Walking Pattern Research Articles

Measurement and Analysis of ground reaction forces Distribution and electromyography for Ankle Joint Fixation Injury Using Different Types of Shoes

One of the health issues that many people encounter on a daily basis is bone fracture, which can happen for a number of reasons, such as arthritis, sprains, or external trauma . The patient experiences instability as a result of these issues . Internal fixation is a type of surgery used to support and mend a damaged bone Treatment options include ankle joint fixation, a surgical procedure employing pins, plates, rods, or screws. This study uses gait analysis methods to assess lower limb biomechanics . Gait analysis is vital for understanding walking patterns and intervention effectiveness. The impact of different shoe designs on ankle mechanics, using the finite element method and ANSYS, is investigated The results of the EMG and the GRF were discussed. This research deepens our understanding of lower limb biomechanics and ankle joint health. By evaluating stress effects and designing custom shoes, it enhances ankle injury treatment and management strategies. The patient, a 70-year-old woman with an internal fixation on her ankle joint, underwent a CT scan of her ankle. The patient underwent a number of experiments to evaluate her stability. EMG was used to determine the muscle stress for a brief period of time, and ground reaction force was then used to determine the pressure of walking. Both EMG and GRF have two walking speeds of1.5and 2 km/h while wearing four different types of shoes. The behavior of the EMG demonstrates that the stress on the muscle increases as walking speed increases, and the results varies depending on the shoe. The patient is afraid to apply pressure to the injured foot, so the health foot has better pressure over the entire foot

God’s gift of wisdom in words, actions, and practical skills

This article examined wisdom, a godly attribute, as a gift God gives. The gift takes at least three forms: skill in wise words, skill in subsequent actions, and skill with one’s hands. Bystanders and readers easily spot wisdom. This article found that wisdom grew and was refined through use. Employing a canonical approach and a literary methodology, this article presented selected Hebrew Bible characters who broadly illustrated God’s gift of wisdom in words and actions; it then considered two men and a group of women who were skilled – wise – with their hands. Four biblical characters noted for wise speech and actions include Joseph, the dream-interpreter and second to Pharaoh as Egypt’s ruler (Gn 41:37–41); the Wise Woman of Abel Beth Maacah, a city’s arbitrator during a siege (2 Sm 20:14–22); Solomon, David’s successor, who asked God for an understanding mind and received wisdom (1 Ki 3:9–12); and Daniel, a Judean exile in Babylon who sought God’s wisdom in a life-and-death situation (Dn 2:19–23). A fifth character, Lady Wisdom (a most interesting persona), teaches that wisdom is not only a gift but also a learned skill. In an ‘Elevator Pitch’ proclaimed loudly in a city’s streets, she invites passers-by to come to her banquet, learn from her, and become wise (Pr 8–9). God’s wisdom also abounded in practical, tactile ways. God gave Bezalel and Oholiab wisdom in crafting furnishings for the Tabernacle in the Wilderness (Ex 31:1–11); wise-hearted women participated as spinners (Ex 35:25–26). This article concluded that whether given as word, action, or skill or learned via study or practiced manually, all wisdom’s forms come from the bountiful Giver, and require a recipient’s maintenance, namely the lifelong pattern of seeking God and walking in his ways (Pr 2). Wise choices in friends, words, and actions result in blessing the learner and subsequently promoting a society’s well-being. Wisdom ripples.Contribution: Through the lens of Old Testament character studies, this article illustrated aspects of God’s gift of wisdom. Stories showed how individuals sought, practiced, and developed wisdom. While wisdom initially met a need, saved a life, or led a nation, it overflowed from the one singularly known as wise to others. However, a condition applied. Wisdom is not inherited; all seekers must learn that wisdom’s objective, like all God’s gifts, is God’s glory.

