Gait coordination in lower limbs plays a critical role in maintaining stability of the human body during walking.For transfemoral amputees,the absence of limbs disrupts this coordination,reducing prosthesis control ac...Gait coordination in lower limbs plays a critical role in maintaining stability of the human body during walking.For transfemoral amputees,the absence of limbs disrupts this coordination,reducing prosthesis control accuracy.Hip-knee coordination mapping offers a feasible solution for lower-limb prosthesis control,involving the generation of a reference trajectory for the knee joint by leveraging information from the hip.However,current reference trajectories are usually derived from static models,which cannot generate reference trajectories robustly when dealing with perturbations.Therefore,this paper introduces a time-dependent model based on the Delayed Feedback Reservoir(DFR)for hip-knee coordination in lower-limb prosthetic control.Experimental results show that DFR outperforms classical gait planning approaches when facing perturbations,achieving a 20%lower Root Mean Square Error(RMSE)and reducing residuals by up to 18.14 degrees.This research contributes to understanding gait mapping approaches and emphasizes the potential of time-dependent models for robust and strong lower-limb prosthetic control.The discovery provides a novel way to enhance the perturbation adaptability of prosthetic control.展开更多
Purpose: Although proximal stability of the trunk is a prerequisite for balance and gait, to determine the role of trunk rehabilitation on trunk control, balance and gait in patients with chronic stroke is yet unknown...Purpose: Although proximal stability of the trunk is a prerequisite for balance and gait, to determine the role of trunk rehabilitation on trunk control, balance and gait in patients with chronic stroke is yet unknown. Method: Fifteen sub-jects (post-stroke duration (3.53 ± 2.98) years) who had the ability to walk 10 meters independently with or without a walking aid;scoring ≤ 21 on Trunk Impairment Scale (TIS), participated in a selective trunk muscle exercise regime, consisting of 45 minutes training per day, four days a week, and for four weeks duration in an outpatient stroke reha-bilitation centre. Results: The overall effect size index for trunk rehabilitation was 1.07. This study showed large effect size index for Trunk Impairment Scale (1.75), Berg Balance Scale (1.65) than for gait variables (0.65). After trunk rehabilitation, there was a significant improvement for gait speed (p= 0.015), cadence (p= 0.001) and gait symmetry (p=0.019) in patients with chronic stroke. In addition, all the spatial gait parameters had a significant change post-intervention. There was no significant change in temporal gait parameters with the exception of affected single limb support time. The level of significance was set at p < 0.05. Conclusion: The exercises consisted of selective trunk movement of the upper and the lower part of trunk had shown larger effect size index for trunk control and balance than for gait in patients with chronic stroke. Future randomized controlled studies incorporating large sample size would provide insight into the effectiveness and clinical relevance of this intervention.展开更多
We present a method for designing free gaits for a structurally symmetrical quadruped robot capable of performing statically stable, omnidirectional walking on irregular terrain. The robot＇s virtual model is construc...We present a method for designing free gaits for a structurally symmetrical quadruped robot capable of performing statically stable, omnidirectional walking on irregular terrain. The robot＇s virtual model is constructed and a control algorithm is proposed by applying virtual components at some strategic locations. The deliberative-based controller can generate flexible sequences of leg transferences while maintaining walking speed, and choose optimum foothold for moving leg based on integration data of exteroceptive terrain profile. Simulation results are presented to show the gait＇s efficiency and system＇s stability in adapting to an uncertain terrain.展开更多
