable motion-sensing technology, could detect subtle changes in gait following slip perturbations comparable to an infrared motion capture system. A total of 12 participants wore Teslasuits equipped with inertial measurement units (IMUs) and reflective markers. The experiments were conducted using the Motek GRAIL system, which allowed for accurate timing of slip perturbations during heel strikes. The data from Teslasuit and camera systems were analyzed using statistical parameter mapping (SPM) to compare gait patterns from the two systems and before and after slip. We found significant changes in ankle angles and moments before and after slip perturbations. We also found that step width significantly increased after slip perturbations (p = 0.03) and total double support time significantly decreased after slip (p = 0.01). However, we found that initial double support time significantly increased after slip (p = 0.01). However, there were no significant differences observed between the Teslasuit and motion capture systems in terms of kinematic curves for ankle, knee, and hip movements. The Teslasuit showed promise as an alternative to camera-based motion capture systems for assessing ankle, knee, and hip kinematics during slips. However, some limitations were noted, including kinematics magnitude differences between the two systems. The findings of this study contribute to the understanding of gait adaptations due to sequential slips and potential use of Teslasuit for fall prevention strategies, such as perturbation training. [ABSTRACT FROM AUTHOR]

BACKGROUND: Clinical gait analysis of sagittal plane lower-limb kinematics using video images is a quantitative tool for clinicians. However, the reliability and validity of limb kinematics after stroke using video images has not been fully investigated. OBJECTIVE: This study aimed to examine the within-session inter-rater reliability and criterion-related validity of lower limb angles measured in sagittal plane images captured using a smartphone for assessing post-stroke gait and to determine which asymmetric parameters are associated with faster gait velocity. METHODS: Thirty-two patients with stroke were included; video images were recorded as they walked at their preferred pace for 1–3 cycles. Lower limb angles (contact, push-off, and excursion angles) and degree of asymmetry were determined based on video images using markers of acromion, greater trochanter, and fifth metatarsal head. Measurement reliability was calculated using the two-way random effects model of intraclass correlation coefficients and minimal detectable change. The criterion validity investigated Pearson's correlation between lower limb angles and their asymmetry and gait velocity. RESULTS: The lower value of the 95% confidence interval of intraclass correlation coefficients (2.3) of the lower limb was 0.891, and the maximum minimal detectable change was 9.6 degrees. Push-off angle showed a moderate-to-strong correlation with gait velocity, whereas the asymmetry of the push-off angle showed a weak correlation with gait velocity. CONCLUSIONS: Assessing post-stroke gait utilizing video images using a smartphone is feasible. The push-off angle, in particular, may provide insight into the clinical assessment of post-stroke gait. [ABSTRACT FROM AUTHOR]

Lower limb exoskeletons and orthoses have been increasingly used to assist the user during gait rehabilitation through torque transmission and motor stability. However, the physical human-robot interface (HRi) has not been properly addressed. Current orthoses lead to spurious forces at the HRi that cause adverse effects and high abandonment rates. This study aims to assess and compare, in a holistic approach, human-robot joint misalignment and gait kinematics in three fixation designs of ankle-foot orthoses (AFOs). These are AFOs with a frontal shin guard (F-AFO), lateral shin guard (L-AFO), and the ankle modulus of the H2 exoskeleton (H2-AFO). An experimental protocol was implemented to assess misalignment, fixation displacement, pressure interactions, user-perceived comfort, and gait kinematics during walking with the three AFOs. The F-AFO showed reduced vertical misalignment (peak of 1.37 ± 0.90 cm, p-value < 0.05), interactions (median pressures of 0.39–3.12 kPa), and higher user-perceived comfort (p-value < 0.05) when compared to H2-AFO (peak misalignment of 2.95 ± 0.64 and pressures ranging from 3.19 to 19.78 kPa). F-AFO also improves the L-AFO in pressure (median pressures ranging from 8.64 to 10.83 kPa) and comfort (p-value < 0.05). All AFOs significantly modified hip joint angle regarding control gait (p-value < 0.01), while the H2-AFO also affected knee joint angle (p-value < 0.01) and gait spatiotemporal parameters (p-value < 0.05). Overall, findings indicate that an AFO with a frontal shin guard and a sports shoe is effective at reducing misalignment and pressure at the HRI, increasing comfort with slight changes in gait kinematics.

