Search results for: Gait analysis

Authors: Ji-il Park, Min Kyu Yu, Jong-woo Lee, Sam-hyeon Yoo

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The purpose of this research is to analyze the gait strategy between the normal and loaded gait. To this end, five male participants satisfied two conditions: the normal and loaded gait (backpack load 25.2 kg). As expected, results showed that additional loads elicited not a proportional increase in vertical and shear ground reaction force (GRF) parameters but also increase of the impulse, momentum and mechanical work. However, in case of the loaded gait, the time duration of the double support phase was increased unexpectedly. It is because the double support phase which is more stable than the single support phase can reduce instability of the loaded gait. Also, the directions of the pre-collision and after-collision were moved upward and downward compared to the normal gait. As a result, regardless of the additional backpack load, the impulse-momentum diagram during the step-to-step transition was maintained such as the normal gait. It means that human walk efficiently to keep stability and minimize total net works in case of the loaded gait.

Keywords: normal gait, loaded gait, impulse, collision, gait analysis, mechanical work, backpack load

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Authors: Chirawat Wattanapanich, Hong Wei

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This study presents new gait representations for improving gait recognition accuracy on cross gait appearances, such as normal walking, wearing a coat and carrying a bag. Based on the Gait Energy Image (GEI), two ideas are implemented to generate new gait representations. One is to append lower knee regions to the original GEI, and the other is to apply convolutional operations to the GEI and its variants. A set of new gait representations are created and used for training multi-class Support Vector Machines (SVMs). Tests are conducted on the CASIA dataset B. Various combinations of the gait representations with different convolutional kernel size and different numbers of kernels used in the convolutional processes are examined. Both the entire images as features and reduced dimensional features by Principal Component Analysis (PCA) are tested in gait recognition. Interestingly, both new techniques, appending the lower knee regions to the original GEI and convolutional GEI, can significantly contribute to the performance improvement in the gait recognition. The experimental results have shown that the average recognition rate can be improved from 75.65% to 87.50%.

Keywords: convolutional image, lower knee, gait

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Authors: Dae-gun Kim, Hyun-joo Kang

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Purpose: The purpose of this study was to investigate the effects of aging on center of pressure, gait angle and gait time. Methods: 29 healthy female college students(FCS) and 28 elderly women (EW) were recruited to participate in this study. A gait analysis system( Gaitview, Korea) was used to collect the center of pressure in static state and gait angle with gait time in dynamic state. Results: Results of the center of pressure do not have significant differences between two groups. In the gait angle test, the FCS showed 1.56±5.2° on their left while the EW showed 9.76±6.54° on their left. In their right, the FCS showed 2.85±6.47° and the EW showed 10.27±6.97°. In the gait angle test, there was a significant difference in the gait time between the female college students and elderly women. A significant difference was evident in the gait time. The FCS on the left was 0.87±0.1sec while the EW’s was 1.28±0.44sec. The FCS on the right was 0.86±0.09sec and the EW was 1.1±0.21sec. The results of this study revealed that the elderly participants aging musculoskeletal system and subsequent changes in their posture altered gait angle and gait time. Therefore, this widening is due to their need to leave their feet on the ground longer for stability slowing their movement. Conclusions: In conclusion, it is advisable to develop an exercise program for the elderly focusing on stability the prevention of falls.

Keywords: center of pressure, gait angle, gait time, elderly women

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Authors: Kang Sungjae

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This research proposes a gait stability evaluation technique based on the linear inverted pendulum model and moving support foot Zero Moment Point. With this, an improvement towards the gait analysis of the orthosis walk is validated. The application of Lagrangian mechanics approximation to the solutions of the dynamics equations for the linear inverted pendulum does not only simplify the solution, but it provides a smooth Zero Moment Point for the double feet support phase. The Zero Moment Point gait analysis techniques mentioned above validates reference trajectories for the center of mass of the gait orthosis, the timing of the steps and landing position references for the swing feet. The stability evaluation technique are tested with a 6 DOF powered gait orthosis. The results obtained are promising for implementations.

Keywords: locomotion, center of mass, gait stability, linear inverted pendulum model

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Authors: Lavanya Srinivasan

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Biometric identification is to identify unique features in a person like fingerprints, iris, ear, and voice recognition that need the subject's permission and physical contact. Gait biometric is used to identify the unique gait of the person by extracting moving features. The main advantage of gait biometric to identify the gait of a person at a distance, without any physical contact. In this work, the gait biometric is used for person re-identification. The person walking naturally compared with the same person walking with bag, coat, and case recorded using longwave infrared, short wave infrared, medium wave infrared, and visible cameras. The videos are recorded in rural and in urban environments. The pre-processing technique includes human identified using YOLO, background subtraction, silhouettes extraction, and synthesis Gait Entropy Image by averaging the silhouettes. The moving features are extracted from the Gait Entropy Energy Image. The extracted features are dimensionality reduced by the principal component analysis and recognised using different classifiers. The comparative results with the different classifier show that linear discriminant analysis outperforms other classifiers with 95.8% for visible in the rural dataset and 94.8% for longwave infrared in the urban dataset.

