Brain machine interfaces (BMIs) have demonstrated lots of successful arm-related reach decoding in past decades, which provide a new hope for restoring the lost motor functions for the disabled. On the other hand, the...Brain machine interfaces (BMIs) have demonstrated lots of successful arm-related reach decoding in past decades, which provide a new hope for restoring the lost motor functions for the disabled. On the other hand, the more sophisticated hand grasp movement, which is more fundamental and crucial for daily life, was less referred. Current state of arts has specified some grasp related brain areas and offline decoding results; however, online decoding grasp movement and real-time neuroprosthetic control have not been systematically investigated. In this study, we obtained neural data from the dorsal premotor cortex (PMd) when monkey reaching and grasping one of four differently shaped objects following visual cues. The four grasp gesture types with an additional resting state were classified asynchronously using a fuzzy k-nearest neighbor model, and an artificial hand was controlled online using a shared control strategy. The results showed that most of the neurons in PMd are tuned by reach and grasp movement, us- ing which we get a high average offline decoding accuracy of 97.1%. In the online demonstration, the instantaneous status of monkey grasping could be extracted successfully to control the artificial hand, with an event-wise accuracy of 85.1%. Overall, our results inspect the neural firing along the time course of grasp and for the first time enables asynchronous neural control of a prosthetic hand, which underline a feasible hand neural prosthesis in BMIs.展开更多
A five-fingered,multi-sensory and biomimetic hand is presented.The cambered palm is specially designed by utilizing the knowledge of anatomy.The position of each finger is arranged according to human hand skeleton.Eac...A five-fingered,multi-sensory and biomimetic hand is presented.The cambered palm is specially designed by utilizing the knowledge of anatomy.The position of each finger is arranged according to human hand skeleton.Each finger with three phalanges could fulfill flexion-extension movement independently.All the fingers are designed using coupling link mechanism.The location of the thumb is designed by maximizing interaction area between the thumb and other fingers.The opposite thumb could grasp along a cone surface,while maintaining its function.The hardware architecture is divided into control system and human-machine interaction system.The mechanical parts,sensors and motion control systems are integrated in the hand structure.In addition,a skin-like glove is designed,which makes the hand more humanlike.According to our primary experimental results,the hand can accomplish several grasp modes by applying an intuitive surface electromyography control scheme.The success rate of 10 modes is up to 90%.展开更多
Dynamic hand gesture recognition is a desired alternative means for human-computer interactions.This paper presents a hand gesture recognition system that is designed for the control of flights of unmanned aerial vehi...Dynamic hand gesture recognition is a desired alternative means for human-computer interactions.This paper presents a hand gesture recognition system that is designed for the control of flights of unmanned aerial vehicles(UAV).A data representation model that represents a dynamic gesture sequence by converting the 4-D spatiotemporal data to 2-D matrix and a 1-D array is introduced.To train the system to recognize designed gestures,skeleton data collected from a Leap Motion Controller are converted to two different data models.As many as 9124 samples of the training dataset,1938 samples of the testing dataset are created to train and test the proposed three deep learning neural networks,which are a 2-layer fully connected neural network,a 5-layer fully connected neural network and an 8-layer convolutional neural network.The static testing results show that the 2-layer fully connected neural network achieves an average accuracy of 96.7%on scaled datasets and 12.3%on non-scaled datasets.The 5-layer fully connected neural network achieves an average accuracy of 98.0%on scaled datasets and 89.1%on non-scaled datasets.The 8-layer convolutional neural network achieves an average accuracy of 89.6%on scaled datasets and 96.9%on non-scaled datasets.Testing on a drone-kit simulator and a real drone shows that this system is feasible for drone flight controls.展开更多
