Gait Behavior Research Articles

Identification of distinct subtypes of post-stroke and neurotypical gait behaviors using neural network analysis of kinematic time series data.

Heterogeneous types of gait impairment are common post-stroke. Studies used supervised and unsupervised machine learning on discrete biomechanical features to summarize the gait cycle and identify common patterns of gait behaviors. However, discrete features cannot account for temporal variations that occur during gait. Here, we propose a novel machine-learning pipeline to identify subgroups of gait behaviors post-stroke using kinematic time series data. We analyzed ankle and knee kinematic data during treadmill walking data in 39 individuals post- stroke and 28 neurotypical controls. The data were first input into a supervised dual-stage Convolutional Neural Network-Temporal Convolutional Network, trained to extract temporal and spatial gait features. Then, we used these features to find clusters of different gait behaviors using unsupervised time series k-means. We repeated the clustering process using 10,000 bootstrap training data samples and a Gaussian Mixture Model to identify stable clusters representative of our dataset. Finally, we assessed the kinematic differences between the identified clusters using 1D statistical parametric mapping ANOVA. We then compared gait spatiotemporal and clinical characteristics between clusters using one-way ANOVA. We obtained five clusters: two clusters of neurotypical individuals (C1 and C2) and three clusters of individuals post-stroke (S1, S2, S3). C1 had kinematics that resembled the normative gait pattern. Individuals in C2 had a shorter stride time than C1. Individuals in S1 had mild impairment and walked with increased bilateral knee flexion during the loading response. Individuals in S2 had moderate impairment, were the slowest among the clusters, took shorter steps, had increased knee flexion during stance bilaterally and reduced paretic knee flexion during swing. Individuals in S3 had mild impairment, asymmetric swing time, had increased ankle abduction during the gait cycle and reduced dorsiflexion bilaterally during loading response and stance. Every individual was assigned to a cluster with a cluster membership likelihood above 93%. Our results indicate that joint kinematics in individuals post-stroke are distinct from controls, even in those individuals with mild impairment. The three subgroups post-stroke showed distinct kinematic impairments during specific phases in the gait cycle, providing additional information to clinicians for gait retraining interventions.

Dynamical systems theory applied to short walking trials

Human walking is an extremely complex neuromuscular activity whose simplicity disappears when an attempt is made to provide a quantitative description of the process. The dynamical systems theory provides a framework for analyzing the stability and chaotic nature of dynamical systems, employing Floquet multipliers (FM) and long and short-term Lyapunov exponents (LE), respectively. This report compares FM and LE from three methods: method A (false nearest neighbors and numerical approximation), method B (false nearest neighbors and semi-analytical technique) and method C (singular value decomposition and semi-analytical technique). Data from 33 healthy older adults with no history of falls were used to explain the dynamic system. A surrogate center of mass trajectory was calculated for the analysis of sway in the transverse plane. Results revealed methodological differences in LE and FM calculations with semi-analytical solutions providing closer approximations to observed gait behavior. The long-term LE from Methods A and B were similar, but other LE pairings differed. Method A’s short-term LE indicated chaotic gaits for all subjects, while long-term LE from Methods A and B indicated chaos for half the subjects. Method C showed non-chaotic gait for most subjects. Method B’s FM indicated over 30% of subjects had unstable gait. Method C yielded values of LE and FM that most closely matched the subjects’ gait patterns. This study offers a methodological foundation for gait analysis using short time-series data, facilitating deeper insights into both stability and chaos within gait dynamics.

Prediction of abnormal gait behavior of lower limbs based on depth vision

Abstract As a kind of lower-limb motor assistance device, the intelligent walking aid robot plays an essential role in helping people with lower-limb diseases to carry out rehabilitation walking training. In order to enhance the safety performance of the lower-limb walking aid robot, this study proposes a deep vision-based abnormal lower-limb gait prediction model construction method for the problem of abnormal gait prediction of patients’ lower limbs. The point cloud depth vision technique is used to acquire lower-limb motion data, and a multi-posture angular prediction model is trained using long and short-term memory networks to build a model of the user’s lower-limb posture characteristics during normal walking as well as a real-time lower-limb motion prediction model. The experimental results indicate that the proposed lower-limb abnormal behavior prediction model is able to achieve a 97.4% prediction rate of abnormal lower-limb movements within 150 ms. Additionally, the model demonstrates strong generalization ability in practical applications. This paper proposes further ideas to enhance the safety performance of lower-limb rehabilitation robot use for patients with lower-limb disabilities.