Three-dimensional (3D) cameras used for gait assessment obviate the need for bodily markers or sensors, making them particularly interesting for clinical applications. Due to their limited field of view, their application has predominantly focused on evaluating gait patterns within short walking distances. However, assessment of gait consistency requires testing over a longer walking distance. The aim of this study is to validate the accuracy for gait assessment of a previously developed method that determines walking spatiotemporal parameters and kinematics measured with a 3D camera mounted on a mobile robot base (ROBOGait). Walking parameters measured with this system were compared with measurements with Xsens IMUs. The experiments were performed on a non-linear corridor of approximately 50 m, resembling the environment of a conventional rehabilitation facility. Eleven individuals exhibiting normal motor function were recruited to walk and to simulate gait patterns representative of common neurological conditions: Cerebral Palsy, Multiple Sclerosis, and Cerebellar Ataxia. Generalized estimating equations were used to determine statistical differences between the measurement systems and between walking conditions. When comparing walking parameters between paired measures of the systems, significant differences were found for eight out of 18 descriptors: range of motion (ROM) of trunk and pelvis tilt, maximum knee flexion in loading response, knee position at toe-off, stride length, step time, cadence; and stance duration. When analyzing how ROBOGait can distinguish simulated pathological gait from physiological gait, a mean accuracy of 70.4%, a sensitivity of 49.3%, and a specificity of 74.4% were found when compared with the Xsens system. The most important gait abnormalities related to the clinical conditions were successfully detected by ROBOGait. The descriptors that best distinguished simulated pathological walking from normal walking in both systems were step width and stride length. This study underscores the promising potential of 3D cameras and encourages exploring their use in clinical gait analysis.

Classification of gait disorders in cerebral palsy (CP) remains challenging. The Winters, Gage, and Hicks (WGH) is a commonly used classification system for unilateral CP regarding the gait patterns (lower limb kinematics) solely in the sagittal plane. Due to the high number of unclassified patients, this classification system might fail to depict all gait disorders accurately. As the information on trunk/pelvic movements, frontal and transverse planes, and kinetics are disregarded in WGH, 3D instrumented gait analysis (IGA) for further characterization is necessary. The objective of this study was a detailed analysis of patients with unilateral CP using IGA taking all planes/degrees of freedom into account including pelvic and trunk movements. A total of 89 individuals with unilateral CP matched the inclusion criteria and were classified by WGH. Subtype-specific differences were analyzed. The most remarkable findings, in addition to the established WGH subtype-specific deviations, were pelvic obliquity and pelvic retraction in all WGH types. Furthermore, the unclassified individuals showed altered hip rotation moments and pelvic retraction almost throughout the whole gait cycle. Transversal malalignment and proximal involvement are relevant in all individuals with unilateral CP. Further studies should focus on WGH type-specific rotational malalignment assessment (static vs. dynamic, femoral vs. tibial) including therapeutic effects and potential subtype-specific compensation mechanisms and/or tertiary deviations of the sound limb. [ABSTRACT FROM AUTHOR]

The use of inertial measurement units (IMUs) to compute gait outputs, such as the 3D lower-limb kinematics is of huge potential, but no consensus on the procedures and algorithms exists. This study aimed at evaluating the validity of a 7-IMUs system against the optoelectronic system. Ten asymptomatic subjects were included. They wore IMUs on their feet, shanks, thighs and pelvis. The IMUs were embedded in clusters with reflective markers. Reference kinematics was computed from anatomical markers. Gait kinematics was obtained from accelerometer and gyroscope data after sensor orientation estimation and sensor-to-segment (S2S) calibration steps. The S2S calibration steps were also applied to the cluster data. IMU-based and cluster-based kinematics were compared to the reference through root mean square errors (RMSEs), centered RMSEs (after mean removal), correlation coefficients (CCs) and differences in amplitude. The mean RMSE and centered RMSE were, respectively, 7.5° and 4.0° for IMU-kinematics, and 7.9° and 3.8° for cluster-kinematics. Very good CCs were found in the sagittal plane for both IMUs and cluster-based kinematics at the hip, knee and ankle levels (CCs > 0.85). The overall mean amplitude difference was about 7°. These results reflected good accordance in our system with the reference, especially in the sagittal plane, but the presence of offsets requires caution for clinical use. [ABSTRACT FROM AUTHOR]