As a typical rhythmic movement, human being＇s rhythmic gait movement can be generated by a central pattern generator （CPG） located in a spinal cord by self- oscillation. Some kinds of gait movements are caused by g...As a typical rhythmic movement, human being＇s rhythmic gait movement can be generated by a central pattern generator （CPG） located in a spinal cord by self- oscillation. Some kinds of gait movements are caused by gait frequency and amplitude variances. As an important property of human being＇s motion vision, the attention selection mechanism plays a vital part in the regulation of gait movement. In this paper, the CPG model is amended under the condition of attention selection on the theoretical basis of Matsuoka neural oscillators. Regulation of attention selection signal for the CPG model parameters and structure is studied, which consequentially causes the frequency and amplitude changes of gait movement output. Further, the control strategy of the CPG model gait movement under the condition of attention selection is discussed, showing that the attention selection model can regulate the output model of CPG gait movement in three different ways. The realization of regulation on the gait movement frequency and amplitude shows a variety of regulation on the CPG gait movement made by attention selection and enriches the controllability of CPG gait movement, which demonstrates potential influence in engineering applications.展开更多
目的:通过网状Meta分析整合直接与间接证据,比较不同非侵入性脑刺激技术及参数对帕金森病患者步态和平衡功能的影响,并排序最佳干预方案。方法:检索CNKI、万方、维普、CBM、PubMed、Cochrane图书馆、EMbase和Web of Science数据库,筛选...目的:通过网状Meta分析整合直接与间接证据,比较不同非侵入性脑刺激技术及参数对帕金森病患者步态和平衡功能的影响,并排序最佳干预方案。方法:检索CNKI、万方、维普、CBM、PubMed、Cochrane图书馆、EMbase和Web of Science数据库,筛选有关非侵入性脑刺激改善帕金森病患者步态和平衡障碍的随机对照试验,检索时限截止到2025-06-16。对纳入的研究进行数据提取,采用RevMan 5.4.1软件和Stata 17.0软件进行统计学处理。结果:①纳入47篇研究,共2767例患者,试验组1399例、对照组1368例;②传统Meta分析结果显示,高频重复经颅磁刺激可以降低统一帕金森病评定量表第三部分(UPDRSⅢ)评分、冻结步态问卷(FOG-Q)评分,缩短起立-行走计时试验(TUGT)时间,增加步长,改善步速,提高Berg平衡量表评分,且均优于常规治疗(P<0.05);经颅直流电刺激可以降低冻结步态问卷评分、缩短起立-行走计时试验时间,增加步长,改善步速,提高Berg平衡量表评分,且均优于常规治疗(P<0.05);低频重复经颅磁刺激可以降低统一帕金森病评定量表第三部分评分,与常规治疗比较有显著性差异(P<0.05);3种脑刺激方法对于步频的改善均无统计学意义(P>0.05),受限于研究数量少,需进一步验证;③网状Meta分析结果显示(以下排序均基于间接比较),在降低统一帕金森评定量表第三部分评分方面:高频重复经颅磁刺激选择初级运动皮质区(M1)+背外侧前额叶皮质区(DLPFC)双侧靶点联合刺激的累积概率排序最高(95.2%),在初级运动皮质区上刺激排序次之(72.5%);在缩短起立-行走计时试验时间方面:高频重复经颅磁刺激在背外侧前额叶皮质区刺激的累积概率排序最高(85.5%),在初级运动皮质区上刺激排序次之(69.0%);在改善步速方面:高频重复经颅磁刺激在背外侧前额叶皮质区的累积概率排序最高(92.5%),在初级运动皮质区上刺激排序次之(76.7%);在提高Berg平衡量表评分方面:高频重复经颅磁刺激在初级运动皮质区上刺激的累积概率排序最高(79.9%),经颅直流电刺激在小脑上刺激排序次之(79.8%);④GRADE证据质量评价结果显示,统一帕金森评定量表第三部分、冻结步态问卷评分、起立-行走计时试验、步长证据等级为中级,步速、步频、Berg平衡量表评分为低级。结论:不同类型非侵入性脑刺激都可以改善帕金森病患者的步态和平衡功能。背外侧前额叶皮质区靶向的高频重复经颅磁刺激对步态功能的改善优于初级运动皮质(中等证据),而初级运动皮质靶向的高频重复经颅磁刺激对平衡功能的改善优于小脑靶向的经颅直流电刺激(低级证据)。展开更多
Dynamically adapt to uneven ground locomotion is a crucial ability for humanoid robots utilized in human environments.However,because of the effect of current pattern generation method,adapting to unknown rough ground...Dynamically adapt to uneven ground locomotion is a crucial ability for humanoid robots utilized in human environments.However,because of the effect of current pattern generation method,adapting to unknown rough ground is limited.Moreover,to maintain large support region by four-point contact during the landing phase is usually a key problem.In order to solve these problems,a landing phase control and online pattern generation in three dimensional environments is proposed.On the basis of robot-environment non-planar interactive modes,a method of landing control based on optimal support region is put forward to realize stable four-point contact by flexible foot,and a controller is employed to adapt to the changes of ground without using prior knowledge.Furthermore,an adaptable foothold planning is put forward to the online pattern generation considering walking speed,uneven terrain,and the effect of lateral movement to the locomotion stability.Finally,the effectiveness of landing control and online pattern generation is demonstrated by dynamic simulations and real robot walking experiments on outdoor uneven ground.The results indicate that the robot kept its balance even though the ground is unknown and irregular.The proposed methods lay a foundation for studies of humanoid robots performing tasks in complex environments.展开更多
