Parkinson’s Disease(PD)is a neurodegenerative disease which shows a deficiency in dopaminehormone in the brain.It is a common irreversible impairment among elderly people.Identifying this disease in its preliminary s...Parkinson’s Disease(PD)is a neurodegenerative disease which shows a deficiency in dopaminehormone in the brain.It is a common irreversible impairment among elderly people.Identifying this disease in its preliminary stage is important to improve the efficacy of the treatment process.Disordered gait is one of the key indications of early symptoms of PD.Therefore,the present paper introduces a novel approach to identify pa rkinsonian gait using raw vertical spatiotemporal ground reaction force.A convolution neural network(CNN)is implemented to identify the features in the parkinsonian gaits and their progressive stages.Moreover,the var iations of the gait pressures were visually recreated using ANSYS finite element software package.The CNN model has shown a 97%accuracy of recognizing parkinsonian gait and their different stages,and ANSYS model is implemented to visualize the pressure variation of the foot during a bottom-up approach.展开更多
The goal of this paper is to develop a unified online motion generation scheme for quadruped lateral-sequence walk and trot gaits based on a linear model predictive control formulation.Specifically,the dynamics of the...The goal of this paper is to develop a unified online motion generation scheme for quadruped lateral-sequence walk and trot gaits based on a linear model predictive control formulation.Specifically,the dynamics of the linear pendulum model is formulated over a predictive horizon by dimensional analysis.Through gait pattern conversion,the lateral-sequence walk and trot gaits of the quadruped can be regarded as unified biped gaits,allowing the dynamics of the linear inverted pendulum model to serve quadruped motion generation.In addition,a simple linearization of the center of pressure constraints for these quadruped gaits is developed for linear model predictive control problem.Furthermore,the motion generation problem can be solved online by quadratic programming with foothold adaptation.It is demonstrated that the proposed unified scheme can generate stable locomotion online for quadruped lateral-sequence walk and trot gaits,both in simulation and on hardware.The results show significant performance improvements compared to previous work.Moreover,the results also suggest the linearly simplified scheme has the ability to robustness against unexpected disturbances.展开更多
The remarkable skill of changing its grasp status and relocating its fingers to perform continuous in-hand manipulation is essential for a multifingered anthropomorphic hand.A commonly utilized method of manipulation ...The remarkable skill of changing its grasp status and relocating its fingers to perform continuous in-hand manipulation is essential for a multifingered anthropomorphic hand.A commonly utilized method of manipulation involves a series of basic movements executed by a high-level controller.However,it remains unclear how these primitives evolve into sophisticated finger gaits during manipulation.Here,we propose an adaptive finger gait-based manipulation method that offers real-time regulation by dynamically changing the primitive interval to ensure the force/moment balance of the object.Successful manipulation relies on contact events that act as triggers for real-time online replanning of multifinger manipulation.We identify four basic motion primitives of finger gaits and create a heuristic finger gait that enables the continuous object rotation of a round cup.Our experimental results verify the effectiveness of the proposed method.Despite the constant breaking and reengaging of contact between the fingers and the object during manipulation,the robotic hand can reliably manipulate the object without failure.Even when the object is subjected to interfering forces,the proposed method demonstrates robustness in managing interference.This work has great potential for application to the dexterous operation of anthropomorphic multifingered hands.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 development of computer vision technology has enabled the use of markerless movement tracking for biomechanical analysis.Recent research has reported the feasibility of markerless systems in motion anal...Background:The development of computer vision technology has enabled the use of markerless movement tracking for biomechanical analysis.Recent research has reported the feasibility of markerless systems in motion analysis but has yet to fully explore their utility for capturing faster movements,such as running.Applied studies using markerless systems in clinical and sports settings are still lacking.Thus,the present study compared running biomechanics estimated by marker-based and markerless systems.Given running speed not only affects sports performance but is also associated with clinical injury prevention,diagnosis,and rehabilitation,we aimed to investigate the effects of speed on the comparison of estimated lower extremity joint moments and powers between markerless and marker-based technologies during treadmill running as a concurrent validating