Purpose: This study verified the effects of transcutaneous electrical nerve stimulation (TENS), which can be worn during walking and exercise, in elderly individuals with late-stage knee pain who exercise regularly. M...Purpose: This study verified the effects of transcutaneous electrical nerve stimulation (TENS), which can be worn during walking and exercise, in elderly individuals with late-stage knee pain who exercise regularly. Methods: Thirty-two late-stage elderly individuals were evaluated for knee pain during rest, walking, and program exercises, with and without TENS. Gait analysis was performed using an IoT-based gait analysis device to examine the effects of TENS-induced analgesia on gait. Results: TENS significantly reduced knee pain during rest, walking, and programmed exercises, with the greatest analgesic effect observed during walking. The greater the knee pain without TENS, the more significant the analgesic effect of TENS. A comparison of gait parameters revealed a significant difference only in the gait cycle time, with a trend towards faster walking with TENS;however, the effect was limited. Conclusion: TENS effectively relieves knee pain in late-stage elderly individuals and can be safely applied during exercise. Pain management using TENS provides important insights into the implementation of exercise therapy in this age group.展开更多
Objective:To analyze the effects of repetitive transcranial magnetic stimulation combined with motor control training on the treatment of stroke-induced hemiplegia,specifically focusing on the impact on patients’bala...Objective:To analyze the effects of repetitive transcranial magnetic stimulation combined with motor control training on the treatment of stroke-induced hemiplegia,specifically focusing on the impact on patients’balance function and gait.Methods:Fifty-two cases of hemiplegic stroke patients were randomly divided into two groups,26 in the control group and 26 in the observation group,using computer-generated random grouping.All participants underwent conventional treatment and rehabilitation training.In addition to these,the control group received repetitive transcranial magnetic pseudo-stimulation therapy+motor control training,while the observation group received repetitive transcranial magnetic stimulation therapy+motor control training.The balance function and gait parameters of both groups were compared before and after the interventions and assessed the satisfaction of the interventions in both groups.Results:Before the invention,there were no significant differences in balance function scores and each gait parameter between the two groups(P>0.05).However,after the intervention,the observation group showed higher balance function scores compared to the control group(P<0.05).The observation group also exhibited higher step speed and step frequency,longer step length,and a higher overall satisfaction level with the intervention compared to the control group(P<0.05).Conclusion:The combination of repetitive transcranial magnetic stimulation and motor control training in the treatment of stroke-induced hemiplegia has demonstrated positive effects.It not only improves the patient’s balance function and gait but also contributes to overall physical rehabilitation.展开更多
Human Activity Recognition(HAR)has always been a difficult task to tackle.It is mainly used in security surveillance,human-computer interaction,and health care as an assistive or diagnostic technology in combination w...Human Activity Recognition(HAR)has always been a difficult task to tackle.It is mainly used in security surveillance,human-computer interaction,and health care as an assistive or diagnostic technology in combination with other technologies such as the Internet of Things(IoT).Human Activity Recognition data can be recorded with the help of sensors,images,or smartphones.Recognizing daily routine-based human activities such as walking,standing,sitting,etc.,could be a difficult statistical task to classify into categories and hence 2-dimensional Convolutional Neural Network(2D CNN)MODEL,Long Short Term Memory(LSTM)Model,Bidirectional long short-term memory(Bi-LSTM)are used for the classification.It has been demonstrated that recognizing the daily routine-based on human activities can be extremely accurate,with almost all activities accurately getting recognized over 90%of the time.Furthermore,because all the examples are generated from only 20 s of data,these actions can be recognised fast.Apart from classification,the work extended to verify and investigate the need for wearable sensing devices in individually walking patients with Cerebral Palsy(CP)for the evaluation of chosen Spatio-temporal features based on 3D foot trajectory.Case-control research was conducted with 35 persons with CP ranging in weight from 25 to 65 kg.Optical Motion Capture(OMC)equipment was used as the referral method to assess the functionality and quality of the foot-worn device.The average accuracy±precision for stride length,cadence,and step length was 3.5±4.3,4.1±3.8,and 0.6±2.7 cm respectively.For cadence,stride length,swing,and step length,people with CP had considerably high inter-stride variables.Foot-worn sensing devices made it easier to examine Gait Spatio-temporal data even without a laboratory set up with high accuracy and precision about gait abnormalities in people who have CP during linear walking.展开更多
Subject identification via the subject’s gait is challenging due to variations in the subject’s carrying and dressing conditions in real-life scenes.This paper proposes a novel targeted 3-dimensional(3D)gait model(3...Subject identification via the subject’s gait is challenging due to variations in the subject’s carrying and dressing conditions in real-life scenes.This paper proposes a novel targeted 3-dimensional(3D)gait model(3DGait)represented by a set of interpretable 3DGait descriptors based on a 3D parametric body model.The 3DGait descriptors are utilised as invariant gait features in the 3DGait recognition method to address object carrying and dressing.The 3DGait recognitionmethod involves 2-dimensional(2D)to 3DGaitdata learningbasedon3Dvirtual samples,a semantic gait parameter estimation Long Short Time Memory(LSTM)network(3D-SGPE-LSTM),a feature fusion deep model based on a multi-set canonical correlation analysis,and SoftMax recognition network.First,a sensory experiment based on 3D body shape and pose deformation with 3D virtual dressing is used to fit 3DGait onto the given 2D gait images.3Dinterpretable semantic parameters control the 3D morphing and dressing involved.Similarity degree measurement determines the semantic descriptors of 2D gait images of subjects with various shapes,poses and styles.Second,using the 2D gait images as input and the subjects’corresponding 3D semantic descriptors as output,an end-to-end 3D-SGPE-LSTM is constructed and trained.Third,body shape,pose and external gait factors(3D-eFactors)are estimated using the 3D-SGPE-LSTM model to create a set of interpretable gait descriptors to represent the 3DGait Model,i.e.,3D intrinsic semantic shape descriptor(3DShape);3D skeleton-based gait pose descriptor(3D-Pose)and 3D dressing with other 3D-eFators.Finally,the 3D-Shape and 3D-Pose descriptors are coupled to a unified pattern space by learning prior knowledge from the 3D-eFators.Practical research on CASIA B,CMU MoBo,TUM GAID and GPJATK databases shows that 3DGait is robust against object carrying and dressing variations,especially under multi-cross variations.展开更多