GAIT DISORDERS IN THE ELDERLY AND THE RISK OF FALLS

Falls are the leading cause of injury in people over 65 in the United States. In 2018, 27.5% of seniors over age 65 reported at least one fall in the past year and 10.2% had injuries after a fall in the past year. One feature of walking that has been used to identify people who are at risk for falling is gait unsteadiness. An unsteady gait pattern will be characterized with greater kinematics variability. Decreasing variability of walking patterns may help to prevent falls by achieving a more stable gait pattern, thus improving the control of the whole-body position and by reducing the mediolateral momentum of the centre of mass. Walking more slowly, with a higher STF and shorter STL, may help to stabilize the gait pattern and allow greater adjustment and flexibility to changes in walking conditions (increasing or decreasing walking speed), especially in patients with history of falls. Compared with the elderly with no history of falls, elderly people who are at risk for falls will have the following characteristics of gait: decreased ankle plantar flexion and hip extension during push-off, increased hip flexion during the swing phase, reduced mediolateral sway and decreased reaction time. Key words: elderly falls, gait analysis.

Prefrontal Cortex Neuromodulation Improve Gait Parameters in Latinx People Living with HIV

Background: Human Immunodeficiency Virus (H.I.V.) infection affects motor and cognitive systems and can lead to impairments in gait and balance. The application of transcranial direct current stimulation (tDCS), particularly to the prefrontal cortex, has shown encouraging results in enhancing cognition and executive functioning in individuals with H.I.V., both in the short and long term. Despite the current research, some experts have suggested that incorporating a task that stimulates higher cognitive centers in conjunction with tDCS may enhance its effects. Purpose: This study aimed to examine the effect of tDCS combined with a tracking task on the prefrontal cortex as a viable treatment for enhancing balance and gait in individuals living with H.I.V. Methods: The study evaluated nine female participants, all living with H.I.V., with an average age of 58.8 ± 4.6. As part of the experiment, each participant's gait was carefully evaluated before and after tDCS treatment to measure any potential changes in their walking patterns accurately. Transcranial Direct Current Stimulation (tDCS) was non-invasively administered to the participants' prefrontal cortex within seven days to investigate its possible effects on brain function. Results: Upon analyzing the data, the results demonstrated significant variations between single and dual tasks in numerous aspects, such as temporospatial, turn, and balance, before transcranial direct current stimulation (tDCS), ultimately shedding light on the potential cognitive difficulties that may arise. Data analysis showed noticeable improvements in various aspects, such as stride length, turn duration, and balance trends, when tDCS was applied. Conclusion: This study's findings suggest that tDCS may improve these parameters. However, it is recommended that treatments be administered over an extended time, which is longer than that observed in this study.

Classifying the walking pattern of humans on different surfaces using convolutional features and shallow machine learning classifiers

This study presents a methodology that combines convolution features with shallow classifiers for classifying the walking pattern on different surfaces. At first, convolution features are extracted from six different inertial measurement units (IMU) sensors mounted on the human body. The shallow classifiers namely quadratic SVM, wide neural network, fine KNN, and linear discriminant analysis are trained using convolution features that successfully pass through the global pooling layer of the CNN model. The proposed methodology is also evaluated on the features extracted from both individual IMU sensor and combined IMU sensors. It is observed that proposed methodology performs better for convolution features extracted from all IMU sensors combined together. The proposed methodology is also compared to the CNN model to demonstrate its efficacy. The obtained results show that the shallow classifier (quadratic SVM) achieves the maximum accuracy of 98.2%, whereas the CNN model achieves the accuracy of 90.73% only. Thus, the proposed methodology can be successfully utilised for classifying different walking surfaces based on the gait cycle data. The proposed approach can benefit in automatic gait adjustment of prosthetic foot based on the walking surfaces.

Reinforcement feedback impairs locomotor adaptation and retention.

Locomotor adaptation is a motor learning process used to alter spatiotemporal elements of walking that are driven by prediction errors, a discrepancy between the expected and actual outcomes of our actions. Sensory and reward prediction errors are two different types of prediction errors that can facilitate locomotor adaptation. Reward and punishment feedback generate reward prediction errors but have demonstrated mixed effects on upper extremity motor learning, with punishment enhancing adaptation, and reward supporting motor memory. However, an in-depth behavioral analysis of these distinct forms of feedback is sparse in locomotor tasks. For this study, three groups of healthy young adults were divided into distinct feedback groups [Supervised, Reward, Punishment] and performed a novel locomotor adaptation task where each participant adapted their knee flexion to 30 degrees greater than baseline, guided by visual supervised or reinforcement feedback (Adaptation). Participants were then asked to recall the new walking pattern without feedback (Retention) and after a washout period with feedback restored (Savings). We found that all groups learned the adaptation task with external feedback. However, contrary to our initial hypothesis, enhancing sensory feedback with a visual representation of the knee angle (Supervised) accelerated the rate of learning and short-term retention in comparison to monetary reinforcement feedback. Reward and Punishment displayed similar rates of adaptation, short-term retention, and savings, suggesting both types of reinforcement feedback work similarly in locomotor adaptation. Moreover, all feedback enhanced the aftereffect of locomotor task indicating changes to implicit learning. These results demonstrate the multi-faceted nature of reinforcement feedback on locomotor adaptation and demonstrate the possible different neural substrates that underly reward and sensory prediction errors during different motor tasks.