Voluntary participation of hemiplegic patients is crucial for functional electrical stimulation therapy.A wearable functional electrical stimulation system has been proposed for real-time volitional hand motor functio...Voluntary participation of hemiplegic patients is crucial for functional electrical stimulation therapy.A wearable functional electrical stimulation system has been proposed for real-time volitional hand motor function control using the electromyography bridge method.Through a series of novel design concepts,including the integration of a detecting circuit and an analog-to-digital converter,a miniaturized functional electrical stimulation circuit technique,a low-power super-regeneration chip for wireless receiving,and two wearable armbands,a prototype system has been established with reduced size,power,and overall cost.Based on wrist joint torque reproduction and classification experiments performed on six healthy subjects,the optimized surface electromyography thresholds and trained logistic regression classifier parameters were statistically chosen to establish wrist and hand motion control with high accuracy.Test results showed that wrist flexion/extension,hand grasp,and finger extension could be reproduced with high accuracy and low latency.This system can build a bridge of information transmission between healthy limbs and paralyzed limbs,effectively improve voluntary participation of hemiplegic patients,and elevate efficiency of rehabilitation training.展开更多
The dynamics properties of a kind of multi-fingered robot hand is analyzed. It is pointed out that the dynamics property of this kind of multifingered robot hand in the approaching process is quite different from that...The dynamics properties of a kind of multi-fingered robot hand is analyzed. It is pointed out that the dynamics property of this kind of multifingered robot hand in the approaching process is quite different from that in the grasping process and,different control algorithm should be taken in the two process. A position-force hybrid control algorithm is proposed which is applied to the control system of the University of Science and Technology Beijing double-thumb robot hand successfully.展开更多
Presents major achievements in researches on coordinated control with multifingered robot hands by first briefing the present status of researches on multifingered robot hands, then discussing the coordinated control ...Presents major achievements in researches on coordinated control with multifingered robot hands by first briefing the present status of researches on multifingered robot hands, then discussing the coordinated control with multifingered robot hands, and finally exploring the way of achieving autonomous grasp, and thoughts on future researches.展开更多
A model-free set-point tracking control approach of multi-fingered robot hand is presented.The set-point tracking controller,which has the structural form of PD controller,is composed with a combination of feedforward...A model-free set-point tracking control approach of multi-fingered robot hand is presented.The set-point tracking controller,which has the structural form of PD controller,is composed with a combination of feedforward term,feedback term and saturation control term.The controller does not require the explicit use of dynamic modeling parameters.Experiments performed on the HIT/DLR hand demonstrate the effectiveness of the proposed approach in performance improvement and real-time application.展开更多
According to the sampling statistics there are over 7 millions limb disabled persons in China from several times of those in the world. For the benefit to the amputees, thousands varies kinds of commencial Products of...According to the sampling statistics there are over 7 millions limb disabled persons in China from several times of those in the world. For the benefit to the amputees, thousands varies kinds of commencial Products of artificial hands, by scientific promotion have ben developed in the recent half century. Among those products the EMG controlling artificial upper limb brings the hope to the amputees. The later are now used widely form the earlest one in 1948.In 1978, Shanghai Jiao Tong University began to study and develop the EMG controlling artificial band mounted to amputes over thousand disabled during a couple of recent decades.The risidual muscles of an amputee are the signal source of the artificial hand controlled by EMG. The evoked EMG which can transmit the brain moving information is one of the bioelectricities from human body. The EMG signal, accumulated at skin surface with surface electrodes, passing through filtering and amplifying circuits controls the movement-this is the main principle of EMG controlling artificial hand.But, owing to the weakness of EMG (μv) and a group of muscles information plus the strong turbulence of electric field (v), the integrated EMG can’t completely reflect the brain moving act and will influence the