Guokun Zuo | Chinese Academy of Sciences (original) (raw)
Papers by Guokun Zuo
2nd International Conference on Artificial Intelligence, Automation, and High-Performance Computing (AIAHPC 2022)
Machines
The recovery treatment of motor dysfunction plays a crucial role in rehabilitation therapy. Rehab... more The recovery treatment of motor dysfunction plays a crucial role in rehabilitation therapy. Rehabilitation robots are partially or fully replacing therapists in assisting patients in exercise by advantage of robot technologies. However, the rehabilitation training system is not yet intelligent enough to provide suitable exercise modes based on the exercise intentions of patients with different motor abilities. In this paper, a dual-modal hybrid self-switching control strategy (DHSS) is proposed to automatically determine the exercise mode of patients, i.e., passive and assistive exercise mode. In this strategy, the potential field method and the ADRC position control are employed to plan trajectories and assist patients’ training. Dual-modal self-switching rules based on the motor and impulse information of patients are presented to identify patients’ motor abilities. Finally, the DHSS assisted five subjects in performing the training with an average deviation error of less than 2 m...
IEEE Sensors Journal, 2022
2020 International Conference on Computer Engineering and Intelligent Control (ICCEIC), 2020
Myoelectric interface offers a promising tool for detecting motion intention and extent of moveme... more Myoelectric interface offers a promising tool for detecting motion intention and extent of movement effort. However, how to achieve motion intention recognition accurately and fast using electromyography (EMG) is an important issue. Many studies present great recognition accuracy, while there is few studies focus on motion recognition speed improvement through exploring motion trend (micro motion) decoding, which is of key importance for the online control strategy of rehabilitation robot. In this paper, we explored the performance of machine learning algorithm in micro motion recognition. The performance of support vector machine (SVM) model was tested for five upper-limb micro motions. As a result, the SVM-based model provides satisfying online performance across all the subjects and motions, achieving an accuracy of 89.7±3.9 % and a total motion recognition time of 0.74±0.08 s. The results show that machine learning algorithm combined with EMG technology can provide accurate and fast upper-limb micro motion intention recognition.
Machines, 2022
Robotic-assisted rehabilitation therapy has been shown to be effective in improving upper limb mo... more Robotic-assisted rehabilitation therapy has been shown to be effective in improving upper limb motor function and the daily behavior of patients with motor dysfunction. At present, the majority of upper limb rehabilitation robots can only move in the two-dimensional plane, and cannot adjust the assistance mode in real-time according to the patient’s rehabilitation needs. In this paper, according to the shortcomings of the current rehabilitation robot only moving in the two-dimensional plane, a type of bilateral mirror upper limb rehabilitation robot structure with the healthy side assisting the affected side is proposed. This can move in three-dimensional space. Additionally, an assist-as-needed (AAN) control strategy for upper limb rehabilitation training is proposed based on the bilateral upper limb rehabilitation robot. The control strategy adopts Gaussian Mixture Model (GMM) and impedance controller to maximize the patient’s rehabilitation effect. In the task’s design, there is ...
Machines, 2022
Medical titanium alloys are widely used in surgery, orthopedics, stomatology and other medical sp... more Medical titanium alloys are widely used in surgery, orthopedics, stomatology and other medical specialties because of their good biocompatibility. In traditional rigid internal fixation applications, titanium alloy strips or plates must be bent to fit the supported surface. Currently, the common practice is to bend titanium alloy bars in three degrees of freedom manually. However, it is difficult to ensure bending accuracy and achieve the best shape. In this study, we introduce a forming robot for internally fixed titanium alloy strips (FRIFTAS). The forming robot is a device that automatically reshapes the titanium strip with various specifications according to medical needs. Here, the design of mechanical and electrical systems and the development of the overall system are described to illustrate how a FRIFTAS is structured and designed. Three bending experimental tests are conducted. In the bending experiments, the robot bends an initial strip on the roll, pitch and yaw direction...