Movement strategies during obstacle crossing in people with Parkinson disease: A systematic review with meta-analysis.

Navigating obstacles involves adjusting walking patterns, particularly when stepping over them. This task may be particularly challenging for people with Parkinson disease (PD) for several reasons.This review aims to compare the spatiotemporal gait parameters of people with and without PD while stepping over obstacles. A systematic literature search was conducted in six databases (PubMed, Scopus, Web of Science, EBSCO, Embase, and SciELO) from inception to September 2023. Studies were selected that evaluated gait parameters of people with and without PD while walking over obstacles. Two independent researchers evaluated the eligibility and extracted gait parameters during obstacle crossing. The risk of bias was assessed using the Joanna Briggs Institute Critical Appraisal Checklist. Heterogeneity was assessed using I2-tests. Random effects models were determined for effect sizes as standardized mean differences (SMD). Twenty-five studies were included in the review and 17 in the meta-analysis. Most of the studies (58%) showed a low risk of bias. People with PD exhibit a shorter step when landing after crossing an obstacle (SMD = -0.50 [-0.69 to -0.31]). Compared to people without PD, people with PD also widen their support base (SMD = 0.27 [0.07-0.47]) and reduce gait velocity (SMD = -0.60 [-0.80 to -0.39]) when crossing the obstacle. People with PD adopt a more conservative motor behavior during obstacle crossing than those without PD, with a shorter step length when landing after crossing an obstacle, greater step width and lower crossing speed.

Increased trailing limb angle in hemiplegic patients after training with a knee orthosis: A randomized controlled trial.

Stroke often induces gait abnormality, such as buckling knee pattern, compromising walking ability. Previous studies indicated that an adequate trailing limb angle (TLA) is critical for recovering walking ability. We hypothesized that correcting gait abnormality by immobilizing the knee joint using a knee orthosis (KO) would improve walking patterns and increase the TLA, and investigated whether walking training using a KO would increase the TLA in post-stroke patients. In a randomized controlled trial, thirty-four participants were assigned to KO (walking training using a KO) and non-KO (without using a KO) groups. Twenty-nine completed the three-week gait training protocol. TLA was measured at baseline and after training. A two-way repeated ANOVA was performed to evaluate TLA increases with training type and time as test factors. A t-test compared TLA changes (ΔTLA) between the two groups. ANOVA showed a main effect for time (F = 64.5, p < 0.01) and interaction (F = 15.4, p < 0.01). ΔTLA was significantly higher in the KO group (14.6±5.8) than in the non-KO group (5.0±7.0, p < 0.001). Walking training using a KO may be practical and effective for increasing TLA in post-stroke patients.

Morphometric study of the legs of the main Chagas vector, Triatoma infestans (Hemiptera: Reduviidae)

In triatomines, vectors of Chagas disease, active dispersal takes place by walking and flying. Flight has received more attention than walking although the last is the dispersal modality used by nymphs due to their lack of wings and also used by adults, which would facilitate the colonization and reinfestation of houses after vector control actions. The present work studied the morphometrical variation of Triatoma infestans legs, the main vector of Chagas disease the Southern Cone of South America. We described morphometric traits and the natural variation of each leg segment. Different linear, size and shape variables of each component of the three right legs of fifth instar nymphs of T. infestans were analyzed using morphometric tools. We analyzed differentiation, variation and correlation for each segment across the fore-, mid and hind legs using different statistical approaches such as general linear model, canonical variates analysis, test of equality of coefficient of variation and partial least square analysis. We also analyzed variation and correlation between segments within each leg with partial least square and morphometric disparity analyses. Our results showed that the segments differed between legs, as general trends, the dimensions (length, width and/or size) were greater in the hind legs, smaller in the forelegs and intermediate in the mid ones. The femur and tibia (length and/or width) showed differences in morphometric variation between legs and the femur and tibia showed the highest levels of correlation between legs. On the other hand, in the fore- and mid legs, the femur (length or width) showed similar variation with tibia and tarsus lengths, but in the hind legs, the femur showed similar variation with all segments and not with the tibia length, and there were strong correlations between linear measurement within each leg. Our results suggest that the femur and tibia could play a determining role in the coordination between the legs that determines the walking pattern. Considering that these segments would also be linked to the specific function that each leg has, this study suggests a preponderant role of the femur and tibia in the walking locomotion of T. infestans.