Pathogenic TDP-43 accelerates the generation of toxic exon1 HTT in Huntington's disease knock-in mice.

Huntington's disease (HD) is caused by a CAG repeat expansion in exon1 of the HTT gene that encodes a polyglutamine tract in huntingtin protein. The formation of HTT exon1 fragments with an expanded polyglutamine repeat has been implicated as a key step in the pathogenesis of HD. It was reported that the CAG repeat length-dependent aberrant splicing of exon1 HTT results in a short polyadenylated mRNA that is translated into an exon1 HTT protein. Under normal conditions, TDP-43 is predominantly found in the nucleus, where it regulates gene expression. However, in various pathological conditions, TDP-43 is mislocalized in the cytoplasm. By investigating HD knock-in mice, we explore whether the pathogenic TDP-43 in the cytoplasm contributes to HD pathogenesis, through expressing the cytoplasmic TDP-43 without nuclear localization signal. We found that the cytoplasmic TDP-43 is increased in the HD mouse brain and that its mislocalization could deteriorate the motor and gait behavior. Importantly, the cytoplasmic TDP-43, via its binding to the intron1 sequence (GU/UG)n of the mouse Htt pre-mRNA, promotes the transport of exon1-intron1 Htt onto ribosome, resulting in the aberrant generation of exon1 Htt. Our findings suggest that cytoplasmic TDP-43 contributes to HD pathogenesis via its binding to and transport of nuclear un-spliced mRNA to the ribosome for the generation of a toxic protein product.

Rat Model of Neuropathic Pain Induced by Spinal Nerve Ligation: A New Approach via an Oblique Lateral Incision.

The spinal nerve ligation (SNL) model is a typical peripheral neuropathic pain model. During its construction, the removal of paraspinal muscles and transverse processes typically occurs, resulting in additional trauma that may potentially affect the pathophysiologic process of neuropathic pain. This study aimed to investigate the feasibility of establishing a more reliable SNL model using an oblique lateral approach. 36 adult male Sprague-Dawley rats were randomly divided into three groups: the traditional SNL (T-SNL) group, the new SNL (N-SNL) group (where the left L5 spinal nerve was ligated with a titanium clip via an oblique lateral approach), and the sham-operated (Sham) group. The operation time, Intraoperative bleeding, the number of rats that died, gait behavior, mechanical and cold pain threshold were recorded and measured. Stereology technology was used to calculate the number of microglia in spinal dorsal horn, and the Enzyme-linked immunosorbent assay (ELISA) technology was used to detect the expression of TNF-α and IL-1β in spinal cord as well as C-reactive protein (CRP) in serum in order to assess the effect of surgery on animal inflammation. Compared with the T-SNL group, operative time and intraoperative bleeding were significantly decreased in the N-SNL group. Within 14 days postoperation, one rat in the N-SNL group was died, two rats in the T-SNL group were died. Compared with the Sham group, the N-SNL group showed obvious spontaneous pain behavior, decreased the pain thresholds, the number of microglia and the expression of TNF-α and IL-1β were significantly increased, and there was no significant difference in these indexes compared with T-SNL group. There was no significant difference in serum CRP levels among the three groups. This study suggests that the oblique lateral approach SNL model is a reliable NP model with the advantages of good reproducibility, accessibility, and low trauma.

The effect of visual sensory interference during multitask obstacle crossing in younger and older adults.