Treadmills are widely used in rehabilitation and gait analysis. However, previous studies have reported differences in terms of kinematics and kinetics between treadmill and overground walking due to physical and psychological factors. The aim of this study was to analyze gait differences due to only the physical factors of treadmill walking. Walking motions of a male participant were captured at 0.63, 1.05, 1.33, and 3.91 m/s. A gait controller of a virtual subject (63 kg) was trained for ground walking at each walking speed via a reinforcement learning method. Additionally, the gait controllers of virtual subjects with different body masses of 47, 79, and 94 kg were trained for ground walking at 1.05 m/s. The gait controllers and virtual subjects were tested for treadmill walking, and their lower-limb joint kinematics were compared with those for ground walking. Treadmill conditions of maximum allowable belt force and feedback control frequency of belt speed were set between 100 and 500 N and between 10 and 50 Hz, respectively. The lower-limb kinematics were identical between the two conditions regardless of the body mass and walking speed when the belt could provide a constant speed regardless of external perturbation in the ideal treadmill. However, kinematic differences were observed when simulation was performed on a non-ideal treadmill with a relatively low belt force and control frequency of belt speed. The root-mean-square differences of the hip, knee, and ankle flexion angles between treadmill and overground running at 3.91 m/s increased by 3.76°, 3.73°, and 4.91°, respectively, when the maximum belt force and control frequency decreased from infinity to 100 N and 10 Hz, respectively. At a maximum belt force exceeding 400 N or a control frequency exceeding 25 Hz, the root-mean-square difference of the joint kinematics was less than 3° for all body masses and walking speeds. Virtual subjects walking on non-ideal treadmills showed different joint kinematics from ground walking. The study identified physical factors that differentiate treadmill walking from overground walking, and suggested the belt forces and control frequencies of a treadmill to achieve the desired limit of kinematic differences.

This study aimed to assess whether the Teslasuit, a wearable motion-sensing technology, could detect subtle changes in gait following slip perturbations comparable to an infrared motion capture system. A total of 12 participants wore Teslasuits equipped with inertial measurement units (IMUs) and reflective markers. The experiments were conducted using the Motek GRAIL system, which allowed for accurate timing of slip perturbations during heel strikes. The data from Teslasuit and camera systems were analyzed using statistical parameter mapping (SPM) to compare gait patterns from the two systems and before and after slip. We found significant changes in ankle angles and moments before and after slip perturbations. We also found that step width significantly increased after slip perturbations (p = 0.03) and total double support time significantly decreased after slip (p = 0.01). However, we found that initial double support time significantly increased after slip (p = 0.01). However, there were no significant differences observed between the Teslasuit and motion capture systems in terms of kinematic curves for ankle, knee, and hip movements. The Teslasuit showed promise as an alternative to camera-based motion capture systems for assessing ankle, knee, and hip kinematics during slips. However, some limitations were noted, including kinematics magnitude differences between the two systems. The findings of this study contribute to the understanding of gait adaptations due to sequential slips and potential use of Teslasuit for fall prevention strategies, such as perturbation training.

Background: Changes in gait characteristics have been reported in people with chronic neck pain (CNP).Research Question: Can we classify people with and without CNP by training machine learning models with Inertial Measurement Units (IMU)-based gait kinematic data?Methods: Eighteen asymptomatic individuals and 21 participants with CNP were recruited for the study and performed two gait trajectories, (1) linear walking with their head straight (single-task) and (2) linear walking with continuous head-rotation (dual-task). Kinematic data were recorded from three IMU sensors attached to the forehead, upper thoracic spine (T1), and lower thoracic spine (T12). Temporal and spectral features were extracted to generate the dataset for both single- and dual-task gait. To evaluate the most significant features and simultaneously reduce the dataset size, the Neighbourhood Component Analysis (NCA) method was utilized. Three supervised models were applied, including K-Nearest Neighbour, Support Vector Machine, and Linear Discriminant Analysis to test the performance of the most important temporal and spectral features.Results: The performance of all classifiers increased after the implementation of NCA. The best performance was achieved by NCA-Support Vector Machine with an accuracy of 86.85%, specificity of 83.30%, and sensitivity of 92.85% during the dual-task gait using only nine features.Significance: The results present a data-driven approach and machine learning-based methods to identify test conditions and features from high-dimensional data obtained during gait for the classification of people with and without CNP. [ABSTRACT FROM AUTHOR]

There are conflicting results regarding the changes in spatio-temporal gait parameters during the 6-min walk test (6MWT) as indicators of gait-related motor performance fatigability (PF) in people with Multiple Sclerosis (pwMS). To further analyze if gait-related motor PF can be quantified using instrumented gait analysis during the 6MWT, we investigated: (i) whether gait parameters recorded during the first or second minute were more stable and thus the better baseline to assess motor PF and (ii) if the minimum toe clearance (MTC) together with "classical" spatio-temporal gait parameters can be used to quantify motor PF in pwMS. Nineteen mildly affected pwMS [12 women/7 men; 47.8 ± 9.0 years; the Expanded Disability Status Scale (EDSS): 2.7 ± 1.0] and 24 healthy controls (HC; 15 women/9 men; 48.8 ± 7.6 years) completed the 6MWT equipped with inertial measurement units. Data were analyzed using the attractor method to compare the stability of gait parameters and, besides "classical" spatio-temporal gait parameters, the MTC was calculated as a potential new marker for motor PF in pwMS as this was shown in healthy older adults. It was found that (i) gait parameters were more stable in the second than in the first minute and (ii) gait-related motor PF could not be detected based on spatio-temporal gait parameters, including the MTC. Descriptive analysis indicated a decrease in MTC variability, which is assumed to be indicative for motor PF, toward the end of the 6MWT in some pwMS. Future studies should investigate gait parameters for the assessment of motor PF in pwMS recorded during more intense and/or longer walking protocols, taking the level of disability into account. Furthermore, using gait parameters recorded in the first minute of the 6MWT as a baseline for the assessment of motor PF should be avoided. [ABSTRACT FROM AUTHOR]