BACKGROUND The results of existing lower extremity robotics studies are conflicting,and few relevant clinical trials have examined short-term efficacy.In addition,most of the outcome indicators in existing studies are...BACKGROUND The results of existing lower extremity robotics studies are conflicting,and few relevant clinical trials have examined short-term efficacy.In addition,most of the outcome indicators in existing studies are scales,which are not objective enough.We used the combination of objective instrument measurement and scale to explore the short-term efficacy of the lower limb A3 robot,to provide a clinical reference.AIM To investigate the improvement of lower limb walking ability and balance in stroke treated by A3 lower limb robot.METHODS Sixty stroke patients were recruited prospectively in a hospital and randomized into the A3 group and the control group.They received 30 min of A3 robotics training and 30 min of floor walking training in addition to 30 min of regular rehabilitation training.The training was performed five times a week,once a day,for 2 wk.The t-test or non-parametric test was used to compare the threedimensional gait parameters and balance between the two groups before and after treatment.RESULTS The scores of basic activities of daily living,Stroke-Specific Quality of Life Scale,FM balance meter,Fugl-Meyer Assessment scores,Rivermead Mobility Index,Stride speed,Stride length,and Time Up and Go test in the two groups were significantly better than before treatment(19.29±12.15 vs 3.52±4.34;22.57±17.99 vs 4.07±2.51;1.21±0.83 vs 0.18±0.40;3.50±3.80 vs 0.96±2.08;2.07±1.21 vs 0.41±0.57;0.89±0.63 vs 0.11±0.32;12.38±9.00 vs 2.80±3.43;18.84±11.24 vs 3.80±10.83;45.12±69.41 vs 8.41±10.20;29.45±16.62 vs 8.68±10.74;P<0.05).All outcome indicators were significantly better in the A3 group than in the control group,except the area of the balance parameter.CONCLUSION For the short-term treatment of patients with subacute stroke,the addition of A3 robotic walking training to conventional physiotherapy appears to be more effective than the addition of ground-based walking training.展开更多
To address the problem of frequent battery replacement for wearable sensors applied to fall detection among the elderly,a portable and lowcost triboelectric nanogenerator(TENG)-based self-powered sensor for human gait...To address the problem of frequent battery replacement for wearable sensors applied to fall detection among the elderly,a portable and lowcost triboelectric nanogenerator(TENG)-based self-powered sensor for human gait monitoring is proposed.The main fabrication materials of the TENG are polytetrafluoroethylene(PTFE)film,aluminum(Al)foil,and polyimide(PI)film,where PTFE and Al are the friction layer materials and the PI film is used to improve the output performance.Exploiting the ability of TENGs to monitor changes in environmental conditions,a self-powered sensor based on the TENG is placed in an insole to collect gait information.Since a TENG does not require a power source to convert physical and mechanical signals into electrical signals,the electrical signals can be used as sensing signals to be analyzed by a computer to recognize daily human activities and fall status.Experimental results show that the accuracy of the TENG-based sensor for recognizing human gait is 97.2%,demonstrating superior sensing performance and providing valuable insights for future monitoring of fall events in the elderly population.展开更多
The current gait planning for legged robots is mostly based on human presets,which cannot match the flexible characteristics of natural mammals.This paper proposes a gait optimization framework for hexapod robots call...The current gait planning for legged robots is mostly based on human presets,which cannot match the flexible characteristics of natural mammals.This paper proposes a gait optimization framework for hexapod robots called Smart Gait.Smart Gait contains three modules:swing leg trajectory optimization,gait period&duty optimization,and gait sequence optimization.The full dynamics of a single leg,and the centroid dynamics of the overall robot are considered in the respective modules.The Smart Gait not only helps the robot to decrease the energy consumption when in locomotion,mostly,it enables the hexapod robot to determine its gait pattern transitions based on its current state,instead of repeating the formalistic clock-set step cycles.Our Smart Gait framework allows the hexapod robot to behave nimbly as a living animal when in 3D movements for the first time.The Smart Gait framework combines offline and online optimizations without any fussy data-driven training procedures,and it can run efficiently on board in real-time after deployment.Various experiments are carried out on the hexapod robot LittleStrong.The results show that the energy consumption is reduced by 15.9%when in locomotion.Adaptive gait patterns can be generated spontaneously both in regular and challenge environments,and when facing external interferences.展开更多
The demand for a non-contact biometric approach for candidate identification has grown over the past ten years.Based on the most important biometric application,human gait analysis is a significant research topic in c...The demand for a non-contact biometric approach for candidate identification has grown over the past ten years.Based on the most important biometric application,human gait analysis is a significant research topic in computer vision.Researchers have paid a lot of attention to gait recognition,specifically the identification of people based on their walking patterns,due to its potential to correctly identify people far away.Gait recognition systems have been used in a variety of applications,including security,medical examinations,identity management,and access control.These systems require a complex combination of technical,operational,and definitional considerations.The employment of gait recognition techniques and technologies has produced a number of beneficial and well-liked applications.Thiswork proposes a novel deep learning-based framework for human gait classification in video sequences.This framework’smain challenge is improving the accuracy of accuracy gait classification under varying conditions,such as carrying a bag and changing clothes.The proposed method’s first step is selecting two pre-trained deep learningmodels and training fromscratch using deep transfer learning.Next,deepmodels have been trained using static hyperparameters;however,the learning rate is calculated using the particle swarmoptimization(PSO)algorithm.Then,the best features are selected from both trained models using the Harris Hawks controlled Sine-Cosine optimization algorithm.This algorithm chooses the best features,combined in a novel correlation-based fusion technique.Finally,the fused best features are categorized using medium,bi-layer,and tri-layered neural networks.On the publicly accessible dataset known as the CASIA-B dataset,the experimental process of the suggested technique was carried out,and an improved accuracy of 94.14% was achieved.The achieved accuracy of the proposed method is improved by the recent state-of-the-art techniques that show the significance of this work.展开更多
Three-dimensional(3D)printing technology has been widely used to create artificial rock samples in rock mechanics.While 3D printing can create complex fractures,the material still lacks sufficient similarity to natura...Three-dimensional(3D)printing technology has been widely used to create artificial rock samples in rock mechanics.While 3D printing can create complex fractures,the material still lacks sufficient similarity to natural rock.Extrusion free forming(EFF)is a 3D printing technique that uses clay as the printing material and cures the specimens through high-temperature sintering.In this study,we attempted to use the EFF technology to fabricate artificial rock specimens.The results show the physico-mechanical properties of the specimens are significantly affected by the sintering temperature,while the nozzle diameter and layer thickness also have a certain impact.The specimens are primarily composed of SiO_(2),with mineral compositions similar to that of natural rocks.The density,uniaxial compressive strength(UCS),elastic modulus,and tensile strength of the printed specimens fall in the range of 1.65–2.54 g/cm3,16.46–50.49 MPa,2.17–13.35 GPa,and 0.82–17.18 MPa,respectively.It is capable of simulating different types of rocks,especially mudstone,sandstone,limestone,and gneiss.However,the simulation of hard rocks with UCS exceeding 50 MPa still requires validation.展开更多
