Displaying publications 1 - 20 of 101 in total

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  1. Sadiq MB, Ramanoon SZ, Mansor R, Syed-Hussain SS, Mossadeq WMS
    Trop Anim Health Prod, 2024 Jan 17;56(2):45.
    PMID: 38231431 DOI: 10.1007/s11250-024-03889-0
    Given the data paucity on dairy farmers' perspectives regarding bovine lameness and hoof diseases, particularly in South East Asian countries, this study was conducted to assess the knowledge, attitude and practices toward lameness and hoof health among dairy cattle farmers in Malaysia. An online-based and face-to-face survey was conducted among 114 dairy farmers from four states in Peninsular Malaysia. Data were analysed using descriptive statistics, principal component analysis and an independent sample t-test. Overall, farmers demonstrated satisfactory knowledge and attitude regarding lameness and its impact on dairy cattle welfare and production. Lameness was ranked the second most important health issue in dairy farms after mastitis. Notably, 90% reported the presence of at least one lame cow on their farms, and 55% stated lameness as the reason for culling their cows. While sole ulcer was the hoof lesion mostly identified by farmers, 75% of them underestimated lameness prevalence on their farms and rarely implemented management strategies such as preventive hoof trimming and footbath. Farmers' educational qualification influenced their understanding of the impact of lameness on dairy cattle production. Despite reflecting satisfactory knowledge and attitude towards lameness in dairy cows, farmers in this study need to improve their current management practices to address lameness problem in their herds. Educating farmers on the importance of early detection and prompt treatment, and preventive measures are crucial for lameness control and improving hoof health in these dairy farms.
    Matched MeSH terms: Gait
  2. Manaf H, Justine M, Ting GH, Latiff LA
    Top Stroke Rehabil, 2014 Mar-Apr;21(2):128-36.
    PMID: 24710973 DOI: 10.1310/tsr2102-128
    Little is known about the effects of attentional loading on performance of turning during walking in individuals with stroke.
    Matched MeSH terms: Gait*
  3. Ng H, Tan WH, Abdullah J, Tong HL
    ScientificWorldJournal, 2014;2014:376569.
    PMID: 25143972 DOI: 10.1155/2014/376569
    This paper describes the acquisition setup and development of a new gait database, MMUGait. This database consists of 82 subjects walking under normal condition and 19 subjects walking with 11 covariate factors, which were captured under two views. This paper also proposes a multiview model-based gait recognition system with joint detection approach that performs well under different walking trajectories and covariate factors, which include self-occluded or external occluded silhouettes. In the proposed system, the process begins by enhancing the human silhouette to remove the artifacts. Next, the width and height of the body are obtained. Subsequently, the joint angular trajectories are determined once the body joints are automatically detected. Lastly, crotch height and step-size of the walking subject are determined. The extracted features are smoothened by Gaussian filter to eliminate the effect of outliers. The extracted features are normalized with linear scaling, which is followed by feature selection prior to the classification process. The classification experiments carried out on MMUGait database were benchmarked against the SOTON Small DB from University of Southampton. Results showed correct classification rate above 90% for all the databases. The proposed approach is found to outperform other approaches on SOTON Small DB in most cases.
    Matched MeSH terms: Gait/physiology*
  4. Alam M, Choudhury IA, Bin Mamat A
    ScientificWorldJournal, 2014;2014:867869.
    PMID: 24892102 DOI: 10.1155/2014/867869
    Robotic technologies are being employed increasingly in the treatment of lower limb disabilities. Individuals suffering from stroke and other neurological disorders often experience inadequate dorsiflexion during swing phase of the gait cycle due to dorsiflexor muscle weakness. This type of pathological gait, mostly known as drop-foot gait, has two major complications, foot-slap during loading response and toe-drag during swing. Ankle foot orthotic (AFO) devices are mostly prescribed to resolve these complications. Existing AFOs are designed with or without articulated joint with various motion control elements like springs, dampers, four-bar mechanism, series elastic actuator, and so forth. This paper examines various AFO designs for drop-foot, discusses the mechanism, and identifies limitations and remaining design challenges. Along with two commercially available AFOs some designs possess promising prospective to be used as daily-wear device. However, the design and mechanism of AFO must ensure compactness, light weight, low noise, and high efficiency. These entailments present significant engineering challenges to develop a new design with wide consumer adoption.
    Matched MeSH terms: Gait Disorders, Neurologic/therapy*
  5. Ong SCL, Nur Azidawati AH, Liew YH, Anita S
    Med J Malaysia, 2017 10;72(5):311-313.
    PMID: 29197889 MyJurnal
    Acute necrotising encephalopathy of childhood (ANEC) is an uncommon disease with characteristic clinical and imaging findings. We present two cases of ANEC secondary to Respiratory Syncytial Virus (RSV) and mycoplasma infections. An eight-month-old boy presented with features of gastroenteritis but soon developed multiple episodes of seizures. Blood and CSF cultures were negative but nasopharyngeal aspirate immunofluorescence was positive for RSV. A nine-year-old girl presented with abnormal behaviour following two days of prodromal symptoms. Her serological markers implicated mycoplasma (IgM titre 1: 640). CT brain of both patients showed bilateral symmetrical thalamic hypodensities, while MRI revealed more extensive white matter involvements.
    Matched MeSH terms: Gait Disorders, Neurologic
  6. Zahari Z, Naga DNA, Bukry SA
    Med J Malaysia, 2024 Mar;79(Suppl 1):168-175.
    PMID: 38555902
    INTRODUCTION: Lower Cross Syndrome (LCS) is a prevalent condition that manifests as muscular tension due to the asymmetry in the strength of the lower extremity muscles. This imbalance could be due to the tautness of the iliopsoas, rectus femoris, tensor fascia latae, adductor group, gastrocnemius, and soleus muscles. LCS causes a postural imbalance in the individual, which triggers low back pain (LBP). When LCS is present alongside LBP, may cause the upper body to sway more in the transverse plane and at the lumbar level, making walking and termination of gait (GT) more difficult. However, the evidence of motor control and gait performance is scarce with inconclusive findings. Thus, this study aimed to review motor control on gait performance among individuals with lower crossed syndrome. This review is conducted to determine the motor control on gait performance in patients with LCS and how the conditions affect gait.