accuracy of EMG-hand, especially those of the multi-multi-degree of freedom.In 1978, only 57% of the controlling aaccuracy of artificial hand with 3-degree of freedom could be reached by the Herbert’s research. In 80’s, the controlling accuracy raised up to 72% by Denning’s new method. Up to now, the accuracy is still not ideal, eventhrogh the Hi-tech of using pattern-recognitionand artincial neuro-net work. The electronic artificial hand will be considered successful and practical only with the moving accuracy more than 95%.Some research by using implant electrode for detecting the neuro-information or EEG controllingmethod met also dimculties for raising the accuracy of artificial hand.For breaking througll the threshold of accuracy limit, the EMG method as mentioned above must bechanged entirely, A newest creative research work on the electronic artificial hand controlled by a "regenerated finger" made by transplanting a toe to the stump is developing in Shanghai Jiao TongUniversity, which is without precedent in the world.The first experimental amputee using "regenerated finger’ to control an electronic artificial forearm with 3-degree of freedom reaches 100% accuracy of movements (i.e. no error within 100 tests). It has been proved that the use of a "regenerated finger" as a controlling signal command makes it possible to use the electronic artificeal hand with multi-degree of freedom without error Thecombining medical science with engineering in the area of designing an electronic artifical upper limb.Acknowledgement: The authors extend their hearty thanks to the famous academician Dr.Chen Zhongwei (Zhong-Sen Hospital) for their creative effort and successful micro-surgical operation for transplanting toe to stump of an amputee, also to the China Science Foundation for supporting. us the fund to develop this research.展开更多
In this article, the transmission dynamics of a Hand-Foot-Mouth disease model with treatment and vaccination interventions are studied. We calculated the basic reproduction number and proved the global stability of di...In this article, the transmission dynamics of a Hand-Foot-Mouth disease model with treatment and vaccination interventions are studied. We calculated the basic reproduction number and proved the global stability of disease-free equilibrium when R0 R0 > 1. Meanwhile, we obtained the optimal control strategies minimizing the cost of intervention and minimizing the infected person. We also give some numerical simulations to verify our theoretical results.展开更多
为了减小配电网带电作业的人身安全风险,降低电力系统的运维成本,文中设计了一种面向配电网作业的半人形智能机器人系统,包括硬件结构和控制系统设计。不同于绝缘杆作业法,该系统通过佩戴数据手套和腕部红外追踪器等多模态可穿戴设备来...为了减小配电网带电作业的人身安全风险,降低电力系统的运维成本,文中设计了一种面向配电网作业的半人形智能机器人系统,包括硬件结构和控制系统设计。不同于绝缘杆作业法,该系统通过佩戴数据手套和腕部红外追踪器等多模态可穿戴设备来捕捉人体动作和作业细节,并采用动态运动基元(dynamic movement primitives, DMP)将人体数据映射到半人形机器人的机械臂和末端灵巧手来进行配网作业。测试结果表明:所设计的半人形机器人系统能够稳定跟踪人体演示细节。在模拟配电网线路中可以完成多种作业功能,作业实验成功率可达88.9%。展开更多
In order to overcome the drawbacks of traditional rehabilitation method,the robot-aided rehabilitation has been widely investigated for the recent years.And the hand rehabilitation robot,as one of the hot research fie...In order to overcome the drawbacks of traditional rehabilitation method,the robot-aided rehabilitation has been widely investigated for the recent years.And the hand rehabilitation robot,as one of the hot research fields,remains many challenging issues to be investigated.This paper presents a new hand exoskeleton system with some novel characteristics.Firstly,both active and passive rehabilitative motions are realized.Secondly,the device is elaborately designed and brings advantages in many aspects.For example,joint motion is accomplished by a parallelogram mechanism and high level motion control is therefore made very simple without the need of complicated kinematics.The adjustable joint limit design ensures that the actual joint angles don＇t exceed the joint range of motion（ROM） and thus the patient safety is guaranteed.This design can fit to the different patients with different joint ROM as well as to the dynamically changing ROM for individual patient.The device can also accommodate to some extent variety of hand sizes.Thirdly,the proposed control strategy simultaneously realizes the position control and force control with the motor driver which only works in force control mode.Meanwhile,the system resistance compensation is preliminary realized and the resisting force is effectively reduced.Some experiments were conducted to verify the proposed system.Experimentally collected data show that the achieved ROM is close to that of a healthy hand and the range of phalange length（ROPL） covers the size of a typical hand,satisfying the size need of regular hand rehabilitation.In order to evaluate the performance when it works as a haptic device in active mode,the equivalent moment of inertia（MOI） of the device was calculated.The results prove that the device has low inertia which is critical in order to obtain good backdrivability.The experiments also show that in the active mode the virtual interactive force is successfully feedback to the finger and the resistance is reduced by one-third;for the passive control mode,the desired trajectory is realized satisfactorily.展开更多