Personalized gait curves are generated to enhance patient adaptability to gait trajectories used for passive training in the early stage of rehabilitation for hemiplegic patients.The article utilizes the random forest...Personalized gait curves are generated to enhance patient adaptability to gait trajectories used for passive training in the early stage of rehabilitation for hemiplegic patients.The article utilizes the random forest algorithm to construct a gait parameter model,which maps the relationship between parameters such as height,weight,age,gender,and gait speed,achieving prediction of key points on the gait curve.To enhance prediction accuracy,an attention mechanism is introduced into the algorithm to focus more on the main features.Meanwhile,to ensure high similarity between the reconstructed gait curve and the normal one,probabilistic motion primitives(ProMP)are used to learn the probability distribution of normal gait data and construct a gait trajectorymodel.Finally,using the specified step speed as input,select a reference gait trajectory from the learned trajectory,and reconstruct the curve of the reference trajectoryusing the gait keypoints predictedby the parametermodel toobtain the final curve.Simulation results demonstrate that the method proposed in this paper achieves 98%and 96%curve correlations when generating personalized lower limb gait curves for different patients,respectively,indicating its suitability for such tasks.展开更多
Objective: To explore gait kinematics analysis and evaluate the surgical efficacy of total knee arthroplasty (TKA), as well as its guiding significance for postoperative rehabilitation. Method: Fifty patients admitted...Objective: To explore gait kinematics analysis and evaluate the surgical efficacy of total knee arthroplasty (TKA), as well as its guiding significance for postoperative rehabilitation. Method: Fifty patients admitted to TKA treatment for knee osteoarthritis from December 2022 to July 2023 were included, which were divided into an intervention group (gait kinematics analysis group, n = 25) and a control group (conventional rehabilitation program group, n = 25). All patients underwent HSS score and KSS score before surgery (T0), 1 month after surgery (T1), 3 months after surgery (T2), and 6 months after surgery (T3). The intervention group underwent gait kinematics analysis at 1 month after surgery (T1) and 3 months after surgery (T2). Two groups measured the hip knee ankle angle (HKA), distal femoral lateral angle (LDFA), and proximal tibial medial angle (MPTA) on knee joint radiographs before and after surgery. Results: There was no significant difference in general information, preoperative imaging parameters, and functional scores between the two groups of patients. There was no significant difference in functional scores and postoperative prosthesis alignment between the two groups of patients in the first month after surgery. The intervention group showed a significant decrease in gait kinematic scores in the first month, with hip joint scores being particularly prominent (P 0.05). Conclusion: Gait kinematic analysis is helpful in evaluating the postoperative efficacy of TKA and can guide early and rapid recovery after TKA.展开更多
Purpose: This study focused on maintaining and improving the walking function of late-stage older individuals while longitudinally tracking the effects of regular exercise programs in a day-care service specialized fo...Purpose: This study focused on maintaining and improving the walking function of late-stage older individuals while longitudinally tracking the effects of regular exercise programs in a day-care service specialized for preventive care over 5 years, using detailed gait function measurements with an accelerometer-based system. Methods: Seventy individuals (17 male and 53 female) of a daycare service in Tokyo participated in a weekly exercise program, meeting 1 - 2 times. The average age of the participants at the start of the program was 81.4 years. Gait function, including gait speed, stride length, root mean square (RMS) of acceleration, gait cycle time and its standard deviation, and left-right difference in stance time, was evaluated every 6 months. Results: Gait speed and stride length improved considerably within six months of starting the exercise program, confirming an initial improvement in gait function. This suggests that regular exercise programs can maintain or improve gait function even age groups that predictably have a gradual decline in gait ability due to enhanced age. In the long term, many indicators tended to approach baseline values. However, the exercise program seemingly counteracts age-related changes in gait function and maintains a certain level of function. Conclusions: While a decline in gait ability with aging is inevitable, establishing appropriate exercise habits in late-stage older individuals may contribute to long-term maintenance of gait function.展开更多
Understanding the neural underpinning of human gait and balance is one of the most pertinent challenges for 21st-century translational neuroscience due to the profound impact that falls and mobility disturbances have ...Understanding the neural underpinning of human gait and balance is one of the most pertinent challenges for 21st-century translational neuroscience due to the profound impact that falls and mobility disturbances have on our aging population.Posture and gait control does not happen automatically,as previously believed,but rather requires continuous involvement of central nervous mechanisms.To effectively exert control over the body,the brain must integrate multiple streams of sensory information,including visual,vestibular,and somatosensory signals.The mechanisms which underpin the integration of these multisensory signals are the principal topic of the present work.Existing multisensory integration theories focus on how failure of cognitive processes thought to be involved in multisensory integration leads to falls in older adults.Insufficient emphasis,however,has been placed on specific contributions of individual sensory modalities to multisensory integration processes and cross-modal interactions that occur between the sensory modalities in relation to gait and balance.In the present work,we review the contributions of somatosensory,visual,and vestibular modalities,along with their multisensory intersections to gait and balance in older adults and patients with Parkinson’s disease.We also review evidence of vestibular contributions to multisensory temporal binding windows,previously shown to be highly pertinent to fall risk in older adults.Lastly,we relate multisensory vestibular mechanisms to potential neural substrates,both at the level of neurobiology(concerning positron emission tomography imaging)and at the level of electrophysiology(concerning electroencephalography).We hope that this integrative review,drawing influence across multiple subdisciplines of neuroscience,paves the way for novel research directions and therapeutic neuromodulatory approaches,to improve the lives of older adults and patients with neurodegenerative diseases.展开更多
Individuals with NGLY1 Deficiency, an inherited autosomal recessive disorder, exhibit hyperkinetic movements including athetoid, myoclonic, dysmetric, and dystonic movements impacting both upper and lower limb motion....Individuals with NGLY1 Deficiency, an inherited autosomal recessive disorder, exhibit hyperkinetic movements including athetoid, myoclonic, dysmetric, and dystonic movements impacting both upper and lower limb motion. This report provides the first set of laboratory-based measures characterizing the gait patterns of two individuals with NGLY1 Deficiency, using both linear and non-linear measures, during treadmill walking, and compares them to neurotypical controls. Lower limb kinematics were obtained with a camera-based motion analysis system and bilateral time normalized lower limb joint time series waveforms were developed. Linear measures of joint range of motion, stride times and peak angular velocity were obtained, and confidence intervals were used to determine if there were differences between the patients and control. Correlations between participant and control mean joint waveforms were calculated and used to evaluate the similarities between patients and controls. Non-linear measures included: joint angle-angle diagrams, phase-portrait areas, and continuous relative phase (CRP) measures. These measures were used to assess joint coordination and control features of the lower limb motion. Participants displayed high correlations with their control counterparts for the hip and knee joint waveforms, but joint motion was restricted. Peak angular velocities were also significantly less than those of the controls. Both angle-angle and phase-portrait areas were less than the controls although the general shapes of those diagrams were similar to those of the controls. The NGLY1 Deficient participants’ CRP measures displayed disrupted coordination patterns with the knee-ankle patterns displaying more disruption than the hip-knee measures. Overall, the participants displayed a functional walking pattern that differed in many quantitative ways from those of the neurotypical controls. Using both linear and non-linear measures to characterize gait provides a more comprehensive and nuanced characterization of NGLY1 gait and can be used to develop interventions targeted toward specific aspects of disordered gait.展开更多