2017 IEEE International Conference on Cybernetics and Intelligent Systems (CIS) and IEEE Conference on Robotics, Automation and Mechatronics (RAM), 2017
The most of patients who have suffered a stroke experience upper limb impairments, making stroke ... more The most of patients who have suffered a stroke experience upper limb impairments, making stroke the leading cause of adult disability. Robot-assisted task-specific training, which is an effective method to improve the performance of action, focuses on learning or relearning a motor skill. Circle-drawing with a robot together are not only beneficial as an adjunct to task-specific training and strengthening upper limb muscles, but also a part of the clinical evaluation protocols. In order to let the robot provide individuals effective prescriptions of rehabilitation settings to achieve precision rehabilitation for post-stroke patients, the acquirement and analysis of characteristics of upper limb muscles during the robot-assisted circle drawing rehabilitation training are most important. The surface EMG is presented and applied to characterize the development of upper limb muscles during motor rehabilitation. The experiment is carried out under the condition of normal people is guided by rehabilitation robot drive upper limb drawing accurate circle in passive mode. It found that the muscle tension of different upper limb muscles changed regularly during circle drawing with the rehabilitation robot guidance, which provides important theoretical basis for making more effective training plans and steers upper limb motor function for stroke rehabilitation.
Computational Intelligence and Neuroscience, 2021
In the research of motor imagery brain-computer interface (MI-BCI), traditional electroencephalog... more In the research of motor imagery brain-computer interface (MI-BCI), traditional electroencephalogram (EEG) signal recognition algorithms appear to be inefficient in extracting EEG signal features and improving classification accuracy. In this paper, we discuss a solution to this problem based on a novel step-by-step method of feature extraction and pattern classification for multiclass MI-EEG signals. First, the training data from all subjects is merged and enlarged through autoencoder to meet the need for massive amounts of data while reducing the bad effect on signal recognition because of randomness, instability, and individual variability of EEG data. Second, an end-to-end sharing structure with attention-based time-incremental shallow convolution neural network is proposed. Shallow convolution neural network (SCNN) and bidirectional long short-term memory (BiLSTM) network are used to extract frequency-spatial domain features and time-series features of EEG signals, respectively...
Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi, 2020
In order to stimulate the patients' active participation in the process of robot-assisted reh... more In order to stimulate the patients' active participation in the process of robot-assisted rehabilitation training of stroke patients, the rehabilitation robots should provide assistant torque to patients according to their rehabilitation needs. This paper proposed an assist-as-needed control strategy for wrist rehabilitation robots. Firstly, the ability evaluation rules were formulated and the patient's ability was evaluated according to the rules. Then the controller was designed. Based on the evaluation results, the controller can calculate the assistant torque needed by the patient to complete the rehabilitation training task and send commands to motor. Finally, the motor is controlled to output the commanded value, which assists the patient to complete the rehabilitation training task. The control strategy was implemented to the wrist function rehabilitation robot, which could achieve the training effect of assist-as-needed and could avoid the surge of assistance torque....
Sensors (Basel, Switzerland), 2021
In this paper, we present a novel muscle synergy extraction method based on multivariate curve re... more In this paper, we present a novel muscle synergy extraction method based on multivariate curve resolution–alternating least squares (MCR-ALS) to overcome the limitation of the nonnegative matrix factorization (NMF) method for extracting non-sparse muscle synergy, and we study its potential application for evaluating motor function of stroke survivors. Nonnegative matrix factorization (NMF) is the most widely used method for muscle synergy extraction. However, NMF is susceptible to components’ sparseness and usually provides inferior reliability, which significantly limits the promotion of muscle synergy. In this study, MCR-ALS was employed to extract muscle synergy from electromyography (EMG) data. Its performance was compared with two other matrix factorization algorithms, NMF and self-modeling mixture analysis (SMMA). Simulated data sets were utilized to explore the influences of the sparseness and noise on the extracted synergies. As a result, the synergies estimated by MCR-ALS w...