GaitFormer: Leveraging dual-stream spatial–temporal Vision Transformer via a single low-cost RGB camera for clinical gait analysis

Gait analysis is an essential technique in treating patients with lower limb dysfunctions. Traditional methods often rely on expensive and complex equipment, such as wearable body sensors and a multi-camera with marker tracking system. Aiming for a more cost-effective yet accurate alternative, this paper introduces GaitFormer, a novel approach that leverages Vision Transformer (ViT) for gait analysis using minimal, non-invasive equipment, i.e. a single low-cost RGB camera. Initially, a unique dataset using a multi-camera system with marker tracking, comprising 6 walking patterns gathered from 80 volunteers is developed. The ViT-based GaitFormer is then proposed to automatically recognize human walking patterns through a single RGB camera. GaitFormer comprises hybrid networks for each step, including: (i) a cascaded convolutional 2D human key points estimation network; (ii) a ViT-based dual-stream spatial–temporal network extending the information of human key points into 3D; (iii) leveraging specific lower limb key joints’ angle features for clinical gait analysis, capturing the geometric, kinematic, and physical attributes of human motion; (iv) employing a pure self-attention-based classification network to recognize clinical human walking patterns. The experiments are designed to comprehensively validate each step against various related baseline methods and multi-camera tracking system, with results demonstrating the promising performance of GaitFormer as an affordable, precise, and integrated solution. To the best of our knowledge, GaitFormer is the first hybrid CNN- and ViT-based end-to-end solution via low-cost device for clinically valuable gait analysis.

Intersegmental coordination in human slip perturbation responses

Intersegmental coordination (ISC) of lower limbs and planar covariation law (PCL) are important phenomena observed in biomechanics of human walking and other activities. Gait perturbations tend to cause deviation from the expected ISC pattern thus violating PCL. We used a data set of seven subjects, who experienced unexpected slips, to investigate and characterize the evolution of ISC during slip recoveries and falls. We have analyzed and presented the development of ISC patterns, encompassing the step preceding the slip initiation and duration of slip until it stops. The results show that the ISC patterns during slip recovery deviate considerably from the normal walking patterns. A newly proposed Euclidian distance-based metric (EDM) was used to quantify the deviation from the normal walking ISC pattern during four slip recoveries and three falls evaluated at gait events such as slip start, foot strike, and peak height of the swing foot. The timing of gait events after slip, pattern of EDM, placement of the feet after slip and temporal patterns of each limb angle have been presented. This initial investigation provides insight into the ISC during slip recovery which highlights the human natural recovery trajectories during such perturbations. The observed patterns of the ISC trajectories during slip can be used for the design of human-inspired controllers for exoskeleton devices that can provide external assistance to human subjects during balance recovery.

Analysis of Gait Pattern Affected by Various Disease : A Review

Gait is pattern of walking of individual, is unique pattern of a person. The gait pattern is affected by various disease, ill condition of a person. In this review article we discuss about various diseases by which gait of an individual gets affected. Some disease are ; Parkinson's disease (PD) is a degenerative brain disorder causing shuffled gait, impaired balance, and freezing of gait. Morquio A syndrome, a group of disorders called mucopolysaccharidosis, can lead to vision, hearing, bone, brain, and heart problems. The anterior cruciate ligament (ACL) is a key stabilizer in the knee, and a torn ACL can cause instability when walking or changing directions. Examination of the gait pattern of a those person who having a disease such as ; Parkinson’s disease, Morquio A syndrome, Anterior Crucial Ligament, etc. In normal human the Gait Cycle has two phases ; Stance and swing phase. The stance phase covers approx 60% gait cycle and swing phase covers remaining 40% of gait cycle. In further studies we can analysis on how this cycle varies in abnormal walking.These review article summarises about gait pattern affected by various diseases. Study of gait pattern used for solving criminal cases as we can recognize various abnormalities a person may have by the analysis of his or her gait pattern. It is used as secondary evidence. By using gait pattern we can find out individuals age, sex, and height.