基金supported by the National Natural Science Foundation of China (61031002, 61001172)National High Technology Research and Development Program of China (2012AA011602, 2011CB504400)the Zhejiang Provincial Natural Science Foundation of China (Y2090707)
文摘Brain machine interfaces (BMIs) have demonstrated lots of successful arm-related reach decoding in past decades, which provide a new hope for restoring the lost motor functions for the disabled. On the other hand, the more sophisticated hand grasp movement, which is more fundamental and crucial for daily life, was less referred. Current state of arts has specified some grasp related brain areas and offline decoding results; however, online decoding grasp movement and real-time neuroprosthetic control have not been systematically investigated. In this study, we obtained neural data from the dorsal premotor cortex (PMd) when monkey reaching and grasping one of four differently shaped objects following visual cues. The four grasp gesture types with an additional resting state were classified asynchronously using a fuzzy k-nearest neighbor model, and an artificial hand was controlled online using a shared control strategy. The results showed that most of the neurons in PMd are tuned by reach and grasp movement, us- ing which we get a high average offline decoding accuracy of 97.1%. In the online demonstration, the instantaneous status of monkey grasping could be extracted successfully to control the artificial hand, with an event-wise accuracy of 85.1%. Overall, our results inspect the neural firing along the time course of grasp and for the first time enables asynchronous neural control of a prosthetic hand, which underline a feasible hand neural prosthesis in BMIs.
基金the National Natural Science Foundation of China(No.50435040)the National High Technology Research and Development Program (863) of China (No.2008AA04Z203)
文摘A five-fingered,multi-sensory and biomimetic hand is presented.The cambered palm is specially designed by utilizing the knowledge of anatomy.The position of each finger is arranged according to human hand skeleton.Each finger with three phalanges could fulfill flexion-extension movement independently.All the fingers are designed using coupling link mechanism.The location of the thumb is designed by maximizing interaction area between the thumb and other fingers.The opposite thumb could grasp along a cone surface,while maintaining its function.The hardware architecture is divided into control system and human-machine interaction system.The mechanical parts,sensors and motion control systems are integrated in the hand structure.In addition,a skin-like glove is designed,which makes the hand more humanlike.According to our primary experimental results,the hand can accomplish several grasp modes by applying an intuitive surface electromyography control scheme.The success rate of 10 modes is up to 90%.
文摘Dynamic hand gesture recognition is a desired alternative means for human-computer interactions.This paper presents a hand gesture recognition system that is designed for the control of flights of unmanned aerial vehicles(UAV).A data representation model that represents a dynamic gesture sequence by converting the 4-D spatiotemporal data to 2-D matrix and a 1-D array is introduced.To train the system to recognize designed gestures,skeleton data collected from a Leap Motion Controller are converted to two different data models.As many as 9124 samples of the training dataset,1938 samples of the testing dataset are created to train and test the proposed three deep learning neural networks,which are a 2-layer fully connected neural network,a 5-layer fully connected neural network and an 8-layer convolutional neural network.The static testing results show that the 2-layer fully connected neural network achieves an average accuracy of 96.7%on scaled datasets and 12.3%on non-scaled datasets.The 5-layer fully connected neural network achieves an average accuracy of 98.0%on scaled datasets and 89.1%on non-scaled datasets.The 8-layer convolutional neural network achieves an average accuracy of 89.6%on scaled datasets and 96.9%on non-scaled datasets.Testing on a drone-kit simulator and a real drone shows that this system is feasible for drone flight controls.