A fault tolerant steer-by-wire (SBW) system requires an operation procedure to cope with partial ... more A fault tolerant steer-by-wire (SBW) system requires an operation procedure to cope with partial system degradations. This paper presents a reliability quantification method that converts the operation procedure into an augmented Markov transition diagram where each state represents either a normal SBW, or a partially degraded or a completely failed SBW. The system reliability is quantified in terms of the state probabilities calculated from a numerical integration of the Markov diagram specified by component failure rates. A structural design was already proposed and an example of operation procedure was derived in our previous study for a SBW system consisting of a principal SBW, a standby SBW and a mechanical backup hopefully with a power assist feature. The proposed method is demonstrated by an application to this SBW design. It turns out that the SBW system demonstrates a considerably high reliability through the introduction of mechanical backup. The power assist, however, is ...
A front Steer-by-Wire (SBW) vehicle does not have conventional mechanical linkage; an actuator su... more A front Steer-by-Wire (SBW) vehicle does not have conventional mechanical linkage; an actuator such as a brushless motor exclusively powers the front steering gear, and the steering wheel is an interface between the driver and the vehicle controller. The SBW vehicles have good prospects of innovative driveability. The performance depends on the vehicle controller that commands the front steer angle according to driver's input. By the use of D* controller that the authors have developed, for instance, the center of gravity (CG) of SBW vehicle promptly follows a trajectory intended by the driver. The SBW system requires an interface that corresponds to the steering wheel for conventional steering vehicle. Challenging problems will be found concerning the structure and the function of such interfaces. A variety of driver models have been proposed so far for the conventional steering vehicles for numerical simulation and theoretical analysis. These models cannot be applied to the SB...
Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi, 2018
Brain-computer interface (BCI) technology enable humans to interact with external devices by deco... more Brain-computer interface (BCI) technology enable humans to interact with external devices by decoding their brain signals. Despite it has made some significant breakthroughs in recent years, there are still many obstacles in its applications and extensions. The current used BCI control signals are generally derived from the brain areas involved in primary sensory- or motor-related processing. However, these signals only reflect a limited range of limb movement intention. Therefore, additional sources of brain signals for controlling BCI systems need to be explored. Brain signals derived from the cognitive brain areas are more intuitive and effective. These signals can be used for expand the brain signal sources as a new approach. This paper reviewed the research status of cognitive BCI based on the single brain area and multiple hybrid brain areas, and summarized its applications in the rehabilitation medicine. It's believed that cognitive BCI technologies would become a possibl...
Neuroscience Letters, 2021
Rhythmic visual cues are beneficial in gait initiation (GI) in Parkinson's disease patients w... more Rhythmic visual cues are beneficial in gait initiation (GI) in Parkinson's disease patients with freezing of gait (FOG), however, the underlying neurophysiological mechanism remains poorly understood. The cognitive control modulated by visual cues during GI has been investigated and considered as a potential factor influencing automatic motor actions, but it is unclear how rhythmic visual cues affect cognitive resources demands during GI. The purpose of this study was to explore the effect of rhythmic visual cues on cognitive resources allocation by recording the anticipatory cerebral cortex electroencephalographic (EEG) activity during GI. Twenty healthy participants initiated gait in response to the rhythmic and non-rhythmic visual cues of stimulus presentation. We assessed the contingent negative variation (CNV) of averaged EEG data over 32 electrode positions during GI preparation, the results of which showed that the CNV was induced over prefrontal, frontal, central, and pa...
E3S Web of Conferences, 2021
Muscle synergy is an important approach to evaluate motor function for patients with neurological... more Muscle synergy is an important approach to evaluate motor function for patients with neurological diseases. Nonnegative matrix factorization (NMF) is the most widely used muscle synergy extraction method from electromyography (EMG) data. However, NMF usually falls into local optimum and is susceptible to noise, which significantly limit the promotion of muscle synergy. In this paper, a reliable synergy extraction method based on multivariate curve resolution-alternating least squares (MCRALS) was put forward. Its performance was compared with NMF through analyzing the EMG data of upper limb motor. The repeatability and intra-subject consistency were used to evaluate the two methods. As a result, MCR-ALS provided unique resolution result and better repeatability and consistency in contrast to NMF. Thus, the results of this study are of significance for the expansion and application of muscle synergy in medicine.