Purpose: We have previously observed substantially higher oxygen uptake in soldiers walking on terrain at night than when performing the same walk in bright daylight. The aims of the present study were to investigate the influence of vision on mechanical efficiency during slow, horizontal, constant-speed walking, and to determine whether any vision influence is modified by load carriage. Methods: Each subject (n = 15) walked (3.3 km/h) for 10 min on a treadmill in four different conditions: (1) full vision, no carried load, (2) no vision, no carried load, (3) full vision with a 25.5-kg rucksack, (4) no vision with a 25.5-kg rucksack. Results: Oxygen uptake was 0.94 ± 0.12 l/min in condition (1), 1.15 ± 0.20 l/min in (2), 1.15 ± 0.12 l/min in (3) and 1.35 ± 0.19 l/min in (4). Thus, lack of vision increased oxygen uptake by about 19%. Analyses of movement pattern, by use of optical markers attached to the limbs and torso, revealed considerably shorter step length (12 and 10%) in the no vision (2 and 4) than full vision conditions (1 and 3). No vision conditions (2 and 4) increased step width by 6 and 6%, and increased vertical foot clearance by 20 and 16% compared to full vision conditions (1 and 3). Conclusion: The results suggest that vision has a marked influence on mechanical efficiency even during entrained, repetitive movements performed on an obstacle-free horizontal surface under highly predictable conditions. [ABSTRACT FROM AUTHOR]

Wearable inertial sensor-based motion analysis systems are promising alternatives to standard camera-based motion capture systems for the measurement of gait parameters and joint kinematics. These wearable sensors, unlike camera-based gold standard systems, find usefulness in outdoor natural environment along with confined indoor laboratory-based environment due to miniature size and wireless data transmission. This study reports validation of our developed (i-Sens) wearable motion analysis system against standard motion capture system. Gait analysis was performed at self-selected speed on non-disabled volunteers in indoor (n = 15) and outdoor (n = 8) environments. Two i-Sens units were placed at the level of knee and hip along with passive markers (for indoor study only) for simultaneous 3D motion capture using a motion capture system. Mean absolute percentage error (MAPE) was computed for spatiotemporal parameters from the i-Sens system versus the motion capture system as a true reference. Mean and standard deviation of kinematic data for a gait cycle were plotted for both systems against normative data. Joint kinematics data were analyzed to compute the root mean squared error (RMSE) and Pearson's correlation coefficient. Kinematic plots indicate a high degree of accuracy of the i-Sens system with the reference system. Excellent positive correlation was observed between the two systems in terms of hip and knee joint angles (Indoor: hip 3.98° ± 1.03°, knee 6.48° ± 1.91°, Outdoor: hip 3.94° ± 0.78°, knee 5.82° ± 0.99°) with low RMSE. Reliability characteristics (defined using standard statistical thresholds of MAPE) of stride length, cadence, walking speed in both outdoor and indoor environment were well within the "Good" category. The i-Sens system has emerged as a potentially cost-effective, valid, accurate, and reliable alternative to expensive, standard motion capture systems for gait analysis. Further clinical trials using the i-Sens system are warranted on participants across different age groups. [ABSTRACT FROM AUTHOR]

There are conflicting results regarding the changes in spatio-temporal gait parameters during the 6-min walk test (6MWT) as indicators of gait-related motor performance fatigability (PF) in people with Multiple Sclerosis (pwMS). To further analyze if gait-related motor PF can be quantified using instrumented gait analysis during the 6MWT, we investigated: (i) whether gait parameters recorded during the first or second minute were more stable and thus the better baseline to assess motor PF and (ii) if the minimum toe clearance (MTC) together with “classical” spatio-temporal gait parameters can be used to quantify motor PF in pwMS. Nineteen mildly affected pwMS [12 women/7 men; 47.8 ± 9.0 years; the Expanded Disability Status Scale (EDSS): 2.7 ± 1.0] and 24 healthy controls (HC; 15 women/9 men; 48.8 ± 7.6 years) completed the 6MWT equipped with inertial measurement units. Data were analyzed using the attractor method to compare the stability of gait parameters and, besides “classical” spatio-temporal gait parameters, the MTC was calculated as a potential new marker for motor PF in pwMS as this was shown in healthy older adults. It was found that (i) gait parameters were more stable in the second than in the first minute and (ii) gait-related motor PF could not be detected based on spatio-temporal gait parameters, including the MTC. Descriptive analysis indicated a decrease in MTC variability, which is assumed to be indicative for motor PF, toward the end of the 6MWT in some pwMS. Future studies should investigate gait parameters for the assessment of motor PF in pwMS recorded during more intense and/or longer walking protocols, taking the level of disability into account. Furthermore, using gait parameters recorded in the first minute of the 6MWT as a baseline for the assessment of motor PF should be avoided.