基金supported by the National Natural Science Foundation of China,No.90307013,90707005,61534003the Science&Technology Pillar Program of Jiangsu Province in China,No.BE2013706
文摘Voluntary participation of hemiplegic patients is crucial for functional electrical stimulation therapy.A wearable functional electrical stimulation system has been proposed for real-time volitional hand motor function control using the electromyography bridge method.Through a series of novel design concepts,including the integration of a detecting circuit and an analog-to-digital converter,a miniaturized functional electrical stimulation circuit technique,a low-power super-regeneration chip for wireless receiving,and two wearable armbands,a prototype system has been established with reduced size,power,and overall cost.Based on wrist joint torque reproduction and classification experiments performed on six healthy subjects,the optimized surface electromyography thresholds and trained logistic regression classifier parameters were statistically chosen to establish wrist and hand motion control with high accuracy.Test results showed that wrist flexion/extension,hand grasp,and finger extension could be reproduced with high accuracy and low latency.This system can build a bridge of information transmission between healthy limbs and paralyzed limbs,effectively improve voluntary participation of hemiplegic patients,and elevate efficiency of rehabilitation training.
文摘The dynamics properties of a kind of multi-fingered robot hand is analyzed. It is pointed out that the dynamics property of this kind of multifingered robot hand in the approaching process is quite different from that in the grasping process and,different control algorithm should be taken in the two process. A position-force hybrid control algorithm is proposed which is applied to the control system of the University of Science and Technology Beijing double-thumb robot hand successfully.
文摘Presents major achievements in researches on coordinated control with multifingered robot hands by first briefing the present status of researches on multifingered robot hands, then discussing the coordinated control with multifingered robot hands, and finally exploring the way of achieving autonomous grasp, and thoughts on future researches.
基金Sponsored by the Program for New Century Excellent Talents in University (Grant No:NCET-09-0056)the National High Technology Research and Development Program of China (Grant No.2009AA043803)
文摘A model-free set-point tracking control approach of multi-fingered robot hand is presented.The set-point tracking controller,which has the structural form of PD controller,is composed with a combination of feedforward term,feedback term and saturation control term.The controller does not require the explicit use of dynamic modeling parameters.Experiments performed on the HIT/DLR hand demonstrate the effectiveness of the proposed approach in performance improvement and real-time application.
文摘According to the sampling statistics there are over 7 millions limb disabled persons in China from several times of those in the world. For the benefit to the amputees, thousands varies kinds of commencial Products of artificial hands, by scientific promotion have ben developed in the recent half century. Among those products the EMG controlling artificial upper limb brings the hope to the amputees. The later are now used widely form the earlest one in 1948.In 1978, Shanghai Jiao Tong University began to study and develop the EMG controlling artificial band mounted to amputes over thousand disabled during a couple of recent decades.The risidual muscles of an amputee are the signal source of the artificial hand controlled by EMG. The evoked EMG which can transmit the brain moving information is one of the bioelectricities from human body. The EMG signal, accumulated at skin surface with surface electrodes, passing through filtering and amplifying circuits controls the movement-this is the main principle of EMG controlling artificial hand.But, owing to the weakness of EMG (μv) and a group of muscles information plus the strong turbulence of electric field (v), the integrated EMG can’t completely reflect the brain moving act and will influence the accuracy of EMG-hand, especially those of the multi-multi-degree of freedom.In 1978, only 57% of the controlling aaccuracy of artificial hand with 3-degree of freedom could be reached by the Herbert’s research. In 80’s, the controlling accuracy raised up to 72% by Denning’s new method. Up to now, the accuracy is still not ideal, eventhrogh the Hi-tech of using pattern-recognitionand artincial neuro-net work. The electronic artificial hand will be considered successful and practical only with the moving accuracy more than 95%.Some research by using implant electrode for detecting the neuro-information or EEG controllingmethod met also dimculties for raising the accuracy of artificial hand.For breaking througll the threshold of accuracy limit, the EMG method as mentioned above must bechanged entirely, A newest creative research work on the electronic artificial hand controlled by a "regenerated finger" made by transplanting a toe to the stump is developing in Shanghai Jiao TongUniversity, which is without precedent in the world.The first experimental amputee using "regenerated finger’ to control an electronic artificial forearm with 3-degree of freedom reaches 100% accuracy of movements (i.e. no error within 100 tests). It has been proved that the use of a "regenerated finger" as a controlling signal command makes it possible to use the electronic artificeal hand with multi-degree of freedom without error Thecombining medical science with engineering in the area of designing an electronic artifical upper limb.Acknowledgement: The authors extend their hearty thanks to the famous academician Dr.Chen Zhongwei (Zhong-Sen Hospital) for their creative effort and successful micro-surgical operation for transplanting toe to stump of an amputee, also to the China Science Foundation for supporting. us the fund to develop this research.