    MATERIALS AND METHODS: The databases Google Scholar, Science Direct, ResearchGate, PubMed, and Scopus were searched to identify potentially relevant documents. The keywords used for the search included "motor control" OR "motor learning" OR" core stability" AND "lower crossed syndrome" AND "gait". The search includes articles published between 1970 and 2022 and written in English. It is excluded when the paper is not a full-text article. After finding the articles, the information was extracted, including author, year of publication, country, objective, type of study, and motor control analysis summary.

    RESULTS: There were 107 articles retrieved from the search. but only seventeen articles were included for analysis. The finding demonstrates that LCS may associate with LBP and reduces the motor control of the core muscle stability which indirectly influences gait performance.

    CONCLUSIONS: This study suggests that individuals with LCS will have an alteration in their gait. However, there is still insufficient information on motor control in gait performance among lower crossed syndrome. Further research is needed to find what factors that may contribute to the adaptation of motor control in gait among LCS population.

    Matched MeSH terms: Gait/physiology
  7. Tajuddin K, Justine M, Mohd Mustafah N, Latif L, Manaf H
    Malays J Med Sci, 2021 Apr;28(2):63-71.
    PMID: 33958961 DOI: 10.21315/mjms2021.28.2.6
    Background: Stroke survivors depend on the unaffected leg during walking and standing. The presence of diabetic peripheral neuropathy (DPN) affecting both legs may further affect the postural balance and gait instability and increase the risk for falls in such patients. Thus, this study was conducted to investigate the effect of dual taskings on the gait and turning performance of stroke survivors with DPN.

    Methods: Forty stroke survivors were recruited (20 with DPN and 20 without DPN) in this cross-sectional study design. Instrumented timed up and go (iTUG) tests were conducted in three different tasking conditions (single task, dual motor and dual cognitive). APDM® Mobility Lab system was used to capture the gait parameters during the iTUG tests. A two-way mixed analysis of variance was used to determine the main effects of gait performance on three taskings during the iTUG test.

    Results: Spatiotemporal gait parameters and turning performance (turning time and turning step times) were more affected by the tasking conditions in stroke survivors with DPN compared to those without DPN (P < 0.05).

    Conclusion: Stroke survivors with DPN had difficulty walking while turning and performing a secondary task simultaneously.