The study purpose was to follow a prospective cohort study design to use gait kinematic parameters to identify the risk factors and to develop a statistical model to predict running-related lower limb injuries of sportspersons. Materials and methods. BTS G-WALK® gait analysis system was used to collect gait kinematic data of 87 subjects from an institute of physical education and sports science. The subjects were followed for a full academic season after which the researcher inquired about their injury occurrences. Binary logistic regression was used to develop a prediction model to predict lower limb injuries of sportspersons. Results. The result of the study revealed that increasing Range of Obliquity, Range of Tilt and Range of Rotation were associated with increased likelihood of future running-related lower limb injury. However, the lower Symmetry Index was associated with increase in the likelihood of future running-related lower limb injury. Conclusions. The study confirmed that it is possible to predict injury, but for practical implication further research is essential with a bigger sample size.

Degenerative processes induce loss of lumbar lordosis and anterior sagittal imbalance (ASI). Optoelectronic study provides kinematic analysis of movement and can also detect ASI. The aim of the present study was to assess gait kinematic modifications induced by ASI. Thirty-five healthy male volunteers were subjected to reversible ASI induced by wearing a kyphotic thermoformed thoracolumbar corset. The deformation was assessed by C7 tilt on EOS (EOS Imaging, Paris, France) full-spine views. Ten optoelectronic gait recordings were made with corset and 10 without. Gait kinematic parameters (stride length, walking speed, rhythm), gait balance parameters (center of mass braking index, stride width, double support time) and spinal sagittal balance parameters (C7T10S1, C7´S1′ and spinal angles) were averaged. Adjusted analysis distinguished direct ASI impact from locomotor factors. The corset-induced ASI produced +15° change in C7 tilt (P < 0.0001), –7.4° in C7T10S1 (P < 0.0001), +66.2 mm in C7´S1′ (P < 0.0001), and +13.1° in spinal angle (P < 0.0001). Radiographic and optoelectronic data correlated significantly. Stride length (P < 0.0001) and rhythm (P = 0.0003) were significantly reduced, contributing to a reduction in walking speed (P < 0.0001), and strongly influencing double support time (β = –0.38; 95% confidence interval [CI]: –0.69; –0.06). Center of mass braking index was significantly reduced (P < 0.0001) and significantly influenced by ASI (β = –0.51; 95% CI: –0.78; –0.28). Stride width was significantly increased by ASI (P < 0.0001), independently of rhythm and stride length. ASI induced by a kyphotic corset was detectable on the optoelectronic system, leading to significant changes in gait kinematics. Locomotor parameters were significantly reduced. Balance parameters were significantly and directly altered by ASI. [ABSTRACT FROM AUTHOR]

Introduction/Objective. The essence of the treatment of degenerative knee joint diseases is pain relief, restoring motion range and stability of knee joints. Methods. In this study, 35 patients participated after having surgery of the knee joint. The patients had a posterior-stabilized (PS) endoprosthesis in one joint, and a posterior cruciate ligament retaining (CR) endoprosthesis in the other. Kinematic data was collected using a 3D optical system for tracking fluorescent markers in time. Based on these data, the following parameters were determined: degree of flexion, mediolateral (ML) translation, lateral gap, medial gap, and the angle of change between the transtibial and transfemoral axes. Results. The results show a more pronounced flexion degree with the PS prosthesis compared to the CR prosthesis. Also, the results show negligible values of the ML translation, lateral gap, and medial gap in both types of prostheses. Using the non-parameter Wilcoxon test, a substantial difference in the angle change between the transtibial and transfemoral axes was confirmed, that is, in the flexion angles on the CR and PS prostheses. Conclusion. This study shows that there is no great difference in the use of the PS or CR designs of endoprostheses. Better behavior and range of motion in the knee joint were established with the implantation of the PS endoprosthesis. This conclusion is confirmed by the substantial difference in the degree of flexion of the knee joint and in the position of the transversal axes of the tibia and femur.