Keywords: biometric, gait, silhouettes, YOLO

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Authors: Jyoti Bharti, Navneet Manjhi, M. K.Gupta, Bimi Jain

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A reliable gait features are required to extract the gait sequences from an images. In this paper suggested a simple method for gait identification which is based on moments. Moment values are extracted on different number of frames of gray scale and silhouette images of CASIA database. These moment values are considered as feature values. Fuzzy logic and nearest neighbour classifier are used for classification. Both achieved higher recognition.

Keywords: gait, fuzzy logic, nearest neighbour, recognition rate, moments

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Authors: S. M. Khairul Halim, Mojtaba Ghodsi, Morteza Mohammadzaheri

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Gait analysis is essential for diagnosing musculoskeletal and neurological conditions. However, current methods are often complex and expensive. This paper introduces a methodology for analysing gait parameters using a smart insole with a built-in accelerometer. The system measures stance time, swing time, step count, and cadence and wirelessly transmits data to a user-friendly IoT dashboard for centralized processing. This setup enables remote monitoring and advanced data analytics, making it a versatile tool for medical diagnostics and everyday usage. Integration with IoT enhances the portability and connectivity of the device, allowing for secure, encrypted data access over the Internet. This feature supports telemedicine and enables personalized treatment plans tailored to individual needs. Overall, the approach provides a cost-effective (almost 25 GBP), accurate, and user-friendly solution for gait analysis, facilitating remote tracking and customized therapy.

Keywords: gait analysis, IoT, smart insole, accelerometer sensor

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Authors: C. G. Shashi Kumar, G. Arun Maiya, H. Manjunath Hande, K. V. Rajagopal

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Background: Diabetes mellitus (DM) is a metabolic disorder with involvement of neurovascular and muscular system. Studies have documented that the gait parameter is altered in type 2 diabetes mellitus with peripheral neuropathy. However, there is a dearth of literature regarding the gait characteristics in type 2 diabetes mellitus (T2DM) without peripheral neuropathy. Therefore, the present study is focused on identifying gait changes in early type 2 diabetes mellitus without peripheral neuropathy. Objective: To analyze the gait characteristics in Type 2 diabetes mellitus without peripheral neuropathy. Methods: After obtaining ethical clearance from Institutional Ethical Committee (IEC), 36 T2DM without peripheral neuropathy and 32 matched healthy subjects were recruited. Gait characteristics (step duration, gait cycle length, gait cycle duration, stride duration, step length, double stance duration) of all the subjects were analyzed using Windtrack dynamic foot scanner. Data were analyzed using Independent‘t’ test to find the difference between the groups (step duration, gait cycle length, gait cycle duration) and Mann-Whitney test was used to analyze the step length and double stance duration to find difference between the groups. Level of significance was kept at P<0.05. Results: Result analysis showed significant decrease in step duration, gait cycle length, gait cycle duration, step length, double stance duration in T2DM subjects as compared to healthy subjects. We also observed a mean increase in stride duration in T2DM subjects compared to healthy subjects.

Keywords: type 2 diabetes mellitus, dynamic foot scan, gait characteristics, medical and health sciences

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Authors: Stepanov Ivan, Musalimov Viktor, Monahov Uriy

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This report examines the current state of human gait simulator development based on the human hip joint model. This unit will create a database of human gait types, useful for setting up and calibrating mechano devices, as well as the creation of new systems of rehabilitation, exoskeletons and walking robots. The system has ample opportunity to configure the dimensions and stiffness, while maintaining relative simplicity.

Keywords: hip joint, human gait, physiotherapy, simulation

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Authors: Nupur Karmaker, Hasin Aupama Azhari, Abdul Al Mortuza, Abhijit Chanda, Golam Abu Zakaria

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Purpose: The purpose of gait analysis is to determine the biomechanics of the joint, phases of gait cycle, graphical and analytical analysis of degree of rotation, analysis of the electrical activity of muscles and force exerted on the hip joint at different locomotion during walking, running and cart pulling. Methods and Materials: Visual gait analysis and electromyography method has been used to detect the degree of rotation of joints and electrical activity of muscles. In cinematography method an object is observed from different sides and takes its video. Cart pulling length has been divided into frames with respect to time by using video splitter software. Phases of gait cycle, degree of rotation of joints, EMG profile and force analysis during walking and running has been taken from different papers. Gait cycle and degree of rotation of joints during cart pulling has been prepared by using video camera, stop watch, video splitter software and Microsoft Excel. Results and Discussion: During the cart pulling the force exerted on hip is the resultant of various forces. The force on hip is the vector sum of the force Fg= mg, due the body of weight of the person and Fa= ma, due to the velocity. Maximum stance phase shows during cart pulling and minimum shows during running. During cart pulling shows maximum degree of rotation of hip joint, knee: running, and ankle: cart pulling. During walking, it has been observed minimum degree of rotation of hip, ankle: during running. During cart pulling, dynamic force depends on the walking velocity, body weight and load weight. Conclusions: 80% people suffer gait related disease with increasing their age. Proper care should take during cart pulling. It will be better to establish the gait laboratory to determine the gait related diseases. If the way of cart pulling is changed i.e the design of cart pulling machine, load bearing system is changed then it would possible to reduce the risk of limb loss, flat foot syndrome and varicose vein in lower limb.