study.Methods:Kinematic data from marker-based/markerless technologies were collected,along with ground reaction force data,from 16 young adults running on an instrumented treadmill at 3 speeds:2.24 m/s,2.91 m/s,and 3.58 m/s(5.0 miles/h,6.5 miles/h,and 8.0 miles/h).Sagittal plane moments and powers of the hip,knee,and ankle were calculated by inverse dynamic methods.Time series analysis and statistical parametric mapping were used to determine system differences.Results:Compared to the marker-based system,the markerless system estimated increased lower extremity joint kinetics with faster speed during the swing phase in most cases.Conclusion:Despite the promising application of markerless technology in clinical settings,systematic markerless overestimation requires focused attention.Based on segment pose estimations,the centers of mass estimated by markerless technologies were farther away from the relevant distal joint centers,which led to greater joint moments and powers estimates by markerless vs.marker-based systems.The differences were amplified by running speed.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
Modern conflicts demand substantial physical and psychological exertion,often resulting in fatigue and diminished combat or operational readiness.Several exoskeletons have been developed recently to address these chal...Modern conflicts demand substantial physical and psychological exertion,often resulting in fatigue and diminished combat or operational readiness.Several exoskeletons have been developed recently to address these challenges,presenting various limitations that affect their operational or everyday usability.This article evaluates the performance of a dual-purpose passive ankle exoskeleton developed for the reduction of metabolic costs during walking,seeking to identify a force element that could be applied to the target population.Based on the 6-min walk test,twenty-nine subjects participated in the study using three different force elements.The results indicate that it is possible to reduce metabolic expenditure while using the developed exoskeleton.Additionally,the comfort and range of motion results verify the exoskeleton's suitability for use in uneven terrain and during extended periods.Nevertheless,the choice of the force element should be tailored to each user,and the control system should be adjustable to optimise the exoskeleton's performance.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
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
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
Hand gestures have been used as a significant mode of communication since the advent of human civilization.By facilitating human-computer interaction(HCI),hand gesture recognition(HGRoc)technology is crucial for seaml...Hand gestures have been used as a significant mode of communication since the advent of human civilization.By facilitating human-computer interaction(HCI),hand gesture recognition(HGRoc)technology is crucial for seamless and error-free HCI.HGRoc technology is pivotal in healthcare and communication for the deaf community.Despite significant advancements in computer vision-based gesture recognition for language understanding,two considerable challenges persist in this field:(a)limited and common gestures are considered,(b)processing multiple channels of information across a network takes huge computational time during discriminative feature extraction.Therefore,a novel hand vision-based convolutional neural network(CNN)model named(HVCNNM)offers several benefits,notably enhanced accuracy,robustness to variations,real-time performance,reduced channels,and scalability.Additionally,these models can be optimized for real-time performance,learn from large amounts of data,and are scalable to handle complex recognition tasks for efficient human-computer interaction.The proposed model was evaluated on two challenging datasets,namely the Massey University Dataset(MUD)and the American Sign Language(ASL)Alphabet Dataset(ASLAD).On the MUD and ASLAD datasets,HVCNNM achieved a score of 99.23% and 99.00%,respectively.These results demonstrate the effectiveness of CNN as a promising HGRoc approach.The findings suggest that the proposed model have potential roles in applications such as sign language recognition,human-computer interaction,and robotics.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
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
BACKGROUND Several studies have reported that the walking trail making test(WTMT)completion time is significantly higher in patients with developmental coordination disorders and mild cognitive impairments.We hypothes...BACKGROUND Several studies have reported that the walking trail making test(WTMT)completion time is significantly higher in patients with developmental coordination disorders and mild cognitive impairments.We hypothesized that WTMT performance would be altered in older adults with white matter hyperintensities(WMH).AIM To explore the performance in the WTMT in older people with WMH.METHODS In this single-center,observational study,25 elderly WMH patients admitted to our hospital from June 2019 to June 2020 served as the WMH group and 20 participants matched for age,gender,and educational