Abstract Background Design modifications in prostheses may cause alterations in gait kinematics, thus influencing functional restoration of knees after total knee arthroplasty (TKA). The aim of the study was to investigate the differences in gait kinematics and clinical outcomes after single radius (SR) versus multiple radius (MR) TKA. Method The present retrospective study included 38 unilateral TKA involving 20 knees using MR design implant and 18 knees using SR design implant. Thirty-six healthy volunteers were also recruited. The mean follow-up time was 16 ± 3 months. At the end of follow-up, the 6 degrees of freedom (DOF) kinematics of knees and range of motion (ROM) were measured with a portable optical tracking system. Knee society score (KSS) and knee injury, and osteoarthritis outcome score (KOOS) were also collected. Results Patients in the SR group had significantly higher scores in activities of daily living (84.7 ± 15.9) and sports and recreation (67.5 ± 25.2) KOOS sub-score than MR group (69.9 ± 17.6, P = 0.012; 50.0 ± 20.8, P = 0.027, respectively). Significant differences were detected between MR knees and SR knees (1.82° ± 3.11° vs 4.93° ± 3.58°, P = 0.009), and MR knees and healthy knees (1.82° ± 3.11° vs 3.62° ± 3.52°, P = 0.032) in adduction/abduction ROM. The proximal/distal translation was significantly smaller in MR knees (0.58 ± 0.54 cm) compared with SR knees (1.03 ± 0.53 cm, P = 0.003) or healthy knees (0.84 ± 0.45 cm, P = 0.039). SR knees (0.24 ± 0.40 cm) had smaller translation compared with the MR group (0.54 ± 0.33 cm, P = 0.017) and control group (0.67 ± 0.36 cm, P = 0.028). No significant difference was detected in the other DOFs during the gait cycle. Significant difference was detected in extension/flexion, internal/external rotation, adduction/abduction, proximal/distal and medial/lateral among MR, SR and healthy knees. Conclusion After TKA, patients have altered gait kinematics compared with the control group. MR and SR design showed varied characteristics in 6 DOF gait kinematics, which could be the cause of the difference in functional outcome.

Background: Understanding joint loading and the crucial role of joint moments is essential for developing treatment strategies in gait analysis, which often requires the precise estimation of joint moments through an inverse dynamic approach. This process necessitates the use of a force plate synchronized with a motion capture system. However, effectively capturing ground reaction force in typically developing (TD) children and those with congenital talipes equino varus (CTEV) presents challenges, while the availability and high cost of additional force plates pose additional challenges. Therefore the study aimed to develop, train, and identify the most effective machine learning (ML) model to predict joint moments from kinematics for TD children and those with CTEV., Method: In a study at the Gait Lab, 13 children with bilateral CTEV and 17 TD children underwent gait analysis to measure kinematics and kinetics, using a 12-camera Qualisys Motion Capture System and an AMTI force plate. ML models were then trained to predict joint moments from kinematic data as input., Results: The random forest regressor and deep neural networks (DNN) proved most effective in predicting joint moments from kinematics for TD children, yielding better results. The Random Forest regressor achieved an average r of 0.75 and nRMSE of 23.03 % for TD children, and r of 0.74 and 23.82 % for CTEV. DNN achieved an average r of 0.75 and nRMSE of 22.83 % for TD children, and r of 0.76 and nRMSE of 23.9 % for CTEV., Conclusions: The findings suggest that using machine learning to predict joint moments from kinematics shows moderate potential as an alternative to traditional gait analysis methods for both TD children and those with CTEV. Despite its potential, the current prediction accuracy limitations hinder the immediate clinical application of these techniques for decision-making in a pediatric population., Competing Interests: None., (© 2024 Professor P K Surendran Memorial Education Foundation. Published by Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.)

Gait analysis is a standard practice used by clinicians and researchers to identify abnormalities, examine disease progression, or assess the success of interventions. Traditionally, assessments were performed with visual inspection by a trained professional. However, with the recent breakthroughs in sensing technologies, there is a growing body of literature that uses features extracted from sensing data as inputs to machine learning methods. These models require a large representative sample of gait cycles labeled according to each category of interest (e.g. standard, anomalous) for model training. This paper provides a personalized, nonparametric statistical framework that can be used for detecting and interpreting gait changes in individuals while requiring only a small number of baseline gait cycles. This framework can be applied using the acceleration trajectory or features from a single Intertial Measurement Unit (IMU). The individualized framework does not require the gait cycles to be labeled and does not require the assumption that the observed patterns are consistent across subjects. The personalized framework is applied to gait cycles extracted from a material handling task that simulates moving heavy loads in a warehouse. Twelve subjects were monitored and significant changes in personalized gait patterns consistent with perceived exertion were observed. Further interpretation of the changes illustrates that participants exhibit individualized patterns in gait as they approach the fatigued state. [ABSTRACT FROM AUTHOR]