International Journal of Advanced Robotic Systems, 2020
Based on evidence from the previous research in rehabilitation robot control strategies, we found... more Based on evidence from the previous research in rehabilitation robot control strategies, we found that the common feature of the effective control strategies to promote subjects’ engagement is creating a reward–punishment feedback mechanism. This article proposes a reward–punishment feedback control strategy based on energy information. Firstly, an engagement estimated approach based on energy information is developed to evaluate subjects’ performance. Secondly, the estimated result forms a reward–punishment term, which is introduced into a standard model-based adaptive controller. This modified adaptive controller is capable of giving the reward–punishment feedback to subjects according to their engagement. Finally, several experiments are implemented using a wrist rehabilitation robot to evaluate the proposed control strategy with 10 healthy subjects who have not cardiovascular and cerebrovascular diseases. The results of these experiments show that the mean coefficient of determi...
IEEE Sensors Journal, 2017
Reasonable stress and strain distribution are essential for the design of six-axis force/torque s... more Reasonable stress and strain distribution are essential for the design of six-axis force/torque sensors. In order to improve the strain distribution, the specific parameters which affect stress and strain distribution need to be found. The numerical solutions of stress and strain on the elastic beam of six-axis force/torque sensors can be quickly obtained by finite element analysis simulation tool, such as ANSYS, but the specific parameters which affect stress and strain distribution cannot be achieved. In this paper, a novel six-axis force/torque sensor scheme with small size and cross beam structure was presented. Then, the mechanical model and analytic equations based on Timoshenko beam theory were established to obtain the analytical solutions of strain. The comparison shows that the analytical solutions and numerical solutions are in good agreement, which indicates that the analytical method is feasible. Finally, the main parameters which affect the strain value and the measure accuracy were analyzed. The analysis results show that the design of six-axis force/torque sensors with cross beam structure can be optimized according to the parameters that affect the stress and strain distribution, if sufficient restrictions are offered. Index Terms-Six-axis force/torque sensors, Timoshenko beam theory, strain analysis, analytical and numerical solutions, optimal solution of structure. I. INTRODUCTION A CQUISITION of multi-dimensional force information is one of the most important senses for intelligent robots. Six-axis force/torque sensors can detect the full force information of three-dimensional space of the robot simultaneously, i.e., three force components: Fx, Fy, Fz and three torque components:Mx, My, Mz of three spatial coordinate axes. As a result, they are the essential parts to improve the intelligence and manipulative level of robots [1]. Such sensors are now widely used for force/torque senses of robots control in various occasions, such as zero force teaching [2], automatic flexible assembly [3], robots multi-hand cooperation [4], robot teleoperation system [5], [6], robotic surgery and rehabilitation training [7], etc.
International Journal of Advanced Robotic Systems, 2019
In human robot interaction systems, human intent detection plays an important role to improve the... more In human robot interaction systems, human intent detection plays an important role to improve the interactive performances and then the rehabilitation effects. A study is proposed to estimate the interactive forces that indirectly detect the human motion intent. A disturbance observer is designed to estimate interactive torques and friction forces without force sensors, and then a friction force model is constructed to estimate the friction force in the robot system. To detect the human–robot interaction force, we subtract the friction force from disturbance observer estimation result. Several experiments were performed to test the performances of the proposed methods. Those methods were applied in an end-effect upper limb rehabilitation robot system. The results show that the precision of the estimated sensor force can increase 5% than the force sensor. The senseless force estimation method we proposed in this article can be an alternative option in force control tasks when force s...
Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi, 2016
Aiming at feature selection problem of motor imagery task in brain computer interface(BCI),an alg... more Aiming at feature selection problem of motor imagery task in brain computer interface(BCI),an algorithm based on mutual information and principal component analysis(PCA)for electroencephalogram(EEG)feature selection is presented.This algorithm introduces the category information,and uses the sum of mutual information matrices between features under different motor imagery category to replace the covariance matrix.The eigenvectors of the sum matrix represent the direction of the principal components and the eigenvalues of the sum matrix are used to determine the dimensionality of principal components.2005 International BCI competition data set was used in our experiments,and four feature extraction methods were adopted,i.e.power spectrum estimation,continuous wavelet transform,wavelet packet decomposition and Hjorth parameters.The proposed feature selection algorithm was adopted to select and combine the most useful features for classification.The results showed that relative to the ...