Background: Although Tai Ji Quan has been shown to relieve pain and improve functional mobility in people with knee osteoarthritis(OA), little is known about its potential benefits on gait characteristics among older ...Background: Although Tai Ji Quan has been shown to relieve pain and improve functional mobility in people with knee osteoarthritis(OA), little is known about its potential benefits on gait characteristics among older Chinese women who have a high prevalence of both radiographic and symptomatic knee OA. This study aims to assess the efficacy of a tailored Tai Ji Quan intervention on gait kinematics for older Chinese women with knee OA.Methods: A randomized controlled trial involving 46 older women in Shanghai, China, with clinically diagnosed knee OA. Randomized(1:1)participants received either a 60 min Tai Ji Quan session(n = 23) 3 times weekly or a 60 min bi-weekly educational session(n = 23) for 24 weeks.Primary outcomes were changes in gait kinematic measures from baseline to 24 weeks. Secondary outcomes included changes in scores on the Western Ontario and Mc Master University Osteoarthritis Index(WOMAC) and Short Physical Performance Battery(SPPB).Results: After 24 weeks the Tai Ji Quan group demonstrated better performance in gait velocity(mean difference, 8.40 cm/s, p = 0.01), step length(mean difference, 3.52 cm, p = 0.004), initial contact angle(mean difference, 2.19°, p = 0.01), and maximal angle(mean difference, 2.61°,p = 0.003) of flexed knees during stance phase compared to the control group. In addition, the Tai Ji Quan group showed significant improvement in WOMAC scores(p < 0.01)(mean difference,-4.22 points in pain, p = 0.002;-2.41 points in stiffness, p < 0.001;-11.04 points in physical function, p = 0.006) and SPPB scores(mean difference, 1.22 points, p < 0.001).Conclusion: Among older Chinese women with knee OA, a tailored Tai Ji Quan intervention improved gait outcomes. The intervention also improved overall function as indexed by the WOMAC and SPPB. These results support the use of Tai Ji Quan for older Chinese adults with knee OA to both improve their functional mobility and reduce pain symptomatology.展开更多
Quadruped robots consume a lot of energy, which is one of the factors restricting their application. Energy efficiency is one of the key evaluating indicators for walking robots. The relationship between energy and el...Quadruped robots consume a lot of energy, which is one of the factors restricting their application. Energy efficiency is one of the key evaluating indicators for walking robots. The relationship between energy and elastic elements of walking robots have been studied, but different walking gait patterns and contact status have important influences on locomotion energy efficiency, and the energy efficiency considering the foot-end trajectory has not been reported. Therefore, the energy consumption and energy efficiency of quadruped robot with trot gait and combined cycloid foot trajectory are studied. The forward and inverse kinematics of quadruped robot is derived. The combined cycloid function is proposed to generate horizontal and vertical foot trajectory respectively, which can ensure the acceleration curve of the foot-end smoother and more successive, and reduce the contact force between feet and environment. Because of the variable topology mechanism characteristic of quadruped robot, the leg state is divided into three different phases which are swing phase, transition phase and stance phase during one trot gait cycle. The non-continuous variable constraint between feet and environment of quadruped robot is studied. The dynamic model of quadruped robot is derived considering the variable topology mechanism characteristic, the periodic contact and elastic elements of the robot. The total energy consumption of walking robot during one gait cycle is analyzed based on the dynamic model. The specific resistance is used to evaluate energy efficiency of quadruped robot. The calculation results show the relationships between specific resistance and gait parameters, which can be used to determine the reasonable gait parameters.展开更多
BACKGROUND De-afferentation or non-weight bearing induces rapid cortical and spinalα-motor neuron excitability.Author supposed that an end-effector type gait robot(EEGR)could provide patients with a training conditio...BACKGROUND De-afferentation or non-weight bearing induces rapid cortical and spinalα-motor neuron excitability.Author supposed that an end-effector type gait robot(EEGR)could provide patients with a training condition that was specific enough to activate rapid cortical/spinal neuroplasticity,leading to immediate muscle strengthening.The electromyographic and biomechanical comparisons were conducted.AIM To compare the electromyographic activities of the thigh and shank muscles and isometric peak torque(PT)before and after walking training on a floor or in the end-effector gait robot.METHODS Twelve outpatients without ambulatory dysfunction were recruited.Order of two interventions(5-min training on a floor at a comfortable pace or training in an EEGR with non-weight bearing on their feet and 100%guidance force at 2.1 km/h)were randomly chosen.Isometric PT,maximal ratio of torque development,amplitude of compound motor action potential(CMAP),and area under the curve(AUC)were evaluated before and 10 min after both interventions.RESULTS The degree of PT improvement of the dominant knee flexors was larger in the EEGR than on the floor(9.6±22.4 Nm/BW,P<0.01).The EEGR-trained patients had greater PT improvement of the dominant knee extensors than those who trained on the floor(4.5±28.1 Nm/BW,P<0.01).However,all electromyographic activities of the thigh and shank muscles(peak CMAP,mean and peak AUC)were significantly lower for the use of the EEGR than walking on the floor.CONCLUSION Immediate strengthening of the knee flexors and extensors was induced after the 5-min EEGR training,despite reduced muscular use.展开更多
文摘Purpose: This study verified the effects of transcutaneous electrical nerve stimulation (TENS), which can be worn during walking and exercise, in elderly individuals with late-stage knee pain who exercise regularly. Methods: Thirty-two late-stage elderly individuals were evaluated for knee pain during rest, walking, and program exercises, with and without TENS. Gait analysis was performed using an IoT-based gait analysis device to examine the effects of TENS-induced analgesia on gait. Results: TENS significantly reduced knee pain during rest, walking, and programmed exercises, with the greatest analgesic effect observed during walking. The greater the knee pain without TENS, the more significant the analgesic effect of TENS. A comparison of gait parameters revealed a significant difference only in the gait cycle time, with a trend towards faster walking with TENS;however, the effect was limited. Conclusion: TENS effectively relieves knee pain in late-stage elderly individuals and can be safely applied during exercise. Pain management using TENS provides important insights into the implementation of exercise therapy in this age group.