level who were undergoing physical examination in our hospital during the same period served as the control group.The participants completed the WTMT-A and WTMT-B to obtain their gait parameters,including WTMT-A completion time,WTMT-B completion time,speed,step length,cadence,and stance phase percent.White matter lesions were scored according to the Fazekas scale.Multiple neuropsychological assessments were carried out to assess cognitive function.The relationships between WTMT performance and cognition and motion in elderly patients with WMH were analyzed by partial Pearson correlation analysis.RESULTS Patients with WMH performed significantly worse on the choice reaction test(CRT)(0.51±0.09 s vs 0.44±0.06 s,P=0.007),verbal fluency test(VFT,14.2±2.75 vs 16.65±3.54,P=0.012),and digit symbol substitution test(16.00±2.75 vs 18.40±3.27,P=0.010)than participants in the control group.The WMH group also required significantly more time to complete the WTMT-A(93.00±10.76 s vs 70.55±11.28 s,P<0.001)and WTMT-B(109.72±12.26 s vs 82.85±7.90 s,P<0.001).WTMT-A completion time was positively correlated with CRT time(r=0.460,P=0.001),while WTMT-B completion time was negatively correlated with VFT(r=-0.391,P=0.008).On the WTMT-A,only speed was found to statistically differ between the WMH and control groups(0.803±0.096 vs 0.975±0.050 m/s,P<0.001),whereas on the WTMT-B,the WMH group exhibited a significantly lower speed(0.778±0.111 vs 0.970±0.053 m/s,P<0.001)and cadence(82.600±4.140 vs 85.500±5.020 steps/m,P=0.039),as well as a higher stance phase percentage(65.061±1.813%vs 63.513±2.465%,P=0.019)relative to controls.CONCLUSION Older adults with WMH showed obviously poorer WTMT performance.WTMT could be a potential indicator for cognitive and motor deficits in patients with WMH.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
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
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
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 investigate the efficacy and safety of low-frequency repetitive transcranial magnetic stimulation(rTMS)for the treatment of lower limb motor dysfunction after stroke.Methods:A total of 96 patients with st...Objective:To investigate the efficacy and safety of low-frequency repetitive transcranial magnetic stimulation(rTMS)for the treatment of lower limb motor dysfunction after stroke.Methods:A total of 96 patients with stroke and lower limb motor dysfunction were enrolled in this study,and were randomly divided into the experimental group and the sham stimulation group using the method of calculator-generated random numbers.Both groups received conventional medication and rehabilitation therapy.The experimental group received 4 weeks of 1 Hz rTMS treatment in the primary cortical motor area(M1)of the healthy side,with the treatment coil tangent to the skull surface;the sham stimulation group underwent the same procedures as the experimental group,but the treatment coil was perpendicular to the skull surface instead.Lower-extremity subscale of the Fugl-Meyer Assessment(FMA-LE),Berg Balance Scale(BBS),gait analysis,and lower-extremity surface electromyography(LESEM)were performed in both groups before and after rTMS treatment.Results:All 96 patients completed the test with no shedding and no adverse reactions.After treatment,the FMA-LE score and BBS score of the 2 groups of patients were significantly improved as compared with the pre-treatment(P<0.05),and the TUG test time was reduced as compared with the pre-treatment(P<0.05).The true stimulation group had greater improvement in all assessment indexes than that of the sham stimulation group(P<0.05).After treatment,the electromyographic activity of the tibialis anterior and rectus femoris muscles in the true simulation group improved significantly.The step length,step speed,and step frequency were also significantly improved in both groups after treatment,and the symmetrical ratio of step length and support time was reduced(P<0.05).Comparison between the groups revealed that the true simulation group significantly improved after rTMS treatment as compared to the sham stimulation group(P<0.05).Conclusion:1Hz rTMS treatment safely and effectively improved motor and balance function in patients with post-stroke lower limb motor dysfunction.展开更多
文摘Parkinson’s Disease(PD)is a neurodegenerative disease which shows a deficiency in dopaminehormone in the brain.It is a common irreversible impairment among elderly people.Identifying this disease in its preliminary stage is important to improve the efficacy of the treatment process.Disordered gait is one of the key indications of early symptoms of PD.Therefore,the present paper introduces a novel approach to identify pa rkinsonian gait using raw vertical spatiotemporal ground reaction force.A convolution neural network(CNN)is implemented to identify the features in the parkinsonian gaits and their progressive stages.Moreover,the var iations of the gait pressures were visually recreated using ANSYS finite element software package.The CNN model has shown a 97%accuracy of recognizing parkinsonian gait and their different stages,and ANSYS model is implemented to visualize the pressure variation of the foot during a bottom-up approach.