This study aimed to investigate the effects of exercise-induced muscle fatigue in the unaffected knee joint on postural control and kinematic changes in stroke patients. Forty participants（20 stroke patients, 20 age-...This study aimed to investigate the effects of exercise-induced muscle fatigue in the unaffected knee joint on postural control and kinematic changes in stroke patients. Forty participants（20 stroke patients, 20 age-matched healthy participants） were recruited. To induce fatigue, maximum voluntary isometric contractions were performed in the unaffected knee joint in a Leg Extension Rehab exercise machine using the pneumatic resistance. We measured static and dynamic balance and lower-limb kinematics during gait. Changes in postural control parameters anteroposterior sway speed and total center of pressure distance differed significantly between the stroke and control groups. In addition, changes in gait kinematic parameters knee and ankle angles of initial contact differed significantly between stroke（paretic and non-paretic） and control groups. Muscle fatigue in the unaffected knee and ankle impaired postural control and debilitates kinematic movement of ipsilateral and contralateral lower limbs, and may place the fatigued stroke patients at greater risk for falls.展开更多
A gait control method for a biped robot based on the deep Q-network (DQN) algorithm is proposed to enhance the stability of walking on uneven ground. This control strategy is an intelligent learning method of posture ...A gait control method for a biped robot based on the deep Q-network (DQN) algorithm is proposed to enhance the stability of walking on uneven ground. This control strategy is an intelligent learning method of posture adjustment. A robot is taken as an agent and trained to walk steadily on an uneven surface with obstacles, using a simple reward function based on forward progress. The reward-punishment (RP) mechanism of the DQN algorithm is established after obtaining the offline gait which was generated in advance foot trajectory planning. Instead of implementing a complex dynamic model, the proposed method enables the biped robot to learn to adjust its posture on the uneven ground and ensures walking stability. The performance and effectiveness of the proposed algorithm was validated in the V-REP simulation environment. The results demonstrate that the biped robot's lateral tile angle is less than 3° after implementing the proposed method and the walking stability is obviously improved.展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.12372065,12372022,and 11932015)Shanghai Pilot Program for Basic Research—Fudan University(Grant No.21TQ1400100-22TQ009).
文摘Gait coordination in lower limbs plays a critical role in maintaining stability of the human body during walking.For transfemoral amputees,the absence of limbs disrupts this coordination,reducing prosthesis control accuracy.Hip-knee coordination mapping offers a feasible solution for lower-limb prosthesis control,involving the generation of a reference trajectory for the knee joint by leveraging information from the hip.However,current reference trajectories are usually derived from static models,which cannot generate reference trajectories robustly when dealing with perturbations.Therefore,this paper introduces a time-dependent model based on the Delayed Feedback Reservoir(DFR)for hip-knee coordination in lower-limb prosthetic control.Experimental results show that DFR outperforms classical gait planning approaches when facing perturbations,achieving a 20%lower Root Mean Square Error(RMSE)and reducing residuals by up to 18.14 degrees.This research contributes to understanding gait mapping approaches and emphasizes the potential of time-dependent models for robust and strong lower-limb prosthetic control.The discovery provides a novel way to enhance the perturbation adaptability of prosthetic control.