文摘In this article, the transmission dynamics of a Hand-Foot-Mouth disease model with treatment and vaccination interventions are studied. We calculated the basic reproduction number and proved the global stability of disease-free equilibrium when R0 R0 > 1. Meanwhile, we obtained the optimal control strategies minimizing the cost of intervention and minimizing the infected person. We also give some numerical simulations to verify our theoretical results.
文摘为了减小配电网带电作业的人身安全风险,降低电力系统的运维成本,文中设计了一种面向配电网作业的半人形智能机器人系统,包括硬件结构和控制系统设计。不同于绝缘杆作业法,该系统通过佩戴数据手套和腕部红外追踪器等多模态可穿戴设备来捕捉人体动作和作业细节,并采用动态运动基元(dynamic movement primitives, DMP)将人体数据映射到半人形机器人的机械臂和末端灵巧手来进行配网作业。测试结果表明:所设计的半人形机器人系统能够稳定跟踪人体演示细节。在模拟配电网线路中可以完成多种作业功能,作业实验成功率可达88.9%。
基金supported by National Natural Science Foundation of China (Grant No. 50975009)
文摘In order to overcome the drawbacks of traditional rehabilitation method,the robot-aided rehabilitation has been widely investigated for the recent years.And the hand rehabilitation robot,as one of the hot research fields,remains many challenging issues to be investigated.This paper presents a new hand exoskeleton system with some novel characteristics.Firstly,both active and passive rehabilitative motions are realized.Secondly,the device is elaborately designed and brings advantages in many aspects.For example,joint motion is accomplished by a parallelogram mechanism and high level motion control is therefore made very simple without the need of complicated kinematics.The adjustable joint limit design ensures that the actual joint angles don＇t exceed the joint range of motion（ROM） and thus the patient safety is guaranteed.This design can fit to the different patients with different joint ROM as well as to the dynamically changing ROM for individual patient.The device can also accommodate to some extent variety of hand sizes.Thirdly,the proposed control strategy simultaneously realizes the position control and force control with the motor driver which only works in force control mode.Meanwhile,the system resistance compensation is preliminary realized and the resisting force is effectively reduced.Some experiments were conducted to verify the proposed system.Experimentally collected data show that the achieved ROM is close to that of a healthy hand and the range of phalange length（ROPL） covers the size of a typical hand,satisfying the size need of regular hand rehabilitation.In order to evaluate the performance when it works as a haptic device in active mode,the equivalent moment of inertia（MOI） of the device was calculated.The results prove that the device has low inertia which is critical in order to obtain good backdrivability.The experiments also show that in the active mode the virtual interactive force is successfully feedback to the finger and the resistance is reduced by one-third;for the passive control mode,the desired trajectory is realized satisfactorily.