When older adults step over obstacles during multitasking, their performance is impaired; the impairment results from central and/or sensory interference. The purpose was to determine if sensory interference alters performance under low levels of cognitive, temporal, and gait demand, and if the change in performance is different for younger versus older adults. Participants included 17 younger adults (20.9±1.9 years) and 14 older adults (69.7±5.4 years). The concurrent task was a single, simple reaction time (RT) task: depress button in response to light cue. The gait task was stepping over an obstacle (8 m walkway) in three conditions: (1) no sensory interference (no RT task), (2) low sensory interference (light cue on obstacle, allowed concurrent foveation of cue and obstacle), or (3) high sensory interference (light cue away from obstacle, prevented concurrent foveation of cue and obstacle). When standing, the light cue location was not relevant (no sensory interference). An interaction (sensory interference by task, p<0.01) indicated that RT was longer for high sensory interference during walking, but RT was not altered for standing, confirming that sensory interference increased RT during obstacle approach. An interaction (sensory interference by age, p<0.01) was observed for foot placement before the obstacle: With high sensory interference, younger adults placed the trail foot closer to the obstacle while older adults placed it farther back from the obstacle. The change increases the likelihood of tripping with the trail foot for younger adults, but with the lead limb for older adults. Recovery from a lead limb trip is more difficult due to shorter time for corrective actions. Overall, visual sensory interference impaired both RT and gait behavior with low levels of multitask demand. Changes in foot placement increased trip risk for both ages, but for different limbs, reducing the likelihood of balance recovery in older adults.

Assessing Spatiotemporal Behavior of Human Gait: A Comparative Study Between Low-Cost Smartphone-Based Mocap and OptiTrack Systems

AbstractThis study assessed the accuracy of a low-cost marker-based motion capture system with smartphone devices to estimate the spatiotemporal behavior of human gait in comparison with the performance of the commercial OptiTrack system. Initially, three test subjects were selected for the study, and after equipping them with passive retroreflective markers, they were recorded for gait velocities of 1.50, 1.90, and 2.30 $$m\bullet {s}^{-1}$$ m ∙ s - 1 while collecting kinematic data and videos. The results showed that the smartphone motion capture system exhibited significant spatiotemporal tracking and accuracy in the x-y trajectories and estimation of joint relative angles of the hip, knee, and ankle joints (θ1, θ2, and θ3, respectively) compared to the commercial OptiTrack system. In this comparison, an average goodness-of-FIT and normalized root mean square error of over 88.93% and 2.71% were obtained, respectively, for the joint relative angles of the hip and knee (θ1 and θ2) in all tests performed. However, the accuracy of the joint relative angle of the ankle (θ3, average FIT: 71.04% and nRMSE: 4.26%) was lower because of the low capture rate of the retroreflective markers in the smartphone system and the higher relative velocity in the lower extremities of the test subjects, which generated noise in the calculation of x-y trajectories. This decrease in accuracy has been reported in other studies. However, both motion capture systems experienced marker data loss at the hip, highlighting the need for improvement in the spatial distribution of the optical devices. The OptiTrack system demonstrated better optical redundancy but still required improvements. In contrast, the smartphone system, with its inherent limitations in terms of optical redundancy and spatial distribution, can be enhanced by incorporating multiple cameras for a three-dimensional view. Despite these limitations, the low-cost smartphone system showed optimal performance with minimal errors compared with the commercial system, making it a cost-effective option with potential for further development. The rapid advancement of smartphone technology and its accessibility make it an attractive choice for motion capture applications.

Are Gait Patterns during In-Lab Running Representative of Gait Patterns during Real-World Training? An Experimental Study.

Biomechanical assessments of running typically take place inside motion capture laboratories. However, it is unclear whether data from these in-lab gait assessments are representative of gait during real-world running. This study sought to test how well real-world gait patterns are represented by in-lab gait data in two cohorts of runners equipped with consumer-grade wearable sensors measuring speed, step length, vertical oscillation, stance time, and leg stiffness. Cohort 1 (N = 49) completed an in-lab treadmill run plus five real-world runs of self-selected distances on self-selected courses. Cohort 2 (N = 19) completed a 2.4 km outdoor run on a known course plus five real-world runs of self-selected distances on self-selected courses. The degree to which in-lab gait reflected real-world gait was quantified using univariate overlap and multivariate depth overlap statistics, both for all real-world running and for real-world running on flat, straight segments only. When comparing in-lab and real-world data from the same subject, univariate overlap ranged from 65.7% (leg stiffness) to 95.2% (speed). When considering all gait metrics together, only 32.5% of real-world data were well-represented by in-lab data from the same subject. Pooling in-lab gait data across multiple subjects led to greater distributional overlap between in-lab and real-world data (depth overlap 89.3-90.3%) due to the broader variability in gait seen across (as opposed to within) subjects. Stratifying real-world running to only include flat, straight segments did not meaningfully increase the overlap between in-lab and real-world running (changes of <1%). Individual gait patterns during real-world running, as characterized by consumer-grade wearable sensors, are not well-represented by the same runner's in-lab data. Researchers and clinicians should consider "borrowing" information from a pool of many runners to predict individual gait behavior when using biomechanical data to make clinical or sports performance decisions.