Keywords: kinematic, gait, gait lab, phase, force analysis

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Authors: Sungpil Ha, Ju Yong Kang, Sangbaek Park, Seung-Ju Lee, Soo-Won Chae

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The growing number of obese patients in aging societies has led to an increase in the number of patients with knee medial osteoarthritis (OA). Artificial joint insertion is the most common treatment for knee medial OA. Surgery is effective for patients with serious arthritic symptoms, but it is costly and dangerous. It is also inappropriate way to prevent a disease as an early stage. Therefore Non-operative treatments such as toe-in gait are proposed recently. Toe-in gait is one of non-surgical interventions, which restrain the progression of arthritis and relieves pain by reducing knee adduction moment (KAM) to facilitate lateral distribution of load on to knee medial cartilage. Numerous studies have measured KAM in various foot progression angle (FPA), and KAM data could be obtained by motion analysis. However, variations in stress at knee cartilage could not be directly observed or evaluated by these experiments of measuring KAM. Therefore, this study applied motion analysis to major gait points (1st peak, mid –stance, 2nd peak) with regard to FPA, and to evaluate the effects of FPA on the human lower extremity, the finite element (FE) method was employed. Three types of gait analysis (toe-in, toe-out, baseline gait) were performed with markers placed at the lower extremity. Ground reaction forces (GRF) were obtained by the force plates. The forces associated with the major muscles were computed using GRF and marker trajectory data. MRI data provided by the Visible Human Project were used to develop a human lower extremity FE model. FE analyses for three types of gait simulations were performed based on the calculated muscle force and GRF. We observed the maximum stress point during toe-in gait was lower than the other types, by comparing the results of FE analyses at the 1st peak across gait types. This is the same as the trend exhibited by KAM, measured through motion analysis in other papers. This indicates that the progression of knee medial OA could be suppressed by adopting toe-in gait. This study integrated motion analysis with FE analysis. One advantage of this method is that re-modeling is not required even with changes in posture. Therefore another type of gait simulation or various motions of lower extremity can be easily analyzed using this method.

Keywords: finite element analysis, gait analysis, human model, motion capture

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Authors: Murad Almadani, Khalil Abu-Hantash, Xinyu Wang, Herbert Jelinek, Kinda Khalaf

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Gait analysis is used by healthcare professionals as a tool to gain a better understanding of the movement impairment and track progress. In most circumstances, monitoring patients in their real-life environments with low-cost equipment such as cameras and wearable sensors is more important. Inertial sensors, on the other hand, cannot provide enough information on angular dynamics. This research offers a method for tracking 2D joint coordinates using cutting-edge vision algorithms and a single RGB camera. We provide an end-to-end comprehensive deep learning pipeline for marker-less gait parameter estimation, which, to our knowledge, has never been done before. To make our pipeline function in real-time for real-world applications, we leverage the AlphaPose human posture prediction model and a deep learning transformer. We tested our approach on the well-known GPJATK dataset, which produces promising results.

Keywords: gait analysis, human pose estimation, deep learning, real time gait estimation, AlphaPose, transformer

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Authors: Athanasios Triantafyllou, Georgios Papagiannis, Vassilios Nikolaou, Panayiotis J. Papagelopoulos, George C. Babis

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In vitro measurements are widely used in order to predict THAs wear rate implementing gait kinematic and kinetic parameters. Clinical tests of materials and designs are crucial to prove the accuracy and validate such measurements. The purpose of this study is to examine the affection of THA gait kinematics and kinetics on wear during gait, the essential functional activity of humans, by comparing in vivo gait data to in vitro results. Our study hypothesis is that both implants will present the same hip joint kinematics and kinetics during gait. 127 unilateral primary cementless total hip arthroplasties were included in the research. Independent t-tests were used to identify a statistically significant difference in kinetic and kinematic data extracted from 3D gait analysis. No statistically significant differences observed at mean peak abduction, flexion and extension moments between the two groups (P.abduction= 0,125, P.flexion= 0,218, P.extension= 0,082). The kinematic measurements show no statistically significant differences too (Prom flexion-extension= 0,687, Prom abduction-adduction= 0,679). THA kinematics and kinetics during gait are important biomechanical parameters directly associated with implants wear. In vitro studies report less wear in CoC than CoXLPE when tested with the same gait cycle kinematic protocol. Our findings confirm that both implants behave identically in terms of kinematics in the clinical environment, thus strengthening in vitro results of CoC advantage. Correlated to all other significant factors that affect THA wear could address in a complete prism the wear on CoC and CoXLPE.