    Matched MeSH terms: Gait; Gait Disorders, Neurologic
  8. Said Mogutham NN, Abdullah JM, Idris Z, Ghani ARI, Abdul Halim S, Naesarajoo JJJ, et al.
    Malays J Med Sci, 2020 Dec;27(6):89-101.
    PMID: 33447137 DOI: 10.21315/mjms2020.27.6.9
    Background: Dizziness is a common presenting complaint among patients in Malaysia. It is a vague term which could be associated with vertigo, imbalance, ataxia or syncope. In order to deal with this overwhelming complaint, a detailed history-taking is essential in confirming aetiology of disease and this should be followed by a meticulous clinical examination. The purpose of the video manuscript it to provide a step-by-step approach to a dizzy and swaying patient, specially catered for Malaysian medical students and trainees.

    Methods: A series of videos were shot, which involved the eye, ear, vestibular system, cerebellar, proprioceptive sense and gait examination. These videos, conducted in Universiti Sains Malaysia (USM) School of Medical Sciences, will be first in Malaysia and will highlight the proper technique and rapport with patients and essential points of each examination. There will be summary at the end of each examination on how to report findings which is a common weakness among students.

    Conclusion: We hope that students and junior doctors could be apply these methods in their daily assessment of dizzy patients and ultimately, reach an accurate diagnosis.

    Matched MeSH terms: Gait
  9. Kaewkaen K, Wongsamud P, Ngaothanyaphat J, Supawarapong P, Uthama S, Ruengsirarak W, et al.
    Malays J Med Sci, 2018 Feb;25(1):67-74.
    PMID: 29599636 DOI: 10.21315/mjms2018.25.1.8
    Background: The walking gait of older adults with balance impairment is affected by dual tasking. Several studies have shown that external cues can stimulate improvement in older adults' performance. There is, however, no current evidence to support the usefulness of external cues, such as audio-visual cueing, in dual task walking in older adults. Thus, the aim of this study was to investigate the influence of an audio-visual cue (simulated traffic light) on dual task walking in healthy older adults and in older adults with balance impairments.

    Methods: A two-way repeated measures study was conducted on 14 healthy older adults and 14 older adults with balance impairment, who were recruited from the community in Chiang Rai, Thailand. Their walking performance was assessed using a four-metre walking test at their preferred gait speed and while walking under two further gait conditions, in randomised order: dual task walking and dual task walking with a simulated traffic light. Each participant was tested individually, with the testing taking between 15 and 20 minutes to perform, including two-minute rest periods between walking conditions. Two Kinect cameras recorded the spatio-temporal parameters using MFU gait analysis software. Each participant was tested for each condition twice. The mean parameters for each condition were analysed using a two-way repeated measures analysis of variance (ANOVA) with participant group and gait condition as factors.

    Result: There was no significant between-group effect for walking speed, stride length and cadence. There were also no significant effects between gait condition and stride length or cadence. However, the effect between gait condition and walking speed was found to be significant [F(1.557, 40.485) = 4.568,P= 0.024, [Formula: see text]].

    Conclusion: An audio-visual cue (simulated traffic light) was found to influence walking speed in both healthy older adults and in older adults with balance impairment. The results suggest that audio-visual cues could be incorporated into healthy lifestyle promotion in older adults with balance impairment.