基金supported by the National Natural Science Foundation of China(Nos.52305072 and 52122503)Natural Science Foundation of Hebei Province of China(No.E2022203095)+2 种基金University-Industry Collaborative Education Program(No.220603936245709)Cultivation Project for Basic Research and Innovation of Yanshan University(No.2021LGQN004)henzhen Special Fund for Future Industrial Development(No.KJZD20230923114222045).
文摘The goal of this paper is to develop a unified online motion generation scheme for quadruped lateral-sequence walk and trot gaits based on a linear model predictive control formulation.Specifically,the dynamics of the linear pendulum model is formulated over a predictive horizon by dimensional analysis.Through gait pattern conversion,the lateral-sequence walk and trot gaits of the quadruped can be regarded as unified biped gaits,allowing the dynamics of the linear inverted pendulum model to serve quadruped motion generation.In addition,a simple linearization of the center of pressure constraints for these quadruped gaits is developed for linear model predictive control problem.Furthermore,the motion generation problem can be solved online by quadratic programming with foothold adaptation.It is demonstrated that the proposed unified scheme can generate stable locomotion online for quadruped lateral-sequence walk and trot gaits,both in simulation and on hardware.The results show significant performance improvements compared to previous work.Moreover,the results also suggest the linearly simplified scheme has the ability to robustness against unexpected disturbances.
基金This work was supported by the National Natural Science Foundation of China(U2013212)the Key Research and Development Program of Zhejiang,China(2021C04015)the Fundamental Research Funds for the Provincial Universities of Zhejiang,China(RF-C2019004).
文摘The remarkable skill of changing its grasp status and relocating its fingers to perform continuous in-hand manipulation is essential for a multifingered anthropomorphic hand.A commonly utilized method of manipulation involves a series of basic movements executed by a high-level controller.However,it remains unclear how these primitives evolve into sophisticated finger gaits during manipulation.Here,we propose an adaptive finger gait-based manipulation method that offers real-time regulation by dynamically changing the primitive interval to ensure the force/moment balance of the object.Successful manipulation relies on contact events that act as triggers for real-time online replanning of multifinger manipulation.We identify four basic motion primitives of finger gaits and create a heuristic finger gait that enables the continuous object rotation of a round cup.Our experimental results verify the effectiveness of the proposed method.Despite the constant breaking and reengaging of contact between the fingers and the object during manipulation,the robotic hand can reliably manipulate the object without failure.Even when the object is subjected to interfering forces,the proposed method demonstrates robustness in managing interference.This work has great potential for application to the dexterous operation of anthropomorphic multifingered hands.
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.