2nd International Conference on Artificial Intelligence, Automation, and High-Performance Computing (AIAHPC 2022)
Machines
The recovery treatment of motor dysfunction plays a crucial role in rehabilitation therapy. Rehab... more The recovery treatment of motor dysfunction plays a crucial role in rehabilitation therapy. Rehabilitation robots are partially or fully replacing therapists in assisting patients in exercise by advantage of robot technologies. However, the rehabilitation training system is not yet intelligent enough to provide suitable exercise modes based on the exercise intentions of patients with different motor abilities. In this paper, a dual-modal hybrid self-switching control strategy (DHSS) is proposed to automatically determine the exercise mode of patients, i.e., passive and assistive exercise mode. In this strategy, the potential field method and the ADRC position control are employed to plan trajectories and assist patients’ training. Dual-modal self-switching rules based on the motor and impulse information of patients are presented to identify patients’ motor abilities. Finally, the DHSS assisted five subjects in performing the training with an average deviation error of less than 2 m...
IEEE Sensors Journal, 2022
2020 International Conference on Computer Engineering and Intelligent Control (ICCEIC), 2020
Myoelectric interface offers a promising tool for detecting motion intention and extent of moveme... more Myoelectric interface offers a promising tool for detecting motion intention and extent of movement effort. However, how to achieve motion intention recognition accurately and fast using electromyography (EMG) is an important issue. Many studies present great recognition accuracy, while there is few studies focus on motion recognition speed improvement through exploring motion trend (micro motion) decoding, which is of key importance for the online control strategy of rehabilitation robot. In this paper, we explored the performance of machine learning algorithm in micro motion recognition. The performance of support vector machine (SVM) model was tested for five upper-limb micro motions. As a result, the SVM-based model provides satisfying online performance across all the subjects and motions, achieving an accuracy of 89.7±3.9 % and a total motion recognition time of 0.74±0.08 s. The results show that machine learning algorithm combined with EMG technology can provide accurate and fast upper-limb micro motion intention recognition.
Machines, 2022
Robotic-assisted rehabilitation therapy has been shown to be effective in improving upper limb mo... more Robotic-assisted rehabilitation therapy has been shown to be effective in improving upper limb motor function and the daily behavior of patients with motor dysfunction. At present, the majority of upper limb rehabilitation robots can only move in the two-dimensional plane, and cannot adjust the assistance mode in real-time according to the patient’s rehabilitation needs. In this paper, according to the shortcomings of the current rehabilitation robot only moving in the two-dimensional plane, a type of bilateral mirror upper limb rehabilitation robot structure with the healthy side assisting the affected side is proposed. This can move in three-dimensional space. Additionally, an assist-as-needed (AAN) control strategy for upper limb rehabilitation training is proposed based on the bilateral upper limb rehabilitation robot. The control strategy adopts Gaussian Mixture Model (GMM) and impedance controller to maximize the patient’s rehabilitation effect. In the task’s design, there is ...
Machines, 2022
Medical titanium alloys are widely used in surgery, orthopedics, stomatology and other medical sp... more Medical titanium alloys are widely used in surgery, orthopedics, stomatology and other medical specialties because of their good biocompatibility. In traditional rigid internal fixation applications, titanium alloy strips or plates must be bent to fit the supported surface. Currently, the common practice is to bend titanium alloy bars in three degrees of freedom manually. However, it is difficult to ensure bending accuracy and achieve the best shape. In this study, we introduce a forming robot for internally fixed titanium alloy strips (FRIFTAS). The forming robot is a device that automatically reshapes the titanium strip with various specifications according to medical needs. Here, the design of mechanical and electrical systems and the development of the overall system are described to illustrate how a FRIFTAS is structured and designed. Three bending experimental tests are conducted. In the bending experiments, the robot bends an initial strip on the roll, pitch and yaw direction...