Impaired Standing Balance in Older Adults with Cognitive Impairment after a Severe Fall

Introduction: Fall-related sequelae as well as balance and gait impairments are more pronounced in older adults who are cognitively impaired (OACI) compared to older adults who are cognitively healthy (OACH). Evidence is scarce about differences in standing balance and gait in OACH and OACI after a fall, even though these are major risks for recurrent falls. Thus, the aim of this study was to investigate early impairments in gait and balance, by adding inertial measurement units (IMUs) to a functional performance test in OACH and OACI after a severe fall with a presentation to the emergency department (ED) and immediate discharge. Methods: The study sample was stratified into participants with and without probable cognitive impairment using the result of the Montreal Cognitive Assessment total score (maximum of 30 points). The cutoff for probable cognitive impairment was set at ≤ 24. Standing balance and gait parameters were measured using three IMUs in n = 69 OACH (72.0 ± 8.2 years) and n = 76 OACI (78.7 ± 8.1 years). Data were collected at participants’ homes as part of a comprehensive geriatric assessment in the “SeFallED” study within 4 weeks after presentation to the ED after a severe fall (German Clinical Trials Register ID: 00025949). ANCOVA was used for statistical analysis, adjusted for age. Results: The data indicated significantly more sway for OACI compared to OACH during balance tasks, whereas no differences in gait behavior were found. In detail, differences in standing balance were revealed for mean velocity (m/s) during parallel stance with eyes open (ηp2 = 0.190, p < 0.001) and eyes closed on a balance cushion (ηp2 = 0.059, p = 0.029), as well as during tandem stance (ηp2 = 0.034, p = 0.044) between OACI and OACH. Further differences between the two groups were detected for path length (m/s2) during parallel stance with eyes open (ηp2 = 0.144, p < 0.001) and eyes closed (ηp2 = 0.044, p < 0.027) and for range (m/s2) during tandem (ηp2 = 0.036, p = 0.036) and parallel stance with eyes closed (ηp2 = 0.045, p = 0.032). Conclusion: Even though both groups have experienced a severe fall with presentation to the ED in the preceding 4 weeks, balance control among OACI indicated a higher fall risk than among OACH. Therefore, effective secondary fall prevention efforts have to be established, particularly for OACI.

Proteus effect or bodily affordance? The influence of virtual high-heels on gait behavior

Shoes are an important part of the fashion industry, stereotypically affect our self-awareness as well as external perception, and can even biomechanically modify our gait pattern. Immersive Virtual Reality (VR) enables users not only to explore virtual environments, but also to control an avatar as a proxy for themselves. These avatars can wear any kind of shoe which might similarly affect self-awareness due to the Proteus Effect and even cause a bodily affordance to change the gait pattern. Bodily affordance describes a behavioral change in accordance with the expected constraints of the avatar a user is embodied with. In this article, we present the results of three user studies investigating potential changes in the gait pattern evoked by wearing virtual high-heels. Two user studies targeted female participants and one user study focused male participants. The participants wore either virtual sneakers or virtual high-heels while constantly wearing sneakers or socks in reality. To measure the gait pattern, the participants walked on a treadmill that also was added to the virtual environment. We measured significant differences in stride length and in the flexion of the hips and knees at heel strike and partly at toe off. Also, participants reported to walk more comfortably in the virtual sneakers in contrast to the virtual high-heels. This indicates a strong acceptance of the virtual shoes as their real shoes and hence suggests the existence of a bodily affordance. While sparking a discussion about the boundaries as well as aspects of the Proteus Effect and providing another insight into the effects of embodiment in VR, our results might also be important for researchers and developers.