文摘Background:The development of computer vision technology has enabled the use of markerless movement tracking for biomechanical analysis.Recent research has reported the feasibility of markerless systems in motion analysis but has yet to fully explore their utility for capturing faster movements,such as running.Applied studies using markerless systems in clinical and sports settings are still lacking.Thus,the present study compared running biomechanics estimated by marker-based and markerless systems.Given running speed not only affects sports performance but is also associated with clinical injury prevention,diagnosis,and rehabilitation,we aimed to investigate the effects of speed on the comparison of estimated lower extremity joint moments and powers between markerless and marker-based technologies during treadmill running as a concurrent validating study.Methods:Kinematic data from marker-based/markerless technologies were collected,along with ground reaction force data,from 16 young adults running on an instrumented treadmill at 3 speeds:2.24 m/s,2.91 m/s,and 3.58 m/s(5.0 miles/h,6.5 miles/h,and 8.0 miles/h).Sagittal plane moments and powers of the hip,knee,and ankle were calculated by inverse dynamic methods.Time series analysis and statistical parametric mapping were used to determine system differences.Results:Compared to the marker-based system,the markerless system estimated increased lower extremity joint kinetics with faster speed during the swing phase in most cases.Conclusion:Despite the promising application of markerless technology in clinical settings,systematic markerless overestimation requires focused attention.Based on segment pose estimations,the centers of mass estimated by markerless technologies were farther away from the relevant distal joint centers,which led to greater joint moments and powers estimates by markerless vs.marker-based systems.The differences were amplified by running speed.
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the Portuguese Army,through CINAMIL,within project ELITE2-Enhancement LITe ExoskeletonFoundation for Science and Technology (FCT),through IDMEC,under LAETA,project UIDB/50022/2020 for supporting this research。
文摘Modern conflicts demand substantial physical and psychological exertion,often resulting in fatigue and diminished combat or operational readiness.Several exoskeletons have been developed recently to address these challenges,presenting various limitations that affect their operational or everyday usability.This article evaluates the performance of a dual-purpose passive ankle exoskeleton developed for the reduction of metabolic costs during walking,seeking to identify a force element that could be applied to the target population.Based on the 6-min walk test,twenty-nine subjects participated in the study using three different force elements.The results indicate that it is possible to reduce metabolic expenditure while using the developed exoskeleton.Additionally,the comfort and range of motion results verify the exoskeleton's suitability for use in uneven terrain and during extended periods.Nevertheless,the choice of the force element should be tailored to each user,and the control system should be adjustable to optimise the exoskeleton's performance.
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funded by Researchers Supporting Project Number(RSPD2024 R947),King Saud University,Riyadh,Saudi Arabia.
文摘Hand gestures have been used as a significant mode of communication since the advent of human civilization.By facilitating human-computer interaction(HCI),hand gesture recognition(HGRoc)technology is crucial for seamless and error-free HCI.HGRoc technology is pivotal in healthcare and communication for the deaf community.Despite significant advancements in computer vision-based gesture recognition for language understanding,two considerable challenges persist in this field:(a)limited and common gestures are considered,(b)processing multiple channels of information across a network takes huge computational time during discriminative feature extraction.Therefore,a novel hand vision-based convolutional neural network(CNN)model named(HVCNNM)offers several benefits,notably enhanced accuracy,robustness to variations,real-time performance,reduced channels,and scalability.Additionally,these models can be optimized for real-time performance,learn from large amounts of data,and are scalable to handle complex recognition tasks for efficient human-computer interaction.The proposed model was evaluated on two challenging datasets,namely the Massey University Dataset(MUD)and the American Sign Language(ASL)Alphabet Dataset(ASLAD).On the MUD and ASLAD datasets,HVCNNM achieved a score of 99.23% and 99.00%,respectively.These results demonstrate the effectiveness of CNN as a promising HGRoc approach.The findings suggest that the proposed model have potential roles in applications such as sign language recognition,human-computer interaction,and robotics.
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.
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.
基金Supported by The Wu Jieping Medical Foundation,No.320.6750.18456.