Gait Pattern Analysis Through Various Techniques and Methods - A Review

The gait cycle, which involves propelling the centre of gravity in the direction of motion, is the interval of time or series of action during locomotion from the moment one foot touches the ground to the moment that same foot contact the ground again. Examination of person’s waking style or standing and walking pattern called gait analysis. The result of this analysis can be used to determine the causes skeletal muscular Examination or neurological issues, as well as it is applicable in criminal investigation to find out the unique gait pattern of an individual by using the different parameters and technique.

Antie-theft Device Tracking System

This project's goal is to develop an Android application that offers SMS-based location tracking capabilities for Android devices. We can also follow the images of the individual who took our Android phone. This function supports Android OS and sends and receives emails and SMS in response to calls. With simple SMS commands, you can track your Android device. Tracing a location: We can use basic SMS commands to locate the misplaced phone. In a theft gadget, the camera can be remotely manipulated to take pictures. It is said of mobile gadgets that they are portable and that a person can carry them from one place to another. Mobile device theft occurs frequently, and the current system watches users' walking patterns and movements.

Multi-View Gait Analysis by Temporal Geometric Features of Human Body Parts.

A gait is a walking pattern that can help identify a person. Recently, gait analysis employed a vision-based pose estimation for further feature extraction. This research aims to identify a person by analyzing their walking pattern. Moreover, the authors intend to expand gait analysis for other tasks, e.g., the analysis of clinical, psychological, and emotional tasks. The vision-based human pose estimation method is used in this study to extract the joint angles and rank correlation between them. We deploy the multi-view gait databases for the experiment, i.e., CASIA-B and OUMVLP-Pose. The features are separated into three parts, i.e., whole, upper, and lower body features, to study the effect of the human body part features on an analysis of the gait. For person identity matching, a minimum Dynamic Time Warping (DTW) distance is determined. Additionally, we apply a majority voting algorithm to integrate the separated matching results from multiple cameras to enhance accuracy, and it improved up to approximately 30% compared to matching without majority voting.

Multi-WiIR: Multi-User Identity Legitimacy Authentication Based on WiFi Device

With the proliferation of WiFi devices, WiFi-based identification technology has garnered attention in the security domain and has demonstrated initial success. Nonetheless, when untrained illegitimate users appear, the classifier tends to categorize them as if they were trained users. In response to this issue, researchers have proposed identity legitimacy authentication systems to identify illicit users, albeit only applicable to individual users. In this article, we propose a multi-user legitimacy authentication system based on WiFi, termed Multi-WiIR. Leveraging WiFi signals, the system captures users’ walking patterns to ascertain their legitimacy. The core concept entails training a multi-branch deep neural network, designated WiIR-Net, for feature extraction of individual users. Binary classifiers are then applied to each user, and legitimacy is established by comparing the model’s output to predefined thresholds, thus facilitating multi-user legitimacy authentication. Moreover, the study experimentally investigated the impact of the number of legitimate individuals on accuracy rates. The results demonstrated that The Multi-WiIR system showed commendable performance with low latency, being capable of conducting legitimacy recognition in scenarios involving up to four users, with an accuracy rate reaching 85.11%.

Comparative Analysis of Gait Kinematics in Older Adults: Free Walking vs. Nordic Walking with Classic and Mechatronic Poles

This investigation aimed to scrutinise the kinematic and spatio-temporal characteristics of free and Nordic walking (NW) in older adults, utilising both traditional and biosensor-integrated mechatronic poles. The hypothesis was that including biosensors for gait analysis in NW poles would not disrupt the walking pattern of older adults compared to standard poles. The study involved seniors aged 65–74 who were amateur Nordic Walking (NW) practitioners. They were instructed to traverse a 100-m distance three times: without poles, with traditional NW poles, and with mechatronic poles. The MyoMOTION MR3 system was used to gather biomechanical data. The study revealed differences in eight kinematic parameters and stride time between free walking and walking with poles. However, no statistically significant differences were observed in any of the parameters, regardless of the pole type used. The findings suggest that older NW practitioners tend to employ free walking patterns even when using poles.