2017 IEEE International Conference on Cybernetics and Intelligent Systems (CIS) and IEEE Conference on Robotics, Automation and Mechatronics (RAM), 2017
The most of patients who have suffered a stroke experience upper limb impairments, making stroke ... more The most of patients who have suffered a stroke experience upper limb impairments, making stroke the leading cause of adult disability. Robot-assisted task-specific training, which is an effective method to improve the performance of action, focuses on learning or relearning a motor skill. Circle-drawing with a robot together are not only beneficial as an adjunct to task-specific training and strengthening upper limb muscles, but also a part of the clinical evaluation protocols. In order to let the robot provide individuals effective prescriptions of rehabilitation settings to achieve precision rehabilitation for post-stroke patients, the acquirement and analysis of characteristics of upper limb muscles during the robot-assisted circle drawing rehabilitation training are most important. The surface EMG is presented and applied to characterize the development of upper limb muscles during motor rehabilitation. The experiment is carried out under the condition of normal people is guided by rehabilitation robot drive upper limb drawing accurate circle in passive mode. It found that the muscle tension of different upper limb muscles changed regularly during circle drawing with the rehabilitation robot guidance, which provides important theoretical basis for making more effective training plans and steers upper limb motor function for stroke rehabilitation.
Computational Intelligence and Neuroscience, 2021
In the research of motor imagery brain-computer interface (MI-BCI), traditional electroencephalog... more In the research of motor imagery brain-computer interface (MI-BCI), traditional electroencephalogram (EEG) signal recognition algorithms appear to be inefficient in extracting EEG signal features and improving classification accuracy. In this paper, we discuss a solution to this problem based on a novel step-by-step method of feature extraction and pattern classification for multiclass MI-EEG signals. First, the training data from all subjects is merged and enlarged through autoencoder to meet the need for massive amounts of data while reducing the bad effect on signal recognition because of randomness, instability, and individual variability of EEG data. Second, an end-to-end sharing structure with attention-based time-incremental shallow convolution neural network is proposed. Shallow convolution neural network (SCNN) and bidirectional long short-term memory (BiLSTM) network are used to extract frequency-spatial domain features and time-series features of EEG signals, respectively...
Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi, 2020
In order to stimulate the patients' active participation in the process of robot-assisted reh... more In order to stimulate the patients' active participation in the process of robot-assisted rehabilitation training of stroke patients, the rehabilitation robots should provide assistant torque to patients according to their rehabilitation needs. This paper proposed an assist-as-needed control strategy for wrist rehabilitation robots. Firstly, the ability evaluation rules were formulated and the patient's ability was evaluated according to the rules. Then the controller was designed. Based on the evaluation results, the controller can calculate the assistant torque needed by the patient to complete the rehabilitation training task and send commands to motor. Finally, the motor is controlled to output the commanded value, which assists the patient to complete the rehabilitation training task. The control strategy was implemented to the wrist function rehabilitation robot, which could achieve the training effect of assist-as-needed and could avoid the surge of assistance torque....
Sensors (Basel, Switzerland), 2021
In this paper, we present a novel muscle synergy extraction method based on multivariate curve re... more In this paper, we present a novel muscle synergy extraction method based on multivariate curve resolution–alternating least squares (MCR-ALS) to overcome the limitation of the nonnegative matrix factorization (NMF) method for extracting non-sparse muscle synergy, and we study its potential application for evaluating motor function of stroke survivors. Nonnegative matrix factorization (NMF) is the most widely used method for muscle synergy extraction. However, NMF is susceptible to components’ sparseness and usually provides inferior reliability, which significantly limits the promotion of muscle synergy. In this study, MCR-ALS was employed to extract muscle synergy from electromyography (EMG) data. Its performance was compared with two other matrix factorization algorithms, NMF and self-modeling mixture analysis (SMMA). Simulated data sets were utilized to explore the influences of the sparseness and noise on the extracted synergies. As a result, the synergies estimated by MCR-ALS w...
A fault tolerant steer-by-wire (SBW) system requires an operation procedure to cope with partial ... more A fault tolerant steer-by-wire (SBW) system requires an operation procedure to cope with partial system degradations. This paper presents a reliability quantification method that converts the operation procedure into an augmented Markov transition diagram where each state represents either a normal SBW, or a partially degraded or a completely failed SBW. The system reliability is quantified in terms of the state probabilities calculated from a numerical integration of the Markov diagram specified by component failure rates. A structural design was already proposed and an example of operation procedure was derived in our previous study for a SBW system consisting of a principal SBW, a standby SBW and a mechanical backup hopefully with a power assist feature. The proposed method is demonstrated by an application to this SBW design. It turns out that the SBW system demonstrates a considerably high reliability through the introduction of mechanical backup. The power assist, however, is ...