文摘Purpose: Although proximal stability of the trunk is a prerequisite for balance and gait, to determine the role of trunk rehabilitation on trunk control, balance and gait in patients with chronic stroke is yet unknown. Method: Fifteen sub-jects (post-stroke duration (3.53 ± 2.98) years) who had the ability to walk 10 meters independently with or without a walking aid;scoring ≤ 21 on Trunk Impairment Scale (TIS), participated in a selective trunk muscle exercise regime, consisting of 45 minutes training per day, four days a week, and for four weeks duration in an outpatient stroke reha-bilitation centre. Results: The overall effect size index for trunk rehabilitation was 1.07. This study showed large effect size index for Trunk Impairment Scale (1.75), Berg Balance Scale (1.65) than for gait variables (0.65). After trunk rehabilitation, there was a significant improvement for gait speed (p= 0.015), cadence (p= 0.001) and gait symmetry (p=0.019) in patients with chronic stroke. In addition, all the spatial gait parameters had a significant change post-intervention. There was no significant change in temporal gait parameters with the exception of affected single limb support time. The level of significance was set at p < 0.05. Conclusion: The exercises consisted of selective trunk movement of the upper and the lower part of trunk had shown larger effect size index for trunk control and balance than for gait in patients with chronic stroke. Future randomized controlled studies incorporating large sample size would provide insight into the effectiveness and clinical relevance of this intervention.
基金supported by the Science and Technology Innovation Fund for the Doctor
文摘We present a method for designing free gaits for a structurally symmetrical quadruped robot capable of performing statically stable, omnidirectional walking on irregular terrain. The robot＇s virtual model is constructed and a control algorithm is proposed by applying virtual components at some strategic locations. The deliberative-based controller can generate flexible sequences of leg transferences while maintaining walking speed, and choose optimum foothold for moving leg based on integration data of exteroceptive terrain profile. Simulation results are presented to show the gait＇s efficiency and system＇s stability in adapting to an uncertain terrain.
基金supported by the National Natural Science Foundation of China(Nos.11232005 and11472104)the Doctoral Fund of Ministry of Education of China(No.20120074110020)
文摘As a typical rhythmic movement, human being＇s rhythmic gait movement can be generated by a central pattern generator （CPG） located in a spinal cord by self- oscillation. Some kinds of gait movements are caused by gait frequency and amplitude variances. As an important property of human being＇s motion vision, the attention selection mechanism plays a vital part in the regulation of gait movement. In this paper, the CPG model is amended under the condition of attention selection on the theoretical basis of Matsuoka neural oscillators. Regulation of attention selection signal for the CPG model parameters and structure is studied, which consequentially causes the frequency and amplitude changes of gait movement output. Further, the control strategy of the CPG model gait movement under the condition of attention selection is discussed, showing that the attention selection model can regulate the output model of CPG gait movement in three different ways. The realization of regulation on the gait movement frequency and amplitude shows a variety of regulation on the CPG gait movement made by attention selection and enriches the controllability of CPG gait movement, which demonstrates potential influence in engineering applications.