Objectives: This study assessed the ability of coaches to rank-order distance runners on running economy (RE) through visual assessment. Methods: Running economy was measured in five trained recreational distance runners at a speed of 3.57 m·s−1, with a minimum VO2 difference of 2-mL.kg−1.min−1 between adjacent runners. Following measurement of RE, participants were filmed from the front, side, and rear while running on a treadmill. Endurance coaches from high school to international level (N = 121) viewed each video and ranked the runners on a scale from 1 (most economical) to 5 (least economical). Coaches also completed a demographic questionnaire and listed running style biomechanical observations they used in determining each ranking. A cumulative odds ordinal logistic regression with proportional odds was run to determine the effect of coaching level, years of coaching experience, years of training experience, competition level, certification status, and education level, on the ability of distance running coaching to accurately rank RE among a group of runners. Results: No coaching characteristic was a significant predictor of ranking accuracy, χ2 = 3.566, p =.735. Conclusions: Visual assessment of effort, based on RE, is a difficult task, even for the trained eye and could be related to difficulty in understanding the interaction effect of various RE factors or the translation of scientific-based knowledge to the field of play. Practically, coaches should be cautious when recommending biomechanical adjustments without considering the interconnected factors related to such changes. [ABSTRACT FROM AUTHOR]

This Gait dataset is essential for studying motion, evaluating prosthesis effects, and improving the design of prosthetic components to meet the needs for daily life in low-income countries where advanced prosthesis are limited. This dataset contains the gait parameters of 14 above-knee prosthesis users (5 female, 9 male) with different passive prosthetic components and 20 healthy participants (10 male, 10 female). The data are spatio-temporal parameters, lower limb joints angles and moments in the sagittal plane, and ground reaction force components. These data were acquired using 6 video cameras (BTS SMART-D) and 2 Kistler force plates in the biomechanics lab at Damascus University. The acquisition process of data follows Davis et al. protocol for clinical gait analysis. It was divided into three main steps: subject preparation, raw data acquisition, and gait parameters calculation. The online repository containing the files is Mendeley Data: [http://dx.doi.org/10.17632/k5y9jkx87y.1]

BACKGROUND: Kinematic analysis has been a dominant tool for addressing the neuromuscular and proprioceptive alterations that occur in Low Back Pain (LBP) patients. Movement variability is a crucial component of this analysis. In the recent years application of non-linear indices seems to be showing the way. OBJECTIVE: The aim of the study was to compare movement variability, as expressed mainly by non-linear indices, at the pelvis and lumbar spine between LBP patients and healthy participants during gait. METHODS: Sixteen (16) LBP patients and thirteen (13) healthy control subjects (non-athletes) participated in the study. Participants walked on a treadmill at different walking conditions while recorded by a 6-infrared camera optoelectronic system. Kinematic variability of pelvic and lumbar movement was analyzed using linear (standard deviation – SD) and non-linear indices (Maximal Lyapunov Exponent – LyE and Approximate Entropy – ApEn). RESULTS: Healthy subjects were found to have significantly greater mean values than LBP patients at seven pelvic and lumbar components in LyE, ApEn and SD. Specifically, the calculated LyE at the pelvis during normal gait was proven to have a sensitivity of 92.3% and a specificity of 90% in the discrimination of healthy subjects from LBP patients. Female subjects presented with higher variability in gait measures than males. CONCLUSION: Healthy participants presented with higher movement variability in their kinematic behavior in comparison to LBP patients. Lower variability values may be partly explained by the attempt of LBP patients to avoid painful end of range of motion positions. In this perspective non-linear indices seem to relate to qualitive characteristics of movement that need to be taken into consideration during rehabilitation. [ABSTRACT FROM AUTHOR]

Neurological disorders and aging induce impaired gait kinematics. Despite recent advances, effective methods using lower-limb exoskeleton robots to restore gait kinematics are as yet limited. In this study, applying virtual stiffness using a hip exoskeleton was investigated as a possible method to guide users to change their gait kinematics. With a view to applications in locomotor rehabilitation, either to provide assistance or promote recovery, this study assessed whether imposed stiffness induced changes in the gait pattern during walking; and whether any changes persisted upon removal of the intervention, which would indicate changes in central neuro-motor control. Both positive and negative stiffness induced immediate and persistent changes of gait kinematics. However, the results showed little behavioral evidence of persistent changes in neuro-motor control, not even short-lived aftereffects. In addition, stride duration was little affected, suggesting that at least two dissociable layers exist in the neuro-motor control of human walking. The lack of neuro-motor adaptation suggests that, within broad limits, the central nervous system is surprisingly indifferent to the details of lower limb kinematics. The lack of neuro-motor adaptation also suggests that alternative methods may be required to implement a therapeutic technology to promote recovery. However, the immediate, significant, and reproducible changes in kinematics suggest that applying hip stiffness with an exoskeleton may be an effective assistive technology for compensation. [ABSTRACT FROM AUTHOR]