A front Steer-by-Wire (SBW) vehicle does not have conventional mechanical linkage; an actuator su... more A front Steer-by-Wire (SBW) vehicle does not have conventional mechanical linkage; an actuator such as a brushless motor exclusively powers the front steering gear, and the steering wheel is an interface between the driver and the vehicle controller. The SBW vehicles have good prospects of innovative driveability. The performance depends on the vehicle controller that commands the front steer angle according to driver's input. By the use of D* controller that the authors have developed, for instance, the center of gravity (CG) of SBW vehicle promptly follows a trajectory intended by the driver. The SBW system requires an interface that corresponds to the steering wheel for conventional steering vehicle. Challenging problems will be found concerning the structure and the function of such interfaces. A variety of driver models have been proposed so far for the conventional steering vehicles for numerical simulation and theoretical analysis. These models cannot be applied to the SB...
Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi, 2018
Brain-computer interface (BCI) technology enable humans to interact with external devices by deco... more Brain-computer interface (BCI) technology enable humans to interact with external devices by decoding their brain signals. Despite it has made some significant breakthroughs in recent years, there are still many obstacles in its applications and extensions. The current used BCI control signals are generally derived from the brain areas involved in primary sensory- or motor-related processing. However, these signals only reflect a limited range of limb movement intention. Therefore, additional sources of brain signals for controlling BCI systems need to be explored. Brain signals derived from the cognitive brain areas are more intuitive and effective. These signals can be used for expand the brain signal sources as a new approach. This paper reviewed the research status of cognitive BCI based on the single brain area and multiple hybrid brain areas, and summarized its applications in the rehabilitation medicine. It's believed that cognitive BCI technologies would become a possibl...
Neuroscience Letters, 2021
Rhythmic visual cues are beneficial in gait initiation (GI) in Parkinson's disease patients w... more Rhythmic visual cues are beneficial in gait initiation (GI) in Parkinson's disease patients with freezing of gait (FOG), however, the underlying neurophysiological mechanism remains poorly understood. The cognitive control modulated by visual cues during GI has been investigated and considered as a potential factor influencing automatic motor actions, but it is unclear how rhythmic visual cues affect cognitive resources demands during GI. The purpose of this study was to explore the effect of rhythmic visual cues on cognitive resources allocation by recording the anticipatory cerebral cortex electroencephalographic (EEG) activity during GI. Twenty healthy participants initiated gait in response to the rhythmic and non-rhythmic visual cues of stimulus presentation. We assessed the contingent negative variation (CNV) of averaged EEG data over 32 electrode positions during GI preparation, the results of which showed that the CNV was induced over prefrontal, frontal, central, and pa...
E3S Web of Conferences, 2021
Muscle synergy is an important approach to evaluate motor function for patients with neurological... more Muscle synergy is an important approach to evaluate motor function for patients with neurological diseases. Nonnegative matrix factorization (NMF) is the most widely used muscle synergy extraction method from electromyography (EMG) data. However, NMF usually falls into local optimum and is susceptible to noise, which significantly limit the promotion of muscle synergy. In this paper, a reliable synergy extraction method based on multivariate curve resolution-alternating least squares (MCRALS) was put forward. Its performance was compared with NMF through analyzing the EMG data of upper limb motor. The repeatability and intra-subject consistency were used to evaluate the two methods. As a result, MCR-ALS provided unique resolution result and better repeatability and consistency in contrast to NMF. Thus, the results of this study are of significance for the expansion and application of muscle synergy in medicine.