文摘Objective:To analyze the effects of repetitive transcranial magnetic stimulation combined with motor control training on the treatment of stroke-induced hemiplegia,specifically focusing on the impact on patients’balance function and gait.Methods:Fifty-two cases of hemiplegic stroke patients were randomly divided into two groups,26 in the control group and 26 in the observation group,using computer-generated random grouping.All participants underwent conventional treatment and rehabilitation training.In addition to these,the control group received repetitive transcranial magnetic pseudo-stimulation therapy+motor control training,while the observation group received repetitive transcranial magnetic stimulation therapy+motor control training.The balance function and gait parameters of both groups were compared before and after the interventions and assessed the satisfaction of the interventions in both groups.Results:Before the invention,there were no significant differences in balance function scores and each gait parameter between the two groups(P>0.05).However,after the intervention,the observation group showed higher balance function scores compared to the control group(P<0.05).The observation group also exhibited higher step speed and step frequency,longer step length,and a higher overall satisfaction level with the intervention compared to the control group(P<0.05).Conclusion:The combination of repetitive transcranial magnetic stimulation and motor control training in the treatment of stroke-induced hemiplegia has demonstrated positive effects.It not only improves the patient’s balance function and gait but also contributes to overall physical rehabilitation.
文摘Human Activity Recognition(HAR)has always been a difficult task to tackle.It is mainly used in security surveillance,human-computer interaction,and health care as an assistive or diagnostic technology in combination with other technologies such as the Internet of Things(IoT).Human Activity Recognition data can be recorded with the help of sensors,images,or smartphones.Recognizing daily routine-based human activities such as walking,standing,sitting,etc.,could be a difficult statistical task to classify into categories and hence 2-dimensional Convolutional Neural Network(2D CNN)MODEL,Long Short Term Memory(LSTM)Model,Bidirectional long short-term memory(Bi-LSTM)are used for the classification.It has been demonstrated that recognizing the daily routine-based on human activities can be extremely accurate,with almost all activities accurately getting recognized over 90%of the time.Furthermore,because all the examples are generated from only 20 s of data,these actions can be recognised fast.Apart from classification,the work extended to verify and investigate the need for wearable sensing devices in individually walking patients with Cerebral Palsy(CP)for the evaluation of chosen Spatio-temporal features based on 3D foot trajectory.Case-control research was conducted with 35 persons with CP ranging in weight from 25 to 65 kg.Optical Motion Capture(OMC)equipment was used as the referral method to assess the functionality and quality of the foot-worn device.The average accuracy±precision for stride length,cadence,and step length was 3.5±4.3,4.1±3.8,and 0.6±2.7 cm respectively.For cadence,stride length,swing,and step length,people with CP had considerably high inter-stride variables.Foot-worn sensing devices made it easier to examine Gait Spatio-temporal data even without a laboratory set up with high accuracy and precision about gait abnormalities in people who have CP during linear walking.
基金funded by the Research Foundation of Education Bureau of Hunan Province,China,under Grant Number 21B0060the National Natural Science Foundation of China,under Grant Number 61701179.
文摘Subject identification via the subject’s gait is challenging due to variations in the subject’s carrying and dressing conditions in real-life scenes.This paper proposes a novel targeted 3-dimensional(3D)gait model(3DGait)represented by a set of interpretable 3DGait descriptors based on a 3D parametric body model.The 3DGait descriptors are utilised as invariant gait features in the 3DGait recognition method to address object carrying and dressing.The 3DGait recognitionmethod involves 2-dimensional(2D)to 3DGaitdata learningbasedon3Dvirtual samples,a semantic gait parameter estimation Long Short Time Memory(LSTM)network(3D-SGPE-LSTM),a feature fusion deep model based on a multi-set canonical correlation analysis,and SoftMax recognition network.First,a sensory experiment based on 3D body shape and pose deformation with 3D virtual dressing is used to fit 3DGait onto the given 2D gait images.3Dinterpretable semantic parameters control the 3D morphing and dressing involved.Similarity degree measurement determines the semantic descriptors of 2D gait images of subjects with various shapes,poses and styles.Second,using the 2D gait images as input and the subjects’corresponding 3D semantic descriptors as output,an end-to-end 3D-SGPE-LSTM is constructed and trained.Third,body shape,pose and external gait factors(3D-eFactors)are estimated using the 3D-SGPE-LSTM model to create a set of interpretable gait descriptors to represent the 3DGait Model,i.e.,3D intrinsic semantic shape descriptor(3DShape);3D skeleton-based gait pose descriptor(3D-Pose)and 3D dressing with other 3D-eFators.Finally,the 3D-Shape and 3D-Pose descriptors are coupled to a unified pattern space by learning prior knowledge from the 3D-eFators.Practical research on CASIA B,CMU MoBo,TUM GAID and GPJATK databases shows that 3DGait is robust against object carrying and dressing variations,especially under multi-cross variations.