文摘目的:通过网状Meta分析整合直接与间接证据,比较不同非侵入性脑刺激技术及参数对帕金森病患者步态和平衡功能的影响,并排序最佳干预方案。方法:检索CNKI、万方、维普、CBM、PubMed、Cochrane图书馆、EMbase和Web of Science数据库,筛选有关非侵入性脑刺激改善帕金森病患者步态和平衡障碍的随机对照试验,检索时限截止到2025-06-16。对纳入的研究进行数据提取,采用RevMan 5.4.1软件和Stata 17.0软件进行统计学处理。结果:①纳入47篇研究,共2767例患者,试验组1399例、对照组1368例;②传统Meta分析结果显示,高频重复经颅磁刺激可以降低统一帕金森病评定量表第三部分(UPDRSⅢ)评分、冻结步态问卷(FOG-Q)评分,缩短起立-行走计时试验(TUGT)时间,增加步长,改善步速,提高Berg平衡量表评分,且均优于常规治疗(P<0.05);经颅直流电刺激可以降低冻结步态问卷评分、缩短起立-行走计时试验时间,增加步长,改善步速,提高Berg平衡量表评分,且均优于常规治疗(P<0.05);低频重复经颅磁刺激可以降低统一帕金森病评定量表第三部分评分,与常规治疗比较有显著性差异(P<0.05);3种脑刺激方法对于步频的改善均无统计学意义(P>0.05),受限于研究数量少,需进一步验证;③网状Meta分析结果显示(以下排序均基于间接比较),在降低统一帕金森评定量表第三部分评分方面:高频重复经颅磁刺激选择初级运动皮质区(M1)+背外侧前额叶皮质区(DLPFC)双侧靶点联合刺激的累积概率排序最高(95.2%),在初级运动皮质区上刺激排序次之(72.5%);在缩短起立-行走计时试验时间方面:高频重复经颅磁刺激在背外侧前额叶皮质区刺激的累积概率排序最高(85.5%),在初级运动皮质区上刺激排序次之(69.0%);在改善步速方面:高频重复经颅磁刺激在背外侧前额叶皮质区的累积概率排序最高(92.5%),在初级运动皮质区上刺激排序次之(76.7%);在提高Berg平衡量表评分方面:高频重复经颅磁刺激在初级运动皮质区上刺激的累积概率排序最高(79.9%),经颅直流电刺激在小脑上刺激排序次之(79.8%);④GRADE证据质量评价结果显示,统一帕金森评定量表第三部分、冻结步态问卷评分、起立-行走计时试验、步长证据等级为中级,步速、步频、Berg平衡量表评分为低级。结论:不同类型非侵入性脑刺激都可以改善帕金森病患者的步态和平衡功能。背外侧前额叶皮质区靶向的高频重复经颅磁刺激对步态功能的改善优于初级运动皮质(中等证据),而初级运动皮质靶向的高频重复经颅磁刺激对平衡功能的改善优于小脑靶向的经颅直流电刺激(低级证据)。
基金supported by National Natural Science Foundation of China (Grant No. 50775008)the PhD Programs Foundation of Ministry of Education of China (Grant No. 200800061019)Hubei provincial Digital Manufacturing Key Laboratory Foundation of China (Grant No.SZ0602)
文摘Dynamically adapt to uneven ground locomotion is a crucial ability for humanoid robots utilized in human environments.However,because of the effect of current pattern generation method,adapting to unknown rough ground is limited.Moreover,to maintain large support region by four-point contact during the landing phase is usually a key problem.In order to solve these problems,a landing phase control and online pattern generation in three dimensional environments is proposed.On the basis of robot-environment non-planar interactive modes,a method of landing control based on optimal support region is put forward to realize stable four-point contact by flexible foot,and a controller is employed to adapt to the changes of ground without using prior knowledge.Furthermore,an adaptable foothold planning is put forward to the online pattern generation considering walking speed,uneven terrain,and the effect of lateral movement to the locomotion stability.Finally,the effectiveness of landing control and online pattern generation is demonstrated by dynamic simulations and real robot walking experiments on outdoor uneven ground.The results indicate that the robot kept its balance even though the ground is unknown and irregular.The proposed methods lay a foundation for studies of humanoid robots performing tasks in complex environments.
文摘This study aimed to investigate the effects of exercise-induced muscle fatigue in the unaffected knee joint on postural control and kinematic changes in stroke patients. Forty participants（20 stroke patients, 20 age-matched healthy participants） were recruited. To induce fatigue, maximum voluntary isometric contractions were performed in the unaffected knee joint in a Leg Extension Rehab exercise machine using the pneumatic resistance. We measured static and dynamic balance and lower-limb kinematics during gait. Changes in postural control parameters anteroposterior sway speed and total center of pressure distance differed significantly between the stroke and control groups. In addition, changes in gait kinematic parameters knee and ankle angles of initial contact differed significantly between stroke（paretic and non-paretic） and control groups. Muscle fatigue in the unaffected knee and ankle impaired postural control and debilitates kinematic movement of ipsilateral and contralateral lower limbs, and may place the fatigued stroke patients at greater risk for falls.
基金Supported by the National Ministries and Research Funds(3020020221111)
文摘A gait control method for a biped robot based on the deep Q-network (DQN) algorithm is proposed to enhance the stability of walking on uneven ground. This control strategy is an intelligent learning method of posture adjustment. A robot is taken as an agent and trained to walk steadily on an uneven surface with obstacles, using a simple reward function based on forward progress. The reward-punishment (RP) mechanism of the DQN algorithm is established after obtaining the offline gait which was generated in advance foot trajectory planning. Instead of implementing a complex dynamic model, the proposed method enables the biped robot to learn to adjust its posture on the uneven ground and ensures walking stability. The performance and effectiveness of the proposed algorithm was validated in the V-REP simulation environment. The results demonstrate that the biped robot's lateral tile angle is less than 3° after implementing the proposed method and the walking stability is obviously improved.
