Search results for: gait abnormalities

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: 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: 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: Noah Odion, Honest Jimu, Blessing Atinuke Afuape

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Introduction: Motor control and gait abnormalities are commonly observed in individuals with autism spectrum disorder (ASD), affecting their mobility and coordination. Understanding the underlying neurological and biomechanical factors is essential for designing effective interventions. This study focuses on developing microchip-integrated wearable devices to capture real-time movement data from individuals with autism. By applying computational models to the collected data, we aim to analyze motor control patterns and gait abnormalities, bridging a crucial knowledge gap in autism-related motor dysfunction. Methods: We designed microchip-enabled wearable devices capable of capturing precise kinematic data, including joint angles, acceleration, and velocity during movement. A cross-sectional study was conducted on individuals with ASD and a control group to collect comparative data. Computational modelling was applied using machine learning algorithms to analyse motor control patterns, focusing on gait variability, balance, and coordination. Finite element models were also used to simulate muscle and joint dynamics. The study employed descriptive and analytical methods to interpret the motor data. Results: The wearable devices effectively captured detailed movement data, revealing significant gait variability in the ASD group. For example, gait cycle time was 25% longer, and stride length was reduced by 15% compared to the control group. Motor control analysis showed a 30% reduction in balance stability in individuals with autism. Computational models successfully predicted movement irregularities and helped identify motor control deficits, particularly in the lower limbs. Conclusions: The integration of microchip-based wearable devices with computational models offers a powerful tool for diagnosing and treating motor control deficits in autism. These results have significant implications for patient care, providing objective data to guide personalized therapeutic interventions. The findings also contribute to the broader field of neuroscience by improving our understanding of the motor dysfunctions associated with ASD and other neurodevelopmental disorders.

Keywords: motor control, gait abnormalities, autism, wearable devices, microchips, computational modeling, kinematic analysis, neurodevelopmental disorders

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

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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: 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: 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: 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: Claudia Norambuena, Myissa Weiss, Maria Ruiz Maya, Matthew Straley, Elijah Hammond, Benjamin Chesebrough, David Grow

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The purpose of this project is to develop a low-cost, portable sensor device that can be used at home for long-term analysis of gait and balance abnormalities. One area of particular concern involves the asymmetries in movement and balance that can accompany certain types of injuries and/or the associated devices used in the repair and rehabilitation process (e.g. the use of splints and casts) which can often increase chances of falls and additional injuries. This device has the capacity to monitor a patient during the rehabilitation process after injury or operation, increasing the patient’s access to healthcare while decreasing the number of visits to the patient’s clinician. The sensor device may thereby improve the quality of the patient’s care, particularly in rural areas where access to the clinician could be limited, while simultaneously decreasing the overall cost associated with the patient’s care. The device consists of nine interconnected accelerometer/ gyroscope/compass chips (9-DOF IMU, Adafruit, New York, NY). The sensors attach to and are used to determine the orientation and acceleration of the patient’s lower abdomen, C7 vertebra (lower neck), L1 vertebra (middle back), anterior side of each thigh and tibia, and dorsal side of each foot. In addition, pressure sensors are embedded in shoe inserts with one sensor (ESS301, Tekscan, Boston, MA) beneath the heel and three sensors (Interlink 402, Interlink Electronics, Westlake Village, CA) beneath the metatarsal bones of each foot. These sensors measure the distribution of the weight applied to each foot as well as stride duration. A small microntroller (Arduino Mega, Arduino, Ivrea, Italy) is used to collect data from these sensors in a CSV file. MATLAB is then used to analyze the data and output the hip, knee, ankle, and trunk angles projected on the sagittal plane. An open-source program Processing is then used to generate an animation of the patient’s gait. The accuracy of the sensors was validated through comparison to goniometric measurements (±2° error). The sensor device was also shown to have sufficient sensitivity to observe various gait abnormalities. Several patients used the sensor device, and the data collected from each represented the patient’s movements. Further, the sensors were found to have the ability to observe gait abnormalities caused by the addition of a small amount of weight (4.5 - 9.1 kg) to one side of the patient. The user-friendly interface and portability of the sensor device will help to construct a bridge between patients and their clinicians with fewer necessary inpatient visits.

Keywords: biomedical sensing, gait analysis, outpatient, rehabilitation

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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: 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: Agata Matuszewska, Małgorzata Syczewska

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The movement of the upper limbs contributes significantly to balance control while walking in humans. However, the impact of different arm swing modes on gait stability is yet to be determined. This work intends to establish numerical parameters for assessing the arm swing. Nineteen people, comprising fifteen young, healthy individuals, two middle-aged individuals, and two individuals with dysfunctions, were analyzed using the movement analysis system. Proposed parameters such as ASᵢₐ (reflecting the arm swing amplitude) and Pearson’s correlation coefficient between the right and left upper limbs can be used to classify the type of movement task each participant performs. The results indicate that the ASᵢₐ parameter could potentially detect any abnormalities in upper limb functions, which may be due to musculoskeletal disorders or other malfunctions.