A Cross Sectional Study on Arch Index among Adolescent Females with Different Body Mass Index Strata

Females in adolescent age have their own way of walking pattern which is unique. Congenital variations are more common in the foot region. Adolescent foot morphology is dependent on gender, genetic, environmental and lifestyle factors. The present study is evidence for analysis of Arch Index within different body mass index strata among adolescent females. The body mass index is classified as underweight (&lt; 18.49), normal weight (18.5-24.9,) overweight (25 – 29.9) and obese (&gt;30). In current study, statistical analysis of Arch Index between the four Body mass index groups by ANOVA was done. High statistical significance (p value &lt; .001) of Arch Index(right),Arch Index(left) between the four BMI groups were identified. The understanding of the pedographic parameters will be informative to anatomists, orthopaedicians, and orthoses manufacturers.

Optimizing Nurse Workflow Efficiency: An Examination of Nurse Walking Behavior and Space Accessibility in Medical Surgical Units.

This study aimed to investigate the effect of spatial adjacencies on nurses' walking patterns and the subsequent impact on staff satisfaction with perceived accessibility and adjacency-related issues. Recognizing the crucial importance of spatial adjacencies in healthcare facilities is essential, as they significantly affect staff morale, fatigue management, operational efficiency, error reduction, and overall patient care excellence, highlighting the need for objective assessments to evaluate the impact of facility layout and space configuration on workflow patterns and staff satisfaction in patient care units. Integrating on-site observations with survey data, we explored how spatial adjacencies affect staff walking behavior and satisfaction in two med-surgical unit floors. The findings highlighted a significant frequency of movements between nurse stations, patient rooms, and medication areas. Regression analysis identified several contributing factors to staff satisfaction, including the proximity of supplies, team visibility, ease of access across departments, and the location of equipment rooms. Specifically, satisfaction with the proximity of supplies was positively associated with increased provider satisfaction with workflow, quality of care, and workplace. Additionally, valuable feedback from staff revealed concerns regarding break room placement, medication area functionality, and disparities in the availability of supplies. This study highlighted the critical need for carefully planned spatial adjacency strategies to enhance workflow efficiency and raise clinical staff satisfaction within healthcare facilities. The actionable insights gleaned from this research offer valuable direction to architects, healthcare administrators, and design professionals, enabling the creation of environments that positively resonate with healthcare providers and improve healthcare operations.

Exploration and demonstration of explainable machine learning models in prosthetic rehabilitation-based gait analysis.

Quantitative gait analysis is important for understanding the non-typical walking patterns associated with mobility impairments. Conventional linear statistical methods and machine learning (ML) models are commonly used to assess gait performance and related changes in the gait parameters. Nonetheless, explainable machine learning provides an alternative technique for distinguishing the significant and influential gait changes stemming from a given intervention. The goal of this work was to demonstrate the use of explainable ML models in gait analysis for prosthetic rehabilitation in both population- and sample-based interpretability analyses. Models were developed to classify amputee gait with two types of prosthetic knee joints. Sagittal plane gait patterns of 21 individuals with unilateral transfemoral amputations were video-recorded and 19 spatiotemporal and kinematic gait parameters were extracted and included in the models. Four ML models-logistic regression, support vector machine, random forest, and LightGBM-were assessed and tested for accuracy and precision. The Shapley Additive exPlanations (SHAP) framework was applied to examine global and local interpretability. Random Forest yielded the highest classification accuracy (98.3%). The SHAP framework quantified the level of influence of each gait parameter in the models where knee flexion-related parameters were found the most influential factors in yielding the outcomes of the models. The sample-based explainable ML provided additional insights over the population-based analyses, including an understanding of the effect of the knee type on the walking style of a specific sample, and whether or not it agreed with global interpretations. It was concluded that explainable ML models can be powerful tools for the assessment of gait-related clinical interventions, revealing important parameters that may be overlooked using conventional statistical methods.