Keywords: total hip arthroplasty biomechanics, THA gait analysis, ceramic on ceramic kinematics, ceramic on XLPE kinetics, total hip replacement wear

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Authors: Vignesh Ratnaraj, Jaewon Chang

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Background: Frailty is associated with poorer outcomes in cardiac surgery, but the heterogeneity in frailty assessment tools makes it difficult to ascertain its true impact in cardiac surgery. Slow gait speed is a simple, validated, and reliable marker of frailty. We performed a systematic review and meta-analysis to examine the effect of slow gait speed on postoperative cardiac surgical patients. Methods: PubMED, MEDLINE, and EMBASE databases were searched from January 2000 to August 2021 for studies comparing slow gait speed and “normal” gait speed. The primary outcome was in-hospital mortality. Secondary outcomes were composite mortality and major morbidity, AKI, stroke, deep sternal wound infection, prolonged ventilation, discharge to a healthcare facility, and ICU length of stay. Results: There were seven eligible studies with 36,697 patients. Slow gait speed was associated with an increased likelihood of in-hospital mortality (risk ratio [RR]: 2.32; 95% confidence interval [CI]: 1.87–2.87). Additionally, they were more likely to suffer from composite mortality and major morbidity (RR: 1.52; 95% CI: 1.38–1.66), AKI (RR: 2.81; 95% CI: 1.44–5.49), deep sternal wound infection (RR: 1.77; 95% CI: 1.59–1.98), prolonged ventilation >24 h (RR: 1.97; 95% CI: 1.48–2.63), reoperation (RR: 1.38; 95% CI: 1.05–1.82), institutional discharge (RR: 2.08; 95% CI: 1.61–2.69), and longer ICU length of stay (MD: 21.69; 95% CI: 17.32–26.05). Conclusion: Slow gait speed is associated with poorer outcomes in cardiac surgery. Frail patients are twofold more likely to die during hospital admission than non-frail counterparts and are at an increased risk of developing various perioperative complications.

Keywords: cardiac surgery, gait speed, recovery, frailty

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Authors: Sina Saadati, Mohammadreza Razzazi

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In this article, we have tried to present an agent-based model of human muscle. A suitable model of muscle is necessary for the analysis of mankind's movements. It can be used by clinical researchers who study the influence of motion sicknesses, like Parkinson's disease. It is also useful in the development of a prosthesis that receives the electromyography signals and generates force as a reaction. Since we have focused on computational efficiency in this research, the model can compute the calculations very fast. As far as it concerns prostheses, the model can be known as a charge-efficient method. In this paper, we are about to illustrate an agent-based model. Then, we will use it to simulate the human gait cycle. This method can also be done reversely in the analysis of gait in motion sicknesses.

Keywords: agent-based modeling and simulation, human muscle, gait cycle, motion sickness

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Authors: Nawaf Al Khashram, Graham Arnold, Weijie Wang

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Background—Gait classifying allows clinicians to differentiate gait patterns into clinically important categories that help in clinical decision making. Reliable comparison of gait data between normal and patients requires knowledge of the gait parameters of normal children's specific age group. However, there is still a lack of the gait database for normal children of different ages. Objectives—The aim of this study is to investigate the kinematics of the lower limb joints during gait for normal children in different age groups. Methods—Fifty-three normal children (34 boys, 19 girls) were recruited in this study. All the children were aged between 5 to 16 years old. Age groups were defined as three types: young child aged (5-7), child (8-11), and adolescent (12-16). When a participant agreed to take part in the project, their parents signed a consent form. Vicon® motion capture system was used to collect gait data. Participants were asked to walk at their comfortable speed along a 10-meter walkway. Each participant walked up to 20 trials. Three good trials were analyzed using the Vicon Plug-in-Gait model to obtain parameters of the gait, e.g., walking speed, cadence, stride length, and joint parameters, e.g. joint angle, force, moments, etc. Moreover, each gait cycle was divided into 8 phases. The range of motion (ROM) angle of pelvis, hip, knee, and ankle joints in three planes of both limbs were calculated using an in-house program. Results—The temporal-spatial variables of three age groups of normal children were compared between each other; it was found that there was a significant difference (p < 0.05) between the groups. The step length and walking speed were gradually increasing from young child to adolescent, while cadence was gradually decreasing from young child to adolescent group. The mean and standard deviation (SD) of the step length of young child, child and adolescent groups were 0.502 ± 0.067 m, 0.566 ± 0.061 m and 0.672 ± 0.053 m, respectively. The mean and SD of the cadence of the young child, child and adolescent groups were 140.11±15.79 step/min, 129±11.84 step/min, and a 115.96±6.47 step/min, respectively. Moreover, it was observed that there were significant differences in kinematic parameters, either whole gait cycle or each phase. For example, RoM of knee angle in the sagittal plane in whole cycle of young child group is (65.03±0.52 deg) larger than child group (63.47±0.47 deg). Conclusion—Our result showed that there are significant differences between each age group in the gait phases and thus children walking performance changes with ages. Therefore, it is important for the clinician to consider age group when analyzing the patients with lower limb disorders before any clinical treatment.