基金Shaoguan Municipal Health Bureau,No.Y22058Shaoguan City Science and Technology Plan Project,No.220517164531600+1 种基金The clinical trial was approved by the Ethics Committee of the Yuebei People's Hospital(No.KY-2021-327)The program was registered online in the Chinese Clinical Trial Registry(Registration No.ChiCTR2100052767)。
文摘BACKGROUND The results of existing lower extremity robotics studies are conflicting,and few relevant clinical trials have examined short-term efficacy.In addition,most of the outcome indicators in existing studies are scales,which are not objective enough.We used the combination of objective instrument measurement and scale to explore the short-term efficacy of the lower limb A3 robot,to provide a clinical reference.AIM To investigate the improvement of lower limb walking ability and balance in stroke treated by A3 lower limb robot.METHODS Sixty stroke patients were recruited prospectively in a hospital and randomized into the A3 group and the control group.They received 30 min of A3 robotics training and 30 min of floor walking training in addition to 30 min of regular rehabilitation training.The training was performed five times a week,once a day,for 2 wk.The t-test or non-parametric test was used to compare the threedimensional gait parameters and balance between the two groups before and after treatment.RESULTS The scores of basic activities of daily living,Stroke-Specific Quality of Life Scale,FM balance meter,Fugl-Meyer Assessment scores,Rivermead Mobility Index,Stride speed,Stride length,and Time Up and Go test in the two groups were significantly better than before treatment(19.29±12.15 vs 3.52±4.34;22.57±17.99 vs 4.07±2.51;1.21±0.83 vs 0.18±0.40;3.50±3.80 vs 0.96±2.08;2.07±1.21 vs 0.41±0.57;0.89±0.63 vs 0.11±0.32;12.38±9.00 vs 2.80±3.43;18.84±11.24 vs 3.80±10.83;45.12±69.41 vs 8.41±10.20;29.45±16.62 vs 8.68±10.74;P<0.05).All outcome indicators were significantly better in the A3 group than in the control group,except the area of the balance parameter.CONCLUSION For the short-term treatment of patients with subacute stroke,the addition of A3 robotic walking training to conventional physiotherapy appears to be more effective than the addition of ground-based walking training.
基金supported by the Xi’an Science and Technology Plan Project (No.2020KJRC0108).
文摘To address the problem of frequent battery replacement for wearable sensors applied to fall detection among the elderly,a portable and lowcost triboelectric nanogenerator(TENG)-based self-powered sensor for human gait monitoring is proposed.The main fabrication materials of the TENG are polytetrafluoroethylene(PTFE)film,aluminum(Al)foil,and polyimide(PI)film,where PTFE and Al are the friction layer materials and the PI film is used to improve the output performance.Exploiting the ability of TENGs to monitor changes in environmental conditions,a self-powered sensor based on the TENG is placed in an insole to collect gait information.Since a TENG does not require a power source to convert physical and mechanical signals into electrical signals,the electrical signals can be used as sensing signals to be analyzed by a computer to recognize daily human activities and fall status.Experimental results show that the accuracy of the TENG-based sensor for recognizing human gait is 97.2%,demonstrating superior sensing performance and providing valuable insights for future monitoring of fall events in the elderly population.
基金Supported by National Key Research and Development Program of China(Grant No.2021YFF0306202).
文摘The current gait planning for legged robots is mostly based on human presets,which cannot match the flexible characteristics of natural mammals.This paper proposes a gait optimization framework for hexapod robots called Smart Gait.Smart Gait contains three modules:swing leg trajectory optimization,gait period&duty optimization,and gait sequence optimization.The full dynamics of a single leg,and the centroid dynamics of the overall robot are considered in the respective modules.The Smart Gait not only helps the robot to decrease the energy consumption when in locomotion,mostly,it enables the hexapod robot to determine its gait pattern transitions based on its current state,instead of repeating the formalistic clock-set step cycles.Our Smart Gait framework allows the hexapod robot to behave nimbly as a living animal when in 3D movements for the first time.The Smart Gait framework combines offline and online optimizations without any fussy data-driven training procedures,and it can run efficiently on board in real-time after deployment.Various experiments are carried out on the hexapod robot LittleStrong.The results show that the energy consumption is reduced by 15.9%when in locomotion.Adaptive gait patterns can be generated spontaneously both in regular and challenge environments,and when facing external interferences.
基金supported by the“Human Resources Program in Energy Technol-ogy”of the Korea Institute of Energy Technology Evaluation and Planning(KETEP)and Granted Financial Resources from the Ministry of Trade,Industry,and Energy,Republic of Korea(No.20204010600090)The funding of this work was provided by Princess Nourah bint Abdulrahman University Researchers Supporting Project Number(PNURSP2023R410),Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘The demand for a non-contact biometric approach for candidate identification has grown over the past ten years.Based on the most important biometric application,human gait analysis is a significant research topic in computer vision.Researchers have paid a lot of attention to gait recognition,specifically the identification of people based on their walking patterns,due to its potential to correctly identify people far away.Gait recognition systems have been used in a variety of applications,including security,medical examinations,identity management,and access control.These systems require a complex combination of technical,operational,and definitional considerations.The employment of gait recognition techniques and technologies has produced a number of beneficial and well-liked applications.Thiswork proposes a novel deep learning-based framework for human gait classification in video sequences.This framework’smain challenge is improving the accuracy of accuracy gait classification under varying conditions,such as carrying a bag and changing clothes.The proposed method’s first step is selecting two pre-trained deep learningmodels and training fromscratch using deep transfer learning.Next,deepmodels have been trained using static hyperparameters;however,the learning rate is calculated using the particle swarmoptimization(PSO)algorithm.Then,the best features are selected from both trained models using the Harris Hawks controlled Sine-Cosine optimization algorithm.This algorithm chooses the best features,combined in a novel correlation-based fusion technique.Finally,the fused best features are categorized using medium,bi-layer,and tri-layered neural networks.On the publicly accessible dataset known as the CASIA-B dataset,the experimental process of the suggested technique was carried out,and an improved accuracy of 94.14% was achieved.The achieved accuracy of the proposed method is improved by the recent state-of-the-art techniques that show the significance of this work.
基金financially supported by the Beijing Natural Science Foundation for Young Scientists(Grant No.8214052)the Talent Fund of Beijing Jiaotong University(Grant No.2021RC226)the State Key Laboratory for GeoMechanics and Deep Underground Engineering,China University of Mining and Technology(Grant No.SKLGDUEK2115).