Effect of vestibular loss on head-on-trunk stability in individuals with vestibular schwannoma

The vestibulo-collic reflex generates neck motor commands to produce head-on-trunk movements that are essential for stabilizing the head relative to space. Here we examined the effects of vestibular loss on head-on-trunk kinematics during voluntary behavior. Head and trunk movements were measured in individuals with vestibular schwannoma before and then 6 weeks after unilateral vestibular deafferentation via surgical resection of the tumor. Movements were recorded in 6 dimensions (i.e., 3 axes of rotation and 3 axes of translation) using small light-weight inertial measurement units while participants performed balance and gait tasks. Kinematic measures differed between individuals with vestibular schwannoma (at both time points) and healthy controls for the more challenging exercises, namely those performed in tandem position or on an unstable surface without visual input. Quantitative assessment of the vestibulo-ocular reflex (VOR) revealed a reduction in VOR gain for individuals with vestibular schwannoma compared to control subjects, that was further reduced following surgery. These findings indicated that the impairment caused by either the tumor or subsequent surgical tumor resection altered head-on-trunk kinematics in a manner that is not normalized by central compensation. In contrast, we further found that head-on-trunk kinematics in individuals with vestibular schwannoma were actually comparable before and after surgery. Thus, taken together, our results indicate that vestibular loss impacts head-on-trunk kinematics during voluntary balance and gait behaviors, and suggest that the neural mechanisms mediating adaptation alter the motion strategies even before surgery in a manner that may be maladaptive for long-term compensation.

Effects of Habituation on Spatiotemporal Gait Measures in Younger Adults

Abstract Virtual reality (VR) has potential benefits for training and rehabilitation (Lei et al., 2019; Rutkowski et al., 2020). In some instances, understanding how performance in VR relates to performance in the real world is a necessary step in building effective environments. This study was designed to determine whether gait in VR changes over time (adaptation), and whether it approaches natural environment performance over time (habituation). Nineteen young adults walked over a gait mat in a real hallway for five minutes and a virtual hallway for three 10-minute blocks. Results indicated that gait was significantly different in the natural environment compared to the first five minutes of immersion (p &amp;lt; 0.05). Group averages also demonstrated that after 10–15 minutes of immersion, there was no statistical difference between the virtual and natural environments across any of the gait measures (p &amp;gt; 0.05). However, individual differences in gait behavior were also evident. While some participants matched performance between virtual and natural environments by the end of the 30-minute session, others did not. These findings provide evidence that individuals adapt differently to motor tasks in VR and suggest that when gait is required in VR, the environment may need to be tailored to the individual to achieve desired outcomes.

Baimai Ointment relieves chronic pain induced by chronic compression of dorsal root ganglion in rats by regulating neuroactive ligand-receptor interaction and HIF-1 signaling pathway

The Baimai Ointment with the effect of relaxing sinew and activating collaterals demonstrates a definite effect on Baimai disease with pain, spasm, stiffness and other symptoms, while the pharmacodynamic characteristics and mechanism of this agent remain unclear. In this study, a rat model of chronic compression of L4 dorsal root ganglion(CCD) was established by lumbar disc herniation, and the efficacy and mechanism of Baimai Ointment in the treatment of CCD were preliminarily explored by behavioral tests, side effect evaluation, network analysis, antagonist and molecular biology verification. The pharmacodynamic experiment indicated that Baimai Ointment significantly improved the pain thresholds(mechanical pain, thermal pain, and cold pain) and gait behavior of CCD model rats without causing tolerance or obvious toxic and side effects. Baimai Ointment inhibited the second-phase nociceptive response of mice in the formalin test, increased the hot plate threshold of normal mice, and down-regulated the expression of inflammatory cytokines in the spinal cord. Network analysis showed that Baimai Ointment had synergistic effect in the treatment of CCD and was related to descending inhibition/facilitation system and neuroinflammation. Furthermore, behavioral tests, Western blot, and immunofluorescence assay revealed that the pain-relieving effect of Baimai Ointment on CCD may be related to the regulation of the interaction between neuroactive ligand and receptors(neuroligands) such as CHRNA7, ADRA2A, and ADRB2, and the down-regulation of the expression of NOS2/pERK/PI3K, the core regulatory element of HIF-1 signaling pathway in spinal microglia. The findings preliminarily reveal the mechanism of relaxing sinew and activating collaterals of Baimai Ointment in the treatment of Baimai disease, providing a reference for the rational drug use and further research of this agent.

Does listening to audiobooks affect gait behavior?

