Jian Huang

Jian Huang
Huazhong University of Science and Technology | hust · Institute of Automation

Ph.D

About

290
Publications
49,772
Reads
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4,455
Citations
Citations since 2017
130 Research Items
3445 Citations
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20172018201920202021202220230200400600
20172018201920202021202220230200400600
20172018201920202021202220230200400600
Introduction
Jian Huang graduated from Huazhong University of Science and Technology (HUST), China in 1997 and received the Master of Engineering degree from HUST in 2000. He received his Ph.D from HUST in 2005. From 2006 to 2008, he was a postdoctoral researcher in the Department of Micro-Nano System Engineering and Department of Mechano-Informatics and Systems, Nagoya University, Japan. In 2015, he was a research fellow in Nagoya University supported by JSPS invitation fellowship. He is currently a full professor with the School of Automation, HUST. He is also a guest professor in Nagoya University of Japan and University Paris-Est Créteil (UPEC) of France. His main research interests include rehabilitation robot, robotic assembly, networked control systems and bioinformatics.
Additional affiliations
October 2008 - October 2013
Huazhong University of Science and Technology
Position
  • Professor (Associate)
October 2006 - September 2008
Nagoya University
Position
  • PostDoc Position

Publications

Publications (290)
Article
Soft-bending pneumatic actuators (SBPA) have shown great potential in various applications owing to their intrinsic compliance. However, motion control is still challenging because of the complicated hysteresis of the elastic material and pneumatic system, which unlike the general hysteresis found in the rigid body mechanism, is rate-dependent and...
Article
Full-text available
Recent advances in flexible wearable devices have boosted the remarkable development of devices for human–machine interfaces, which are of great value to emerging cybernetics, robotics, and Metaverse systems. However, the effectiveness of existing approaches is limited by the quality of sensor data and classification models with high computational...
Article
Full-text available
Objective: While neuroscience research has established a link between vision and intention, studies on gaze data features for intention recognition are absent. The majority of existing gaze-based intention recognition approaches are based on deliberate long-term fixation and suffer from insufficient accuracy. In order to address the lack of feature...
Article
In this article, a robust trajectory tracking control method is proposed for the passive gait training exoskeleton system driven by pneumatic muscles (PMs). Conventional model-based controllers suffer from limitations with respect to model uncertainties and external disturbances caused by PMs and complex robotic systems. An echo state network (ESN)...
Article
An effective fault locating method is necessary to ensure the stable and efficient operation of solid oxide fuel cells (SOFCs). There is still a lack of a common fault locating method for locating multiple faults in SOFC systems. Therefore, this article proposes a multifault spatiotemporal locating method combining long short-term memory (LSTM) art...
Article
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Gait analysis and evaluation are vital for disease diagnosis and rehabilitation. Current gait analysis technologies require wearable devices or high-resolution vision systems within a limited usage space. To facilitate gait analysis and quantitative walking-ability evaluation in daily environments without using wearable devices, a mobile gait analy...
Article
In dynamic outdoor environments characterized by turbulent airflow and intermittent odor plumes, robotic odor plume tracking remains challenging, because existing algorithms heavily rely on manually tuning or learning from expert experience, which are hard to implement in an unknown environment. In this paper, a multi-continuous-output Takagi–Sugen...
Article
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In emotion recognition based on physiological signals, collecting enough labeled data of a single subject for training is time-consuming and expensive. The physiological signals’ individual differences and the inherent noise will significantly affect emotion recognition accuracy. To overcome the difference in subject physiological signals, we propo...
Article
With the excellent characteristic of intrinsic compliance, pneumatic artificial muscle can improve the interaction comfort of wearable robotic devices. This paper resolves the safety tracking control problem of a pneumatically actuated lower limb exoskeleton system. A single-parameter adaptive fuzzy control strategy is proposed with high control pr...
Article
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Traditional human emotion recognition is based on electroencephalogram (EEG) data collection technologies which rely on plenty of rigid electrodes and lack anti‐interference, wearing comfort, and portability. Moreover, a significant distribution difference in EEG data also results in low classification accuracy. Here, on‐skin biosensors with adhesi...
Article
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The closed kinematic structure of Gough–Stewart platforms causes the kinematic control problem, particularly forward kinematics. In the traditional hybrid algorithm (backpropagation neural network and Newton–Raphson), it is difficult for the neural network part to train different datasets, causing training errors. Moreover, the Newton–Raphson metho...
Article
Underactuated systems are extensively utilized in practice while attracting a huge deal of attention in theoretical studies. There are few robust control strategies for general underactuated systems because of the variety of their dynamic models. A dynamic surface control strategy with a nonlinear disturbance observer is proposed in this study, to...
Article
The papers in this special section focus on cyborg intelligence. Well-known scientists and experts have expressed concern that robots may take over the world. More generally, there is a concern that robots could take over human jobs and leave billions of people suffering long-term unemployment. Yet, such concerns ignored the potential of intelligen...
Article
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Robust classification of natural hand grasp type based on electromyography (EMG) still has some shortcomings in the practical prosthetic hand control, owing to the influence of dynamic arm position changing during hand actions. This study provided a framework for robust hand grasp type classification during dynamic arm position changes, improving b...
Article
Current linkage-driven prosthetic hands still show limitations in aspects such as the thumb design and fingertip sensor. Moreover, linkage-driven prosthetic hands still lack quantitative precision grasp quality. In this study, we developed a novel thumb structure with coupled abduction–adduction and pronation–supination movement in the trapeziometa...
Article
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Sit-to-stand (STS) transfer is an easy everyday activity for healthy people, but it is a challenging task for the elderly, and patients with lower-limb weaknesses. This article presents an intelligent assistive walker, which assists the user to accomplish safe STS transfers. An STS intention recognition method is proposed based on an optimized adap...
Article
In recent years, the electronic devices and wireless network are seen everywhere, generating a massive amount of online surveillance video data that can be applied to recognize facial expressions to sustain the smart education cloud deployment. However, research highlights of existing Facial Expression Recognition (FER) methods mainly focus on the...
Chapter
Course scheduling is a difficult problem in real school management, which takes a lot of effort of the staff. In this paper, an optimization method based on genetic algorithm is proposed to