文摘Three-dimensional(3D)printing technology has been widely used to create artificial rock samples in rock mechanics.While 3D printing can create complex fractures,the material still lacks sufficient similarity to natural rock.Extrusion free forming(EFF)is a 3D printing technique that uses clay as the printing material and cures the specimens through high-temperature sintering.In this study,we attempted to use the EFF technology to fabricate artificial rock specimens.The results show the physico-mechanical properties of the specimens are significantly affected by the sintering temperature,while the nozzle diameter and layer thickness also have a certain impact.The specimens are primarily composed of SiO_(2),with mineral compositions similar to that of natural rocks.The density,uniaxial compressive strength(UCS),elastic modulus,and tensile strength of the printed specimens fall in the range of 1.65–2.54 g/cm3,16.46–50.49 MPa,2.17–13.35 GPa,and 0.82–17.18 MPa,respectively.It is capable of simulating different types of rocks,especially mudstone,sandstone,limestone,and gneiss.However,the simulation of hard rocks with UCS exceeding 50 MPa still requires validation.
基金supported by Guizhou Provincial Department of Science and Technology(Guizhou Science and Technology Cooperation Support[2021]General 442)Guizhou Provincial Department of Science and Technology(Guizhou Science and Technology Cooperation Support[2023]General 179)Guizhou Provincial Department of Science and Technology(Guizhou Science and Technology Cooperation Support[2023]General 096).
文摘Personalized gait curves are generated to enhance patient adaptability to gait trajectories used for passive training in the early stage of rehabilitation for hemiplegic patients.The article utilizes the random forest algorithm to construct a gait parameter model,which maps the relationship between parameters such as height,weight,age,gender,and gait speed,achieving prediction of key points on the gait curve.To enhance prediction accuracy,an attention mechanism is introduced into the algorithm to focus more on the main features.Meanwhile,to ensure high similarity between the reconstructed gait curve and the normal one,probabilistic motion primitives(ProMP)are used to learn the probability distribution of normal gait data and construct a gait trajectorymodel.Finally,using the specified step speed as input,select a reference gait trajectory from the learned trajectory,and reconstruct the curve of the reference trajectoryusing the gait keypoints predictedby the parametermodel toobtain the final curve.Simulation results demonstrate that the method proposed in this paper achieves 98%and 96%curve correlations when generating personalized lower limb gait curves for different patients,respectively,indicating its suitability for such tasks.
文摘Objective: To explore gait kinematics analysis and evaluate the surgical efficacy of total knee arthroplasty (TKA), as well as its guiding significance for postoperative rehabilitation. Method: Fifty patients admitted to TKA treatment for knee osteoarthritis from December 2022 to July 2023 were included, which were divided into an intervention group (gait kinematics analysis group, n = 25) and a control group (conventional rehabilitation program group, n = 25). All patients underwent HSS score and KSS score before surgery (T0), 1 month after surgery (T1), 3 months after surgery (T2), and 6 months after surgery (T3). The intervention group underwent gait kinematics analysis at 1 month after surgery (T1) and 3 months after surgery (T2). Two groups measured the hip knee ankle angle (HKA), distal femoral lateral angle (LDFA), and proximal tibial medial angle (MPTA) on knee joint radiographs before and after surgery. Results: There was no significant difference in general information, preoperative imaging parameters, and functional scores between the two groups of patients. There was no significant difference in functional scores and postoperative prosthesis alignment between the two groups of patients in the first month after surgery. The intervention group showed a significant decrease in gait kinematic scores in the first month, with hip joint scores being particularly prominent (P 0.05). Conclusion: Gait kinematic analysis is helpful in evaluating the postoperative efficacy of TKA and can guide early and rapid recovery after TKA.
文摘Purpose: This study focused on maintaining and improving the walking function of late-stage older individuals while longitudinally tracking the effects of regular exercise programs in a day-care service specialized for preventive care over 5 years, using detailed gait function measurements with an accelerometer-based system. Methods: Seventy individuals (17 male and 53 female) of a daycare service in Tokyo participated in a weekly exercise program, meeting 1 - 2 times. The average age of the participants at the start of the program was 81.4 years. Gait function, including gait speed, stride length, root mean square (RMS) of acceleration, gait cycle time and its standard deviation, and left-right difference in stance time, was evaluated every 6 months. Results: Gait speed and stride length improved considerably within six months of starting the exercise program, confirming an initial improvement in gait function. This suggests that regular exercise programs can maintain or improve gait function even age groups that predictably have a gradual decline in gait ability due to enhanced age. In the long term, many indicators tended to approach baseline values. However, the exercise program seemingly counteracts age-related changes in gait function and maintains a certain level of function. Conclusions: While a decline in gait ability with aging is inevitable, establishing appropriate exercise habits in late-stage older individuals may contribute to long-term maintenance of gait function.
文摘Understanding the neural underpinning of human gait and balance is one of the most pertinent challenges for 21st-century translational neuroscience due to the profound impact that falls and mobility disturbances have on our aging population.Posture and gait control does not happen automatically,as previously believed,but rather requires continuous involvement of central nervous mechanisms.To effectively exert control over the body,the brain must integrate multiple streams of sensory information,including visual,vestibular,and somatosensory signals.The mechanisms which underpin the integration of these multisensory signals are the principal topic of the present work.Existing multisensory integration theories focus on how failure of cognitive processes thought to be involved in multisensory integration leads to falls in older adults.Insufficient emphasis,however,has been placed on specific contributions of individual sensory modalities to multisensory integration processes and cross-modal interactions that occur between the sensory modalities in relation to gait and balance.In the present work,we review the contributions of somatosensory,visual,and vestibular modalities,along with their multisensory intersections to gait and balance in older adults and patients with Parkinson’s disease.We also review evidence of vestibular contributions to multisensory temporal binding windows,previously shown to be highly pertinent to fall risk in older adults.Lastly,we relate multisensory vestibular mechanisms to potential neural substrates,both at the level of neurobiology(concerning positron emission tomography imaging)and at the level of electrophysiology(concerning electroencephalography).We hope that this integrative review,drawing influence across multiple subdisciplines of neuroscience,paves the way for novel research directions and therapeutic neuromodulatory approaches,to improve the lives of older adults and patients with neurodegenerative diseases.