Keywords: arm swing, human balance, interlimb coordination, motion analysis system

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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: 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: 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: 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: 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: Mohamed Ahmed Fouad

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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: 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: El Hansali Hasnaa, Bennani Mohammed

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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: 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: Albert K. Chong, Jasim Ahmed Ali Al-Baghdadi, Peter B. Milburn

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Precise capture of plantar 3D surface of the foot at the loading gait phases on rigid substrate was found to be valuable for the assessment of the physiology, health and problems of the feet. Photogrammetry, a precision 3D spatial data capture technique is suitable for this type of dynamic application. In this research, the technique is utilised to study of the effect on the plantar deformation for having a strip of kinesiology tape on the plantar surface while going through the loading phase of gait. For this pilot study, one healthy adult male subject was recruited under the USQ University human research ethics guidelines for this preliminary study. The 3D plantar deformation data of both with and without applying the tape were analysed. The results and analyses are presented together with the detail of the findings.

Keywords: gait, human plantar, plantar loading, photogrammetry, kinesiology tape

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Authors: Seema Saini, Arsh Shikalgar, Neelam Tejani, Tushar J. Palekar

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This study introduces and evaluates a gait assessment system device as an educational model for healthcare students. The system aims to enhance learning through active experimentation with educators, focusing on teaching fundamental concepts like torque, potential energy, and kinetic movements. A total of 80 fourth-year healthcare students specializing in physiotherapy participated in this study. The study utilized a pre-post multiple-choice question (MCQ) examination format to evaluate the student's learning outcomes. Post-test performance significantly improved compared to pre-test scores (mean difference p<0.001, t=5.96). Participants reported that the gait assessment model effectively aided in achieving learning objectives, increasing topic understanding and interest, and enhancing comprehension of biomechanical events in gait.

Keywords: biomechanics, educational innovation, interactive learning, healthcare education

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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: 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: 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: Catarina Isabel Ramos Pereira, Jorge Machado, Begona Alonso Criado, Maria João Santos

Abstract:

Introduction: Gait disorders are one of the symptoms that have severe implications on the quality of life in Parkinson's disease (PD). Currently, there is no therapy to reverse or treat this condition. None of the drugs used in conventional medical treatment is entirely efficient, and all have a high incidence of side effects. Acupuncture treatment is believed to improve motor ability, but there is still little scientific evidence in individuals with PD. Aim: The aim of the study is to investigate the acute effect of acupuncture on gait parameters in Parkinson's disease. Methods: This is a randomized and controlled crossover study. The same individual patient was part of both the experimental (real acupuncture) and control group (false acupuncture/sham), and the sequence was randomized. Gait parameters were measured at two different moments, before and after treatment, using four force platforms as well as the collection of 3D markers positions taken by 11 cameras. Images were quantitatively analyzed using Qualisys Track Manager software that let us extract data related to the quality of gait and balance. Seven patients with the diagnosis of Parkinson's disease were included in the study. Results: Statistically significant differences were found in gait speed (p = 0.016), gait cadence (p = 0.006), support base width (p = 0.0001), medio-lateral oscillation (p = 0.017), left-right step length (p = 0.0002), and stride length: right-right (p = 0.0000) and left-left (p = 0.0018), time of left support phase (p = 0.029), right support phase (p = 0.025) and double support phase (p = 0.015), between the initial and final moments for the experimental group. Differences in right-left stride length were found for both groups. Conclusion: Our results show that acupuncture could enhance gait in Parkinson's disease patients. Deep research involving a larger number of volunteers should be accomplished to validate these encouraging findings.

Keywords: acupuncture, traditional Chinese medicine, Parkinson's disease, gait

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

Abstract:

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: Qazi Umer Jamil, Abubakr Siddique, Mubeen Ur Rehman, Nida Aziz, Mohsin I. Tiwana

Abstract:

This paper discusses a brain controlled robotic gait trainer for neurorehabilitation of Spinal Cord Injury (SCI) patients. Patients suffering from Spinal Cord Injuries (SCI) become unable to execute motion control of their lower proximities due to degeneration of spinal cord neurons. The presented approach can help SCI patients in neuro-rehabilitation training by directly translating patient motor imagery into walkers motion commands and thus bypassing spinal cord neurons completely. A non-invasive EEG based brain-computer interface is used for capturing patient neural activity. For signal processing and classification, an open source software (OpenVibe) is used. Classifiers categorize the patient motor imagery (MI) into a specific set of commands that are further translated into walker motion commands. The robotic walker also employs fall detection for ensuring safety of patient during gait training and can act as a support for SCI patients. The gait trainer is tested with subjects, and satisfactory results were achieved.

Keywords: brain computer interface (BCI), gait trainer, spinal cord injury (SCI), neurorehabilitation

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Authors: Sang-Hoon Park, Yeji Ho, Gwang-Moon Eom

Abstract:

Fast and accurate detection of Freezing of Gait (FOG) is desirable for appropriate application of cueing which has been shown to ameliorate FOG. Utilization of frequency spectrum of leg acceleration to derive the freeze index requires much calculation and it would lead to delayed cueing. We hypothesized that FOG can be reasonably detected from the time domain amplitude of foot acceleration. A time instant was recognized as FOG if the mean amplitude of the acceleration in the time window surrounding the time instant was in the specific FOG range. Parameters required in the FOG detection was optimized by simulated annealing. The suggested time domain methods showed performances comparable to those of frequency domain methods.

Keywords: freezing of gait, detection, Parkinson's disease, time-domain method

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