The use of inertial measurement units (IMUs) to compute gait outputs, such as the 3D lower-limb kinematics is of huge potential, but no consensus on the procedures and algorithms exists. This study aimed at evaluating the validity of a 7-IMUs system against the optoelectronic system. Ten asymptomatic subjects were included. They wore IMUs on their feet, shanks, thighs and pelvis. The IMUs were embedded in clusters with reflective markers. Reference kinematics was computed from anatomical markers. Gait kinematics was obtained from accelerometer and gyroscope data after sensor orientation estimation and sensor-to-segment (S2S) calibration steps. The S2S calibration steps were also applied to the cluster data. IMU-based and cluster-based kinematics were compared to the reference through root mean square errors (RMSEs), centered RMSEs (after mean removal), correlation coefficients (CCs) and differences in amplitude. The mean RMSE and centered RMSE were, respectively, 7.5° and 4.0° for IMU-kinematics, and 7.9° and 3.8° for cluster-kinematics. Very good CCs were found in the sagittal plane for both IMUs and cluster-based kinematics at the hip, knee and ankle levels (CCs > 0.85). The overall mean amplitude difference was about 7°. These results reflected good accordance in our system with the reference, especially in the sagittal plane, but the presence of offsets requires caution for clinical use.

Background/aims: Extracorporeal shockwave therapy might be a considerable substitute to present treatment alternatives to reduce spasticity and improve range of motion in patients with cerebral palsy, which could improve their quality of life and gait pattern. The aim of this study was to investigate the effect of extracorporeal shockwave therapy on gait parameters in children with spastic diplegic cerebral palsy. Methods: A total of 34 children with spastic diplegia (19 boys and 15 girls) participated in the study. Their ages ranged from 5–7 years (mean 5.8 ± standard deviation 1.2 years). They were randomly assigned into two equal groups, the study and the control group. Both groups received the traditional physiotherapy programme, three sessions a week consecutively for 3 months. Children in the study group also received extracorporeal shockwave therapy one session a week for 3 months. Results: There was a significant improvement of spasticity, step length and stride width in the control group (P=0.017, 0.015, 0.033 respectively). Walking speed did not show a significant change in the control group (P=0.1). In the study group, there was a significant improvement in spasticity, stride length, stride width, and walking speed (P=0.0001, 0.005, 0.029, 0.014 respectively). Comparing the gained improvement in the study and the control group, the results showed that the improvement in the study group significantly exceeded that of the control group in spasticity, stride length, stride width and walking speed (P=0.0003, 0.011, 0.043, 0.002 respectively). Conclusions: Extracorporeal shockwave therapy is effective in reducing spasticity and improving gait patterns in children with spastic diplegia cerebral palsy. [ABSTRACT FROM AUTHOR]

People with cognitive impairments show deficits during physical performances such as gait, in particular during cognitively challenging conditions (i.e. dual‐task gait [DTG]). However, it is unclear if people at risk of dementia, such as those with subjective memory complaints (SMC), also display gait and central deficits associated with DTG. In this study, we investigated the effects of single‐ and dual‐task gait (STG and DTG), on left prefrontal cortex (PFC) activation in elderly people with subjective memory complaints (SMC) and Dementia. A total of 58 older adults (aged 65–94 years; 26 Healthy; 23 SMC; 9 Dementia) were recruited. Gait spatiotemporal characteristics (i.e. stride velocity and length) were assessed using an instrumented walkway during STG and DTG. Single‐channel functional near‐infrared spectroscopy over the left PFC was used to measure changes in oxyhaemoglobin (O2Hb) during gait. Stride velocity and length during STG (all p <.05) and DTG (all p <.000) were significantly impaired in people with Dementia compared to Healthy and SMC individuals. No differences were observed between Healthy and SMC. For STG, a greater increase in O2Hb (p <.05) was observed in those with Dementia compared to the Healthy and SMC, while no differences were observed between Healthy and SMC. A significant increase and decline in O2Hb was observed during DTG in the SMC and Dementia groups, respectively, compared to Healthy. Our findings indicate an altered pattern of cerebral haemodynamic response of the left PFC in DTG in people with SMC and Dementia, which may suggest that central changes precede functional impairments in people with SMC. [ABSTRACT FROM AUTHOR]