Keywords: age group, gait analysis, kinematics, normal children

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Authors: Vedat Kurt, Tansel Koyunoglu, Gamze Kurt, Ozgen Aras

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Low back pain is one of the most common health problem in public. Common symptoms that can be associated with low back pain include; pain, functional disability, gait disturbances. The aim of the study was to investigate the differences between disability scores and gait parameters in subjects with low back pain. Sixty participants are included in our study, (35 men, 25 women, mean age: 37.65±10.02 years). Demographic characteristics of participants were recorded. Pain (visual analog scale) and disability level (Oswestry Disability Index(ODI)) were evaluated. Gait parameters were measured with Zebris-FDM-2 platform. Independent samples t-test was used to analyse the differences between subjects with under 40 points (n=31, mean age:35.8±11.3) and above 40 points (n=29, mean age:39.6±8.1) of ODI scores. Significant level in statistical analysis was accepted as 0.05. There was no significant difference between the ODI scores and groups’ ages. Statistically significant differences were found in step width between subjects with under 40 points of ODI and above 40 points of ODI score(p < 0.05). But there were non-significant differences with other gait parameters (p > 0.05). The differences between gait parameters and pain scores were not statistically significant (p > 0.05). Researchers generally agree that individuals with LBP walk slower and take shorter steps and have asymmetric step lengths when compared with than their age-matched pain-free counterparts. Also perceived general disability may have moderate correlation with walking performance. In the current study, the patients classified as minimal/moderate and severe disability level by using ODI scores. As a result, a patient with LBP who have higher disability level tends to increase support surface. On the other hand, we did not find any relation between pain intensity and gait parameters. It may be caused by the classification system of pain scores. Additional research is needed to investigate the effects of functionality level and pain intensity on gait in subjects with low back pain under different classification types.

Keywords: functionality, low back pain, gait, pain

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Authors: Sangbaek Park, Seungju Lee, Soo-Won Chae

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Unstable shoes are known to strengthen lower extremity muscles and improve gait ability and to change the user’s gait pattern. The change in gait pattern affects human body enormously because the walking is repetitive and steady locomotion in daily life. It is possible to estimate the joint motion including joint moment, force and inertia effect using kinematic and kinetic analysis. However, the change of internal stress at the articular cartilage has not been possible to estimate. The purpose of this research is to evaluate the internal stress of human body during gait with unstable shoes. In this study, FE analysis was combined with motion capture experiment to obtain the boundary condition and loading condition during walking. Motion capture experiments were performed with a participant during walking with normal shoes and with unstable shoes. Inverse kinematics and inverse kinetic analysis was performed with OpenSim. The joint angle and muscle forces were estimated as results of inverse kinematics and kinetics analysis. A detailed finite element (FE) lower extremity model was constructed. The joint coordinate system was added to the FE model and the joint coordinate system was coincided with OpenSim model’s coordinate system. Finally, the joint angles at each phase of gait were used to transform the FE model’s posture according to actual posture from motion capture. The FE model was transformed into the postures of three major phases (1st peak of ground reaction force, mid stance and 2nd peak of ground reaction force). The direction and magnitude of muscle force were estimated by OpenSim and were applied to the FE model’s attachment point of each muscle. Then FE analysis was performed to compare the stress at knee cartilage during gait with normal shoes and unstable shoes.

Keywords: finite element analysis, gait analysis, human model, motion capture

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Authors: Mariana Volpini, Volker Bartenbach, Marcos Pinotti, Robert Riener

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Restoration of gait ability is an important task in the rehabilitation of people with neurological disorders presenting a great impact in the quality of life of an individual. Based on the motor learning concept, robotic assisted treadmill training has been introduced and found to be a feasible and promising therapeutic option in neurological rehabilitation but unfortunately it is not available for most patients in developing countries due to the high cost. This paper presents the concept of a low cost rehabilitation robot to help consolidate the robotic-assisted gait training as a reality in clinical practice in most countries. This work indicates that it is possible to build a simpler rehabilitation device respecting the physiological trajectory of the ankle.

Keywords: bioengineering, gait therapy, low cost rehabilitation robot, rehabilitation robotics

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Authors: Naznine Anwar, Kim Cornish, Izelle Labuschagne, Nellie Georgiou-Karistianis

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Falls and subsequent injuries are common features in symptomatic Huntington’s disease (symp-HD) individuals. As part of daily walking, navigating around obstacles may incur a greater risk of falls in symp-HD. We designed obstacle-crossing experiment to examine adaptive gait dynamics and to identify underlying spatiotemporal gait characteristics that could increase the risk of falling in symp-HD. This experiment involved navigating around one or two ground-based obstacles under two conditions (walking while navigating around one obstacle, and walking while navigating around two obstacles). A total of 32 participants were included, 16 symp-HD and 16 healthy controls with age and sex matched. We used a GAITRite electronic walkway to examine the spatiotemporal gait characteristics and inter-trail gait variability when participants walked at their preferable speed. A minimum of six trials were completed which were performed for baseline free walk and also for each and every condition during navigating around the obstacles. For analysis, we separated all walking steps into three phases as approach steps, navigating steps and recovery steps. The mean and inter-trail variability (within participant standard deviation) for each step gait variable was calculated across the six trails. We found symp-HD individuals significantly decreased their gait velocity and step length and increased step duration variability during the navigating steps and recovery steps compared with approach steps. In contrast, HC individuals showed less difference in gait velocity, step time and step length variability from baseline in both respective conditions as well as all three approaches. These findings indicate that increasing spatiotemporal gait variability may be a possible compensatory strategy that is adopted by symp-HD individuals to effectively navigate obstacles during walking. Such findings may offer benefit to clinicians in the development of strategies for HD individuals to improve functional outcomes in the home and hospital based rehabilitation program.