文摘BACKGROUND Several studies have reported that the walking trail making test(WTMT)completion time is significantly higher in patients with developmental coordination disorders and mild cognitive impairments.We hypothesized that WTMT performance would be altered in older adults with white matter hyperintensities(WMH).AIM To explore the performance in the WTMT in older people with WMH.METHODS In this single-center,observational study,25 elderly WMH patients admitted to our hospital from June 2019 to June 2020 served as the WMH group and 20 participants matched for age,gender,and educational level who were undergoing physical examination in our hospital during the same period served as the control group.The participants completed the WTMT-A and WTMT-B to obtain their gait parameters,including WTMT-A completion time,WTMT-B completion time,speed,step length,cadence,and stance phase percent.White matter lesions were scored according to the Fazekas scale.Multiple neuropsychological assessments were carried out to assess cognitive function.The relationships between WTMT performance and cognition and motion in elderly patients with WMH were analyzed by partial Pearson correlation analysis.RESULTS Patients with WMH performed significantly worse on the choice reaction test(CRT)(0.51±0.09 s vs 0.44±0.06 s,P=0.007),verbal fluency test(VFT,14.2±2.75 vs 16.65±3.54,P=0.012),and digit symbol substitution test(16.00±2.75 vs 18.40±3.27,P=0.010)than participants in the control group.The WMH group also required significantly more time to complete the WTMT-A(93.00±10.76 s vs 70.55±11.28 s,P<0.001)and WTMT-B(109.72±12.26 s vs 82.85±7.90 s,P<0.001).WTMT-A completion time was positively correlated with CRT time(r=0.460,P=0.001),while WTMT-B completion time was negatively correlated with VFT(r=-0.391,P=0.008).On the WTMT-A,only speed was found to statistically differ between the WMH and control groups(0.803±0.096 vs 0.975±0.050 m/s,P<0.001),whereas on the WTMT-B,the WMH group exhibited a significantly lower speed(0.778±0.111 vs 0.970±0.053 m/s,P<0.001)and cadence(82.600±4.140 vs 85.500±5.020 steps/m,P=0.039),as well as a higher stance phase percentage(65.061±1.813%vs 63.513±2.465%,P=0.019)relative to controls.CONCLUSION Older adults with WMH showed obviously poorer WTMT performance.WTMT could be a potential indicator for cognitive and motor deficits in patients with WMH.
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.
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 investigate the efficacy and safety of low-frequency repetitive transcranial magnetic stimulation(rTMS)for the treatment of lower limb motor dysfunction after stroke.Methods:A total of 96 patients with stroke and lower limb motor dysfunction were enrolled in this study,and were randomly divided into the experimental group and the sham stimulation group using the method of calculator-generated random numbers.Both groups received conventional medication and rehabilitation therapy.The experimental group received 4 weeks of 1 Hz rTMS treatment in the primary cortical motor area(M1)of the healthy side,with the treatment coil tangent to the skull surface;the sham stimulation group underwent the same procedures as the experimental group,but the treatment coil was perpendicular to the skull surface instead.Lower-extremity subscale of the Fugl-Meyer Assessment(FMA-LE),Berg Balance Scale(BBS),gait analysis,and lower-extremity surface electromyography(LESEM)were performed in both groups before and after rTMS treatment.Results:All 96 patients completed the test with no shedding and no adverse reactions.After treatment,the FMA-LE score and BBS score of the 2 groups of patients were significantly improved as compared with the pre-treatment(P<0.05),and the TUG test time was reduced as compared with the pre-treatment(P<0.05).The true stimulation group had greater improvement in all assessment indexes than that of the sham stimulation group(P<0.05).After treatment,the electromyographic activity of the tibialis anterior and rectus femoris muscles in the true simulation group improved significantly.The step length,step speed,and step frequency were also significantly improved in both groups after treatment,and the symmetrical ratio of step length and support time was reduced(P<0.05).Comparison between the groups revealed that the true simulation group significantly improved after rTMS treatment as compared to the sham stimulation group(P<0.05).Conclusion:1Hz rTMS treatment safely and effectively improved motor and balance function in patients with post-stroke lower limb motor dysfunction.