BackgroundThe effect of listening to audiobooks, podcasts, and other audio files while walking on gait performance has not been well studied. Although the number of audio users is growing annually. Evidence suggests that a posture-first strategy contributes to gait stability in healthy individuals during dual-task conditions, but this effect may be diminished when the cognitive task is consciously prioritized. Objectives: To study the effect of listening to an audiobook while walking, as a daily life-like dual-task, on spatiotemporal gait parameters.MethodsForty young healthy (24.05 ± 3.66) subjects participated in the study. Spatiotemporal gait parameters were measured for 5 min on a treadmill once without (single-task) and once while listening to an audiobook through over-ear headphones (dual-task). Measured parameters included spatiotemporal parameters, gait phases, maximum pressure, and dual-task cost. Data were statistically analyzed using SPSS software.ResultsThere were no significant differences in any of the studied parameters between the single- and dual-task conditions, even though the subjective cognitive load of listening to audiobooks while walking was high. However, participants with different habits had significant differences in gait phases and maximum pressure. Rare listeners had a shorter stance phase, a longer swing phase, and a higher maximum pressure on the dominant heel. They also had significant differences in dual-task costs.ConclusionNo differences in the spatiotemporal gait parameters for walking with and without listening to audiobooks, as a daily life-like dual-task, were observed. However, the difference between participants who listened rarely and participants who listened often may confirm the “posture first” strategy in young healthy people.Trial registrationDRKS00025837, retrospectively registered on 23.11.2021.

The topographical attenuation of cutaneous input is modulated at the ankle joint during gait.

The attenuation of sensory inputs via various methods has been demonstrated to impair balance control and alter locomotor behavior during human walking; however, the effects of attenuating foot sole sensation under distinct areas of the foot sole on lower extremity motor output remains poorly understood. Thus, the purpose of this study was to attenuate cutaneous feedback via regional hypothermia under five different areas of the foot sole and investigate the resultant modulation of kinematic and muscle activity during level walking. Electromyography from eight lower leg muscles, kinematics, and location of center of pressure was recorded from 48 healthy young adults completing walking trials with normal and reduced cutaneous sensation from bilateral foot soles. The results of this study highlight the modulatory response of the tibialis anterior in terminal stance (propulsion and toe-off) and medial gastrocnemius muscle throughout the entire stance phase of gait. The topographical organization of foot sole skin in response to the attenuation of cutaneous feedback from different areas of the foot sole significantly modified locomotor activity. Furthermore, the locomotor response to cutaneous attenuation under the same regions that we previously facilitated with tactile feedback do not oppose each other, suggesting different physiological changes to foot sole skin generate unique gait behaviors.

Discovering individual-specific gait signatures from data-driven models of neuromechanical dynamics.

Locomotion results from the interactions of highly nonlinear neural and biomechanical dynamics. Accordingly, understanding gait dynamics across behavioral conditions and individuals based on detailed modeling of the underlying neuromechanical system has proven difficult. Here, we develop a data-driven and generative modeling approach that recapitulates the dynamical features of gait behaviors to enable more holistic and interpretable characterizations and comparisons of gait dynamics. Specifically, gait dynamics of multiple individuals are predicted by a dynamical model that defines a common, low-dimensional, latent space to compare group and individual differences. We find that highly individualized dynamics-i.e., gait signatures-for healthy older adults and stroke survivors during treadmill walking are conserved across gait speed. Gait signatures further reveal individual differences in gait dynamics, even in individuals with similar functional deficits. Moreover, components of gait signatures can be biomechanically interpreted and manipulated to reveal their relationships to observed spatiotemporal joint coordination patterns. Lastly, the gait dynamics model can predict the time evolution of joint coordination based on an initial static posture. Our gait signatures framework thus provides a generalizable, holistic method for characterizing and predicting cyclic, dynamical motor behavior that may generalize across species, pathologies, and gait perturbations.

Slip Risk Prediction Using Intelligent Insoles and a Slip Simulator

Slip and fall accidents are the leading cause of injuries for all ages, and for fatal injuries in adults over 65 years. Various factors, such as floor surface conditions and contaminants, shoe tread patterns, and gait behavior, affect the slip risk. Moreover, the friction between the shoe outsoles and the floor continuously changes as their surfaces undergo normal wear over time. However, continuous assessment of slip resistance is very challenging with conventional measurement techniques. This study addresses this challenge by introducing a novel approach that combines sensor fusion technology and machine learning techniques to create intelligent insoles designed for fall risk prediction. In addition, a state-of-the-art slip simulator, capable of mimicking the foot’s motion during a slip, was developed and utilized for the assessment of slipperiness between various shoes and floor surfaces. Data acquisition involved the collection of pressure data and three-axial accelerations using instrumented shoe insoles, complemented by friction coefficient measurements via the slip simulator. The collected dataset includes four types of shoes, three floor surfaces, and four surface conditions, including dry, wet, soapy, and oily. After preprocessing of the collected dataset, the simulator was used to train five different machine learning algorithms for slip risk classification. The trained algorithms provided promising results for slip risk prediction for different conditions, offering the potential to be employed in real-time slip risk prediction and safety enhancement.