Keywords: Huntington’s disease, gait variables, navigating around obstacle, basal ganglia dysfunction

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Authors: Neeraj Vij, Christian Leber, Kenneth Schmidt

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Introduction: Total knee arthroplasty is a common procedure. It is well known that the biomechanics of the knee do not fully return to their normal state. Motion analysis has been used to study the biomechanics of the knee after total knee arthroplasty. The purpose of this scoping review is to summarize the current use of gait analysis in total knee arthroplasty and to identify the preoperative motion analysis parameters for which a systematic review aimed at determining the reliability and validity may be warranted. Materials and Methods: This IRB-exempt scoping review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) checklist strictly. Five search engines were searched for a total of 279 articles. Articles underwent a title and abstract screening process followed by full-text screening. Included articles were placed in the following sections: the role of gait analysis as a research tool for operative decisions, other research applications for motion analysis in total knee arthroplasty, gait analysis as a tool in predicting radiologic outcomes, gait analysis as a tool in predicting clinical outcomes. Results: Eleven articles studied gait analysis as a research tool in studying operative decisions. Motion analysis is currently used to study surgical approaches, surgical techniques, and implant choice. Five articles studied other research applications for motion analysis in total knee arthroplasty. Other research applications for motion analysis currently include studying the role of the unicompartmental knee arthroplasty and novel physical therapy protocols aimed at optimizing post-operative care. Two articles studied motion analysis as a tool for predicting radiographic outcomes. Preoperative gait analysis has identified parameters than can predict postoperative tibial component migration. 15 articles studied motion analysis in conjunction with clinical scores. Conclusions: There is a broad range of applications within the research domain of total knee arthroplasty. The potential application is likely larger. However, the current literature is limited by vague definitions of ‘gait analysis’ or ‘motion analysis’ and a limited number of articles with preoperative and postoperative functional and clinical measures. Knee adduction moment, knee adduction impulse, total knee range of motion, varus angle, cadence, stride length, and velocity have the potential for integration into composite clinical scores. A systematic review aimed at determining the validity, reliability, sensitivities, and specificities of these variables is warranted.

Keywords: motion analysis, joint replacement, patient-reported outcomes, knee surgery

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Authors: A. Alzahrani, G. Arnold, W. Wang

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Background: Stroke commonly occurs in middle-aged and elderly populations, and the diagnosis of early stroke is still difficult. Patients who have suffered a stroke have different balance and gait patterns from healthy people. Advanced techniques of motion analysis have been routinely used in the clinical assessment of cerebral palsy. However, so far, little research has been done on the direct diagnosis of early stroke patients using motion analysis. Objectives: The aim of this study was to investigate whether patients with stroke have different balance and gait from healthy people and which biomechanical parameters could be used to predict and diagnose potential patients who are at a potential risk to stroke. Methods: Thirteen patients with stroke were recruited as subjects whose gait and balance was analysed. Twenty normal subjects at the matched age participated in this study as a control group. All subjects’ gait and balance were collected using Vicon Nexus® to obtain the gait parameters, kinetic, and kinematic parameters of the hip, knee, and ankle joints in three planes of both limbs. Participants stood on force platforms to perform a single leg balance test. Then, they were asked to walk along a 10 m walkway at their comfortable speed. Participants performed 6 trials of single-leg balance for each side and 10 trials of walking. From the recorded trials, three good ones were analysed using the Vicon Plug-in-Gait model to obtain gait parameters, e.g., walking speed, cadence, stride length, and joint parameters, e.g., joint angle, force, moments, etc. Result: The temporal-spatial variables of Stroke subjects were compared with the healthy subjects; it was found that there was a significant difference (p < 0.05) between the groups. The step length, speed, cadence were lower in stroke subjects as compared to the healthy groups. The stroke patients group showed significantly decreased in gait speed (mean and SD: 0.85 ± 0.33 m/s), cadence ( 96.71 ± 16.14 step/min), and step length (0.509 ± 017 m) in compared to healthy people group whereas the gait speed was 1.2 ± 0.11 m/s, cadence 112 ± 8.33 step/min, and step length 0.648 ± 0.43 m. Moreover, it was observed that patients with stroke have significant differences in the ankle, hip, and knee joints’ kinematics in the sagittal and coronal planes. Also, the result showed that there was a significant difference between groups in the single-leg balance test, e.g., maintaining single-leg stance time in the stroke patients showed shorter duration (5.97 ± 6.36 s) in compared to healthy people group (14.36 ± 10.20 s). Conclusion: Our result showed that there are significantly differences between stroke patients and healthy subjects in the various aspects of gait analysis and balance test, as a consequences of these findings some of the biomechanical parameters such as joints kinematics, gait parameters, and single-leg stance balance test could be used in clinical practice to predict and diagnose potential patients who are at a high risk of further stroke.