    Matched MeSH terms: Gait
  10. Fairus FZ, Joseph LH, Omar B, Ahmad J, Sulaiman R
    Malays J Med Sci, 2016 Mar;23(2):21-7.
    PMID: 27547111 MyJurnal
    The understanding of vertical ground reaction force (VGRF) during walking and half-squatting is necessary and commonly utilised during the rehabilitation period. The purpose of this study was to establish measurement reproducibility of VGRF that reports the minimal detectable changes (MDC) during walking and half-squatting activity among healthy male adults.
    Matched MeSH terms: Gait
  11. Tan KK, Easaw PE
    Singapore Med J, 1995 Jun;36(3):326-7.
    PMID: 8553105
    A 5-year-old Chinese boy presented with difficulty in walking and weakness of his lower limbs for one year, especially towards the evening. Bilateral equinovarus posturing of the feet and tremors of the upper limbs were noted on physical examination. Dopa-responsive dystonia was diagnosed after a remarkable symptomatic response to levodopa. This disorder is reported here to highlight an often misdiagnosed condition is children which is important because it is treatable. Dopa-responsive dystonia should be considered in the differential diagnosis of gait disturbance in children.
    Matched MeSH terms: Gait
  12. Sikandar T, Rabbi MF, Ghazali KH, Altwijri O, Alqahtani M, Almijalli M, et al.
    Sensors (Basel), 2021 Apr 17;21(8).
    PMID: 33920617 DOI: 10.3390/s21082836
    Human body measurement data related to walking can characterize functional movement and thereby become an important tool for health assessment. Single-camera-captured two-dimensional (2D) image sequences of marker-less walking individuals might be a simple approach for estimating human body measurement data which could be used in walking speed-related health assessment. Conventional body measurement data of 2D images are dependent on body-worn garments (used as segmental markers) and are susceptible to changes in the distance between the participant and camera in indoor and outdoor settings. In this study, we propose five ratio-based body measurement data that can be extracted from 2D images and can be used to classify three walking speeds (i.e., slow, normal, and fast) using a deep learning-based bidirectional long short-term memory classification model. The results showed that average classification accuracies of 88.08% and 79.18% could be achieved in indoor and outdoor environments, respectively. Additionally, the proposed ratio-based body measurement data are independent of body-worn garments and not susceptible to changes in the distance between the walking individual and camera. As a simple but efficient technique, the proposed walking speed classification has great potential to be employed in clinics and aged care homes.
    Matched MeSH terms: Gait
  13. Haque F, Reaz MBI, Chowdhury MEH, Ezeddin M, Kiranyaz S, Alhatou M, et al.
    Sensors (Basel), 2022 May 05;22(9).
    PMID: 35591196 DOI: 10.3390/s22093507
    Diabetic neuropathy (DN) is one of the prevalent forms of neuropathy that involves alterations in biomechanical changes in the human gait. Diabetic foot ulceration (DFU) is one of the pervasive types of complications that arise due to DN. In the literature, for the last 50 years, researchers have been trying to observe the biomechanical changes due to DN and DFU by studying muscle electromyography (EMG) and ground reaction forces (GRF). However, the literature is contradictory. In such a scenario, we propose using Machine learning techniques to identify DN and DFU patients by using EMG and GRF data. We collected a dataset from the literature which involves three patient groups: Control (n = 6), DN (n = 6), and previous history of DFU (n = 9) and collected three lower limb muscles EMG (tibialis anterior (TA), vastus lateralis (VL), gastrocnemius lateralis (GL)), and three GRF components (GRFx, GRFy, and GRFz). Raw EMG and GRF signals were preprocessed, and different feature extraction techniques were applied to extract the best features from the signals. The extracted feature list was ranked using four different feature ranking techniques, and highly correlated features were removed. In this study, we considered different combinations of muscles and GRF components to find the best performing feature list for the identification of DN and DFU. We trained eight different conventional ML models: Discriminant analysis classifier (DAC), Ensemble classification model (ECM), Kernel classification model (KCM), k-nearest neighbor model (KNN), Linear classification model (LCM), Naive Bayes classifier (NBC), Support vector machine classifier (SVM), and Binary decision classification tree (BDC), to find the best-performing algorithm and optimized that model. We trained the optimized the ML algorithm for different combinations of muscles and GRF component features, and the performance matrix was evaluated. Our study found the KNN algorithm performed well in identifying DN and DFU, and we optimized it before training. We found the best accuracy of 96.18% for EMG analysis using the top 22 features from the chi-square feature ranking technique for features from GL and VL muscles combined. In the GRF analysis, the model showed 98.68% accuracy using the top 7 features from the Feature selection using neighborhood component analysis for the feature combinations from the GRFx-GRFz signal. In conclusion, our study has shown a potential solution for ML application in DN and DFU patient identification using EMG and GRF parameters. With careful signal preprocessing with strategic feature extraction from the biomechanical parameters, optimization of the ML model can provide a potential solution in the diagnosis and stratification of DN and DFU patients from the EMG and GRF signals.