文摘Individuals with NGLY1 Deficiency, an inherited autosomal recessive disorder, exhibit hyperkinetic movements including athetoid, myoclonic, dysmetric, and dystonic movements impacting both upper and lower limb motion. This report provides the first set of laboratory-based measures characterizing the gait patterns of two individuals with NGLY1 Deficiency, using both linear and non-linear measures, during treadmill walking, and compares them to neurotypical controls. Lower limb kinematics were obtained with a camera-based motion analysis system and bilateral time normalized lower limb joint time series waveforms were developed. Linear measures of joint range of motion, stride times and peak angular velocity were obtained, and confidence intervals were used to determine if there were differences between the patients and control. Correlations between participant and control mean joint waveforms were calculated and used to evaluate the similarities between patients and controls. Non-linear measures included: joint angle-angle diagrams, phase-portrait areas, and continuous relative phase (CRP) measures. These measures were used to assess joint coordination and control features of the lower limb motion. Participants displayed high correlations with their control counterparts for the hip and knee joint waveforms, but joint motion was restricted. Peak angular velocities were also significantly less than those of the controls. Both angle-angle and phase-portrait areas were less than the controls although the general shapes of those diagrams were similar to those of the controls. The NGLY1 Deficient participants’ CRP measures displayed disrupted coordination patterns with the knee-ankle patterns displaying more disruption than the hip-knee measures. Overall, the participants displayed a functional walking pattern that differed in many quantitative ways from those of the neurotypical controls. Using both linear and non-linear measures to characterize gait provides a more comprehensive and nuanced characterization of NGLY1 gait and can be used to develop interventions targeted toward specific aspects of disordered gait.
基金funded by the Shanghai City Committee of Science and Technology Key Project (No. 12490503200)the National Science Foundation for Distinguished Young Scholars of China (No. 81025022)
文摘Background: Although Tai Ji Quan has been shown to relieve pain and improve functional mobility in people with knee osteoarthritis(OA), little is known about its potential benefits on gait characteristics among older Chinese women who have a high prevalence of both radiographic and symptomatic knee OA. This study aims to assess the efficacy of a tailored Tai Ji Quan intervention on gait kinematics for older Chinese women with knee OA.Methods: A randomized controlled trial involving 46 older women in Shanghai, China, with clinically diagnosed knee OA. Randomized(1:1)participants received either a 60 min Tai Ji Quan session(n = 23) 3 times weekly or a 60 min bi-weekly educational session(n = 23) for 24 weeks.Primary outcomes were changes in gait kinematic measures from baseline to 24 weeks. Secondary outcomes included changes in scores on the Western Ontario and Mc Master University Osteoarthritis Index(WOMAC) and Short Physical Performance Battery(SPPB).Results: After 24 weeks the Tai Ji Quan group demonstrated better performance in gait velocity(mean difference, 8.40 cm/s, p = 0.01), step length(mean difference, 3.52 cm, p = 0.004), initial contact angle(mean difference, 2.19°, p = 0.01), and maximal angle(mean difference, 2.61°,p = 0.003) of flexed knees during stance phase compared to the control group. In addition, the Tai Ji Quan group showed significant improvement in WOMAC scores(p < 0.01)(mean difference,-4.22 points in pain, p = 0.002;-2.41 points in stiffness, p < 0.001;-11.04 points in physical function, p = 0.006) and SPPB scores(mean difference, 1.22 points, p < 0.001).Conclusion: Among older Chinese women with knee OA, a tailored Tai Ji Quan intervention improved gait outcomes. The intervention also improved overall function as indexed by the WOMAC and SPPB. These results support the use of Tai Ji Quan for older Chinese adults with knee OA to both improve their functional mobility and reduce pain symptomatology.
基金supported by National Natural Science Foundation of China(Grant No.51375289)Shanghai Municipal National Natural Science Foundation of China(Grant No.13ZR1415500)Innovation Fund of Shanghai Education Commission of China(Grant No.13YZ020)
文摘Quadruped robots consume a lot of energy, which is one of the factors restricting their application. Energy efficiency is one of the key evaluating indicators for walking robots. The relationship between energy and elastic elements of walking robots have been studied, but different walking gait patterns and contact status have important influences on locomotion energy efficiency, and the energy efficiency considering the foot-end trajectory has not been reported. Therefore, the energy consumption and energy efficiency of quadruped robot with trot gait and combined cycloid foot trajectory are studied. The forward and inverse kinematics of quadruped robot is derived. The combined cycloid function is proposed to generate horizontal and vertical foot trajectory respectively, which can ensure the acceleration curve of the foot-end smoother and more successive, and reduce the contact force between feet and environment. Because of the variable topology mechanism characteristic of quadruped robot, the leg state is divided into three different phases which are swing phase, transition phase and stance phase during one trot gait cycle. The non-continuous variable constraint between feet and environment of quadruped robot is studied. The dynamic model of quadruped robot is derived considering the variable topology mechanism characteristic, the periodic contact and elastic elements of the robot. The total energy consumption of walking robot during one gait cycle is analyzed based on the dynamic model. The specific resistance is used to evaluate energy efficiency of quadruped robot. The calculation results show the relationships between specific resistance and gait parameters, which can be used to determine the reasonable gait parameters.
基金Supported by the Research Project of Future Growth Engine Flagship Project,No:CN16040)by Minister of Science,ICT and Future Planningthe National Research Foundation of Korea grant funded by the Korea government(Ministry of Science,ICT and Future Planning),No.NRF-2017R1A2B4011478
文摘BACKGROUND De-afferentation or non-weight bearing induces rapid cortical and spinalα-motor neuron excitability.Author supposed that an end-effector type gait robot(EEGR)could provide patients with a training condition that was specific enough to activate rapid cortical/spinal neuroplasticity,leading to immediate muscle strengthening.The electromyographic and biomechanical comparisons were conducted.AIM To compare the electromyographic activities of the thigh and shank muscles and isometric peak torque(PT)before and after walking training on a floor or in the end-effector gait robot.METHODS Twelve outpatients without ambulatory dysfunction were recruited.Order of two interventions(5-min training on a floor at a comfortable pace or training in an EEGR with non-weight bearing on their feet and 100%guidance force at 2.1 km/h)were randomly chosen.Isometric PT,maximal ratio of torque development,amplitude of compound motor action potential(CMAP),and area under the curve(AUC)were evaluated before and 10 min after both interventions.RESULTS The degree of PT improvement of the dominant knee flexors was larger in the EEGR than on the floor(9.6±22.4 Nm/BW,P<0.01).The EEGR-trained patients had greater PT improvement of the dominant knee extensors than those who trained on the floor(4.5±28.1 Nm/BW,P<0.01).However,all electromyographic activities of the thigh and shank muscles(peak CMAP,mean and peak AUC)were significantly lower for the use of the EEGR than walking on the floor.CONCLUSION Immediate strengthening of the knee flexors and extensors was induced after the 5-min EEGR training,despite reduced muscular use.