Keywords: gait analysis, kinetics, kinematics, single-leg stance, Stroke

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Authors: P. Shrivastava, A. Shukla, K. Verma, S. Rungta

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Parkinson's disease is a chronic neurological disorder that directly affects human gait. It leads to slowness of movement, causes muscle rigidity and tremors. Gait serve as a primary outcome measure for studies aiming at early recognition of disease. Using gait techniques, this paper implements efficient binary bat algorithm for an early detection of Parkinson's disease by selecting optimal features required for classification of affected patients from others. The data of 166 people, both fit and affected is collected and optimal feature selection is done using PSO and Bat algorithm. The reduced dataset is then classified using neural network. The experiments indicate that binary bat algorithm outperforms traditional PSO and genetic algorithm and gives a fairly good recognition rate even with the reduced dataset.

Keywords: parkinson, gait, feature selection, bat algorithm

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Authors: Mehdi Razeghi

Abstract:

Background: The purpose of this case series was to quantify gait to study muscular dystrophy disease. In this research, the quantitative differences between normal and waddling gaits were assessed by force plate analysis. Methods: Nineteen myopathy patients and twenty normal subjects serving as the control group participated in this research. In this study, quantitative analyses of gait have been used to investigate the differences between the mobility of normal subjects and myopathy patients. This study was carried out at the Iranian Muscular Dystrophy Association in Boali Hospital, Tehran, Iran, from October 2015 to July 2020. Patient data were collected from Iranian Muscular Dystrophy Association members. individuals signed an informed consent form approved by the ethics committee of the Azad University. All of the gait tests were performed using a Kistler force platform. Participants walked at a self-selected speed, barefoot, independently, and without assistive devices. Results: Our findings indicate that there were no significant differences between the patients and the control group in the anterior-posterior components of the ground reaction forces; however, there were considerable differences in the force components between the groups in the medial-lateral and vertical directions of the ground reaction force. In addition, there were significant differences in the time parameters between the groups in the vertical and medial-lateral directions.

Keywords: biomechanics, force plate analysis, gait disorder, ground reaction force, kinetic analysis, myopathy disease, rehabilitation engineering

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Authors: Soofiyan Atar, Adil Shaikh, Sahil Rajpurkar, Pragnesh Bhalala, Aniket Desai, Irfan Siddavatam

Abstract:

Deep reinforcement learning (deep RL) algorithms leverage the symbolic power of complex controllers by automating it by mapping sensory inputs to low-level actions. Deep RL eliminates the complex robot dynamics with minimal engineering. Deep RL provides high-risk involvement by directly implementing it in real-world scenarios and also high sensitivity towards hyperparameters. Tuning of hyperparameters on a pneumatic quadruped robot becomes very expensive through trial-and-error learning. This paper presents an automated learning control for a pneumatic quadruped robot using sample efficient deep Q learning, enabling minimal tuning and very few trials to learn the neural network. Long training hours may degrade the pneumatic cylinder due to jerk actions originated through stochastic weights. We applied this method to the pneumatic quadruped robot, which resulted in a hopping gait. In our process, we eliminated the use of a simulator and acquired a stable gait. This approach evolves so that the resultant gait matures more sturdy towards any stochastic changes in the environment. We further show that our algorithm performed very well as compared to programmed gait using robot dynamics.

Keywords: model-based reinforcement learning, gait stability, supervised learning, pneumatic quadruped

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Authors: Mohamed Ahmed Fouad

Abstract:

Background: Stroke is the most leading cause to functional disability and gait problems. Objectives: The purpose of this study was to determine the effect of rhythmic auditory stimulation combined with treadmill training on selected gait kinematics in stroke patients. Methods: Thirty male stroke patients participated in this study. The patients were assigned randomly into two equal groups, (study and control). Patients in the study group received treadmill training combined with rhythmic auditory stimulation in addition to selected physical therapy program for hemiparetic patients. Patients in the control group received treadmill training in addition to the same selected physical therapy program including strengthening, stretching, weight bearing, balance exercises and gait training. Biodex gait trainer 2 TM was used to assess selected gait kinematics (step length, step cycle, walking speed, time on each foot and ambulation index) before and after six weeks training period (end of treatment) for both groups. Results: There was a statistically significant increase in walking speed, step cycle, step length, percent of the time on each foot and ambulation index in both groups post-treatment. The improvement in gait parameters post-treatment was significantly higher in the study group compared to the control. Conclusion: Rhythmic auditory stimulation combined with treadmill training is effective in improving selected gait kinematics in stroke patients when added to the selected physical therapy program.

Keywords: stroke, rhythmic auditory stimulation, treadmill training, gait kinematics

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Authors: El Hansali Hasnaa, Bennani Mohammed

Abstract:

Hexapod legged robot’s missions, particularly in irregular and dangerous areas, require high stability and high precision. In this paper, we consider the rectangular architecture body of legged robots with six legs distributed symmetrically along two sides, each leg contains three degrees of freedom for greater mobility. The aim of this work is planning tripod gait trajectory, based on the computing of the kinematic model to determine the joint variables in the lifting and the propelling phases. For this, appropriate coordinate frames are attached to the body and legs in order to obtain clear representation and efficient generation of the system equations. A simulation in MATLAB software platform is developed to confirm the kinematic model and various trajectories to the tripod gait adopted by the hexapod robot in its locomotion.