    Matched MeSH terms: Gait/physiology
  14. Hii CST, Gan KB, Zainal N, Mohamed Ibrahim N, Azmin S, Mat Desa SH, et al.
    Sensors (Basel), 2023 Jul 18;23(14).
    PMID: 37514783 DOI: 10.3390/s23146489
    Gait analysis is an essential tool for detecting biomechanical irregularities, designing personalized rehabilitation plans, and enhancing athletic performance. Currently, gait assessment depends on either visual observation, which lacks consistency between raters and requires clinical expertise, or instrumented evaluation, which is costly, invasive, time-consuming, and requires specialized equipment and trained personnel. Markerless gait analysis using 2D pose estimation techniques has emerged as a potential solution, but it still requires significant computational resources and human involvement, making it challenging to use. This research proposes an automated method for temporal gait analysis that employs the MediaPipe Pose, a low-computational-resource pose estimation model. The study validated this approach against the Vicon motion capture system to evaluate its reliability. The findings reveal that this approach demonstrates good (ICC(2,1) > 0.75) to excellent (ICC(2,1) > 0.90) agreement in all temporal gait parameters except for double support time (right leg switched to left leg) and swing time (right), which only exhibit a moderate (ICC(2,1) > 0.50) agreement. Additionally, this approach produces temporal gait parameters with low mean absolute error. It will be useful in monitoring changes in gait and evaluating the effectiveness of interventions such as rehabilitation or training programs in the community.
    Matched MeSH terms: Gait*
  15. Perera CK, Gopalai AA, Gouwanda D, Ahmad SA, Salim MSB
    Sci Rep, 2023 Oct 03;13(1):16640.
    PMID: 37789077 DOI: 10.1038/s41598-023-43148-0
    Forward continuation, balance, and sit-to-stand-and-walk (STSW) are three common movement strategies during sit-to-walk (STW) executions. Literature identifies these strategies through biomechanical parameters using gold standard laboratory equipment, which is expensive, bulky, and requires significant post-processing. STW strategy becomes apparent at gait-initiation (GI) and the hip/knee are primary contributors in STW, therefore, this study proposes to use the hip/knee joint angles at GI as an alternate method of strategy classification. To achieve this, K-means clustering was implemented using three clusters corresponding to the three STW strategies; and two feature sets corresponding to the hip/knee angles (derived from motion capture data); from an open access online database (age: 21-80 years; n = 10). The results identified forward continuation with the lowest hip/knee extension, followed by balance and then STSW, at GI. Using this classification, strategy biomechanics were investigated by deriving the established biomechanical quantities from literature. The biomechanical parameters that significantly varied between strategies (P 
    Matched MeSH terms: Gait
  16. Sikandar T, Rabbi MF, Ghazali KH, Altwijri O, Almijalli M, Ahamed NU
    Sci Rep, 2023 Sep 27;13(1):16177.
    PMID: 37758958 DOI: 10.1038/s41598-023-43428-9
    Gait data collection from overweight individuals walking on irregular surfaces is a challenging task that can be addressed using inertial measurement unit (IMU) sensors. However, it is unclear how many IMUs are needed, particularly when body attachment locations are not standardized. In this study, we analysed data collected from six body locations, including the torso, upper and lower limbs, to determine which locations exhibit significant variation across different real-world irregular surfaces. We then used deep learning method to verify whether the IMU data recorded from the identified body locations could classify walk patterns across the surfaces. Our results revealed two combinations of body locations, including the thigh and shank (i.e., the left and right shank, and the right thigh and right shank), from which IMU data should be collected to accurately classify walking patterns over real-world irregular surfaces (with classification accuracies of 97.24 and 95.87%, respectively). Our findings suggest that the identified numbers and locations of IMUs could potentially reduce the amount of data recorded and processed to develop a fall prevention system for overweight individuals.
    Matched MeSH terms: Gait
  17. Cuk A, Bezdan T, Jovanovic L, Antonijevic M, Stankovic M, Simic V, et al.
    Sci Rep, 2024 Feb 21;14(1):4309.
    PMID: 38383690 DOI: 10.1038/s41598-024-54680-y