Translational evaluation of gait behavior in rodent models of arthritic disorders with the CatWalk device - a narrative review.

Arthritic disorders have become one of the main contributors to the global burden of disease. Today, they are one of the leading causes of chronic pain and disability worldwide. Current therapies are incapable of treating pain sufficiently and preventing disease progression. The lack of understanding basic mechanisms underlying the initiation, maintenance and progression of arthritic disorders and related symptoms represent the major obstacle in the search for adequate treatments. For a long time, histological evaluation of joint pathology was the predominant outcome parameter in preclinical arthritis models. Nevertheless, quantification of pain and functional limitations analogs to arthritis related symptoms in humans is essential to enable bench to bedside translation and to evaluate the effectiveness of new treatment strategies. As the experience of pain and functional deficits are often associated with altered gait behavior, in the last decades, automated gait analysis has become a well-established tool for the quantitative evaluation of the sequalae of arthritic disorders in animal models. The purpose of this review is to provide a detailed overview on the current literature on the use of the CatWalk gait analysis system in rodent models of arthritic disorders, e.g., Osteoarthritis, Monoarthritis and Rheumatoid Arthritis. Special focus is put on the assessment and monitoring of pain-related behavior during the course of the disease. The capability of evaluating the effect of distinct treatment strategies and the future potential for the application of the CatWalk in rodent models of arthritic disorders is also addressed in this review. Finally, we discuss important consideration and provide recommendations on the use of the CatWalk in preclinical models of arthritic diseases.

Tonic Activation of NR2D-Containing NMDARs Exacerbates Dopaminergic Neuronal Loss in MPTP-Injected Parkinsonian Mice.

NR2D subunit-containing NMDA receptors (NMDARs) gradually disappear during brain maturation but can be recruited by pathophysiological stimuli in the adult brain. Here, we report that 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) intoxication recruited NR2D subunit-containing NMDARs that generated an Mg2+-resistant tonic NMDA current (INMDA) in dopaminergic (DA) neurons in the midbrain of mature male mice. MPTP selectively generated an Mg2+-resistant tonic INMDA in DA neurons in the substantia nigra pars compacta (SNpc) and ventral tegmental area (VTA). Consistently, MPTP increased NR2D but not NR2B expression in the midbrain regions. Pharmacological or genetic NR2D interventions abolished the generation of Mg2+-resistant tonic INMDA in SNpc DA neurons, and thus attenuated subsequent DA neuronal loss and gait deficits in MPTP-treated mice. These results show that extrasynaptic NR2D recruitment generates Mg2+-resistant tonic INMDA and exacerbates DA neuronal loss, thus contributing to MPTP-induced Parkinsonism. The state-dependent NR2D recruitment could be a novel therapeutic target for mitigating cell type-specific neuronal death in neurodegenerative diseases.SIGNIFICANCE STATEMENT NR2D subunit-containing NMDA receptors (NMDARs) are widely expressed in the brain during late embryonic and early postnatal development, and then downregulated during brain maturation and preserved at low levels in a few regions of the adult brain. Certain stimuli can recruit NR2D subunits to generate tonic persistent NMDAR currents in nondepolarized neurons in the mature brain. Our results show that MPTP intoxication recruits NR2D subunits in midbrain dopaminergic (DA) neurons, which leads to tonic NMDAR current-promoting dopaminergic neuronal death and consequent abnormal gait behavior in the MPTP mouse model of Parkinson's disease (PD). This is the first study to indicate that extrasynaptic NR2D recruitment could be a target for preventing neuronal death in neurodegenerative diseases.

Investigating gait behavior in children with scoliosis diagnosed Juvenile Idiopathic Arthritis: Pilot Study

Investigating gait behavior in children with scoliosis diagnosed Juvenile Idiopathic Arthritis: Pilot Study