Keywords: hexapod legged robot, inverse kinematic model, simulation in MATLAB, tripod gait

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Authors: Mohamed A. Eid, Sobhy M. Aly

Abstract:

Background: About 75% of children with spastic hemiplegic cerebral palsy walk independently, but most still show abnormal gait patterns because of contractures across the joints and muscle spasticity. Objective: The purpose of this study was to investigate and compare the effects of extracorporeal shock wave therapy (ESWT) versus functional electrical stimulation (FES) on spasticity, function, and gait parameters in children with hemiplegic cerebral palsy (CP). Methods: A randomized controlled trail was conducted for 45 children with hemiplegic CP ranging in age from 6 to 9 years. They were assigned randomly using opaque envelopes into three groups. Physical Therapy (PT) group consisted of 15 children and received the conventional physical therapy program (CPTP) in addition to ankle foot orthosis (AFO). ESWT group consisted of 15 children and received the CPTP, AFO in addition to ESWT. FES group also consisted of 15 children and received the CPTP, AFO in addition to FES. All groups received the program of treatment 3 days/week for 12 weeks. Evaluation of spasticity by using the Modified Ashworth Scale (MAS), function by using the Pediatric Evaluation Disability Inventory (PEDI) and gait parameters by using the 3-D gait analysis was conducted at baseline and after 12 weeks of the treatment program. Results: Within groups, significant improvements in spasticity, function, and gait (P = 0.05) were observed in both ESWT and FES groups after treatment. While between groups, ESWT group showed significant improvements in all measured variables compared with FES and PT groups (P ˂ 0.05) after treatment. Conclusion: ESWT induced significant improvement than FES in decreasing spasticity and improving function and gait in children with hemiplegic CP. Therefore, ESWT should be included as an adjunctive therapy in the rehabilitation program of these children.

Keywords: cerebral palsy, extracorporeal shock wave therapy, functional electrical stimulation, function, gait, spasticity

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Authors: Aliza Lee, Mark Wilt, John Bonk, Scott Floyd, Bradley Hoffman, Karen Uchmanowicz

Abstract:

Bipartite medial cuneiforms are relatively rare but may play a significant role in biomechanical and gait abnormalities. It is believed that a bipartite medial cuneiform may alter the available range of motion due to its larger morphological variant, thus limiting the metatarsal plantarflexion needed to achieve adequate hallux dorsiflexion for normal gait. Radiographic and clinical assessments were performed on 2 patients who reported foot pain along the first ray. Both patients had visible bipartite medial cuneiforms on MRI. Using gait plate and Metascan™ analysis, both were noted to have four measurements far beyond the expected range. Medial and lateral heel peak pressure, hallux peak pressure, and 1st metatarsal peak pressure were all noted to be increased. These measurements are believed to be increased due to the hindrance placed on the available ROM of the 1st ray by the increased size of the medial cuneiform. A larger patient population would be needed to fully understand this developmental anomaly.

Keywords: bipartite medial cuneiforms, cuneiform, developmental anomaly, gait abnormality

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Authors: Radwa E. Sweif, Amira A. A. Abdallah

Abstract:

Background: Evaluation of gait efficiency is used to examine energy consumption especially in patients with movement disorders. Hypothesis/Purpose: This study compared the physiological and mechanical measures of gait efficiency between patients with ACL reconstruction (ACLR) and healthy controls and correlated among these measures. Methods: Seventeen patients with ACLR and sixteen healthy controls with mean ± SD age 23.06±4.76 vs 24.85±6.47 years, height 173.93±6.54 vs 175.64±7.37cm, and weight 74.25±12.1 vs 76.52±10.14 kg, respectively, participated in the study. The patients were operated on six months prior to testing. They should have completed their accelerated rehabilitation program during this period. A 3D motion analysis system was used for collecting the mechanical measures (Biomechanical Efficiency Quotient (BEQ), the maximum degree of knee internal rotation during stance phase and speed of walking). The physiological measures (Physiological Cost Index (PCI) and Rate of Perceived Exertion (RPE)) were collected after performing the 6- minute walking test. Results: MANOVA showed that the maximum degree of knee internal rotation, PCI, and RPE increased and the speed decreased significantly (p<0.05) in the patients compared with the controls with no significant difference for the BEQ. Finally, there were significant (p<0.05) positive correlations between each of the PCI & RPE and each of the BEQ, speed of walking and the maximum degree of knee internal rotation in each group. Conclusion: It was concluded that there are alterations in both mechanical and physiological measures of gait efficiency in patients with ACLR after being rehabilitated, clarifying the need for performing additional endurance as well as knee stability training programs. Moreover, the positive correlations indicate that using either of the mechanical or physiological measures for evaluating gait efficiency is acceptable.

Keywords: ACL reconstruction, mechanical, physiological, gait efficiency

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