    Parkinson's disease (PD) is a progressively debilitating neurodegenerative disorder that primarily affects the dopaminergic system in the basal ganglia, impacting millions of individuals globally. The clinical manifestations of the disease include resting tremors, muscle rigidity, bradykinesia, and postural instability. Diagnosis relies mainly on clinical evaluation, lacking reliable diagnostic tests and being inherently imprecise and subjective. Early detection of PD is crucial for initiating treatments that, while unable to cure the chronic condition, can enhance the life quality of patients and alleviate symptoms. This study explores the potential of utilizing long-short term memory neural networks (LSTM) with attention mechanisms to detect Parkinson's disease based on dual-task walking test data. Given that the performance of networks is significantly inductance by architecture and training parameter choices, a modified version of the recently introduced crayfish optimization algorithm (COA) is proposed, specifically tailored to the requirements of this investigation. The proposed optimizer is assessed on a publicly accessible real-world clinical gait in Parkinson's disease dataset, and the results demonstrate its promise, achieving an accuracy of 87.4187 % for the best-constructed models.
    Matched MeSH terms: Gait
  18. Kim SH, Kim DW
    Sains Malaysiana, 2015;44:1745-1750.
    A fracture, which mostly results from a fall, is fatal for the elderly. A fall occurred when a person cannot maintain the
    body position. Most falls occurred when a person walks on a slippery surface or trips over an object on the ground during
    a gait. Most people try to avoid falls instinctively and fall when their attempt fails. As such, this study investigated the
    difference between two movements- a movement to avoid falls and a forward-falling movement without a fall-avoiding
    movement- by analyzing the body movements of the subjects. A fast-moving fall-guiding device with a pneumatic actuator
    was used to guide falls. The movement of the device could simulate a foot slip that may happen during daily activities.
    A three-axis acceleration sensor and a Bluetooth module were used to avoid disturbing the body movement during a fall
    as a wire sensor or a movement analysis system does.
    Matched MeSH terms: Gait
  19. Hasan CZC, Jailani R, Md Tahir N, Ilias S
    Res Dev Disabil, 2017 Jul;66:55-63.
    PMID: 28284567 DOI: 10.1016/j.ridd.2017.02.015
    Minimal information is known about the three-dimensional (3D) ground reaction forces (GRF) on the gait patterns of individuals with autism spectrum disorders (ASD). The purpose of this study was to investigate whether the 3D GRF components differ significantly between children with ASD and the peer controls. 15 children with ASD and 25 typically developing (TD) children had participated in the study. Two force plates were used to measure the 3D GRF data during walking. Time-series parameterization techniques were employed to extract 17 discrete features from the 3D GRF waveforms. By using independent t-test and Mann-Whitney U test, significant differences (p<0.05) between the ASD and TD groups were found for four GRF features. Children with ASD demonstrated higher maximum braking force, lower relative time to maximum braking force, and lower relative time to zero force during mid-stance. Children with ASD were also found to have reduced the second peak of vertical GRF in the terminal stance. These major findings suggest that children with ASD experience significant difficulties in supporting their body weight and endure gait instability during the stance phase. The findings of this research are useful to both clinicians and parents who wish to provide these children with appropriate treatments and rehabilitation programs.
    Matched MeSH terms: Gait*
  20. Abdul Rahman RA, Rafi F, Hanapiah FA, Nikmat AW, Ismail NA, Manaf H
    Rehabil Res Pract, 2018;2018:2071726.
    PMID: 30402290 DOI: 10.1155/2018/2071726
    Background: Tasks requiring simultaneous mobility and cognition (dual tasks) have been associated with incidence of falls. Although these deficits have been documented in individuals with neurologic disorder, the effect of dual task in children with traumatic brain injury has not been fully explored.

    Objective: To investigate the effect of dual-task (dual-motor and dual-cognitive task) conditions on spatiotemporal gait parameters during timed up and go test in children with traumatic brain injury.

    Methods and Material: A total of 14 children with traumatic brain injury and 21 typically developing children participated in this case-control study. Functional balance was assessed before the actual testing to predict the risk of falls. Timed up and go test was performed under single-task and dual-task (dual-motor and dual-cognitive task) conditions. Spatiotemporal gait parameters were determined using the APDM Mobility Lab system. The descriptive statistics and t-test were used to analyze demographic characteristics and repeated measure ANOVA test was used to analyze the gait parameters.

    Results: Under dual-task (dual-motor and dual-cognitive task) conditions during the timed up and go test, gait performance significantly deteriorated. Furthermore, the total time to complete the timed up and go test, stride velocity, cadence, and step time during turning were significantly different between children with traumatic brain injury and typically developing children.

    Conclusions: These findings suggest that gait parameters were compromised under dual-task conditions in children with traumatic brain injury. Dual-task conditions may become a component of gait training to ensure a complete and comprehensive rehabilitation program.

    Matched MeSH terms: Gait
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