International Journal of Advanced Robotic Systems, 2020
Based on evidence from the previous research in rehabilitation robot control strategies, we found... more Based on evidence from the previous research in rehabilitation robot control strategies, we found that the common feature of the effective control strategies to promote subjects’ engagement is creating a reward–punishment feedback mechanism. This article proposes a reward–punishment feedback control strategy based on energy information. Firstly, an engagement estimated approach based on energy information is developed to evaluate subjects’ performance. Secondly, the estimated result forms a reward–punishment term, which is introduced into a standard model-based adaptive controller. This modified adaptive controller is capable of giving the reward–punishment feedback to subjects according to their engagement. Finally, several experiments are implemented using a wrist rehabilitation robot to evaluate the proposed control strategy with 10 healthy subjects who have not cardiovascular and cerebrovascular diseases. The results of these experiments show that the mean coefficient of determi...
IEEE Sensors Journal, 2017
Reasonable stress and strain distribution are essential for the design of six-axis force/torque s... more Reasonable stress and strain distribution are essential for the design of six-axis force/torque sensors. In order to improve the strain distribution, the specific parameters which affect stress and strain distribution need to be found. The numerical solutions of stress and strain on the elastic beam of six-axis force/torque sensors can be quickly obtained by finite element analysis simulation tool, such as ANSYS, but the specific parameters which affect stress and strain distribution cannot be achieved. In this paper, a novel six-axis force/torque sensor scheme with small size and cross beam structure was presented. Then, the mechanical model and analytic equations based on Timoshenko beam theory were established to obtain the analytical solutions of strain. The comparison shows that the analytical solutions and numerical solutions are in good agreement, which indicates that the analytical method is feasible. Finally, the main parameters which affect the strain value and the measure accuracy were analyzed. The analysis results show that the design of six-axis force/torque sensors with cross beam structure can be optimized according to the parameters that affect the stress and strain distribution, if sufficient restrictions are offered. Index Terms-Six-axis force/torque sensors, Timoshenko beam theory, strain analysis, analytical and numerical solutions, optimal solution of structure. I. INTRODUCTION A CQUISITION of multi-dimensional force information is one of the most important senses for intelligent robots. Six-axis force/torque sensors can detect the full force information of three-dimensional space of the robot simultaneously, i.e., three force components: Fx, Fy, Fz and three torque components:Mx, My, Mz of three spatial coordinate axes. As a result, they are the essential parts to improve the intelligence and manipulative level of robots [1]. Such sensors are now widely used for force/torque senses of robots control in various occasions, such as zero force teaching [2], automatic flexible assembly [3], robots multi-hand cooperation [4], robot teleoperation system [5], [6], robotic surgery and rehabilitation training [7], etc.
International Journal of Advanced Robotic Systems, 2019
In human robot interaction systems, human intent detection plays an important role to improve the... more In human robot interaction systems, human intent detection plays an important role to improve the interactive performances and then the rehabilitation effects. A study is proposed to estimate the interactive forces that indirectly detect the human motion intent. A disturbance observer is designed to estimate interactive torques and friction forces without force sensors, and then a friction force model is constructed to estimate the friction force in the robot system. To detect the human–robot interaction force, we subtract the friction force from disturbance observer estimation result. Several experiments were performed to test the performances of the proposed methods. Those methods were applied in an end-effect upper limb rehabilitation robot system. The results show that the precision of the estimated sensor force can increase 5% than the force sensor. The senseless force estimation method we proposed in this article can be an alternative option in force control tasks when force s...
Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi, 2016
Aiming at feature selection problem of motor imagery task in brain computer interface(BCI),an alg... more Aiming at feature selection problem of motor imagery task in brain computer interface(BCI),an algorithm based on mutual information and principal component analysis(PCA)for electroencephalogram(EEG)feature selection is presented.This algorithm introduces the category information,and uses the sum of mutual information matrices between features under different motor imagery category to replace the covariance matrix.The eigenvectors of the sum matrix represent the direction of the principal components and the eigenvalues of the sum matrix are used to determine the dimensionality of principal components.2005 International BCI competition data set was used in our experiments,and four feature extraction methods were adopted,i.e.power spectrum estimation,continuous wavelet transform,wavelet packet decomposition and Hjorth parameters.The proposed feature selection algorithm was adopted to select and combine the most useful features for classification.The results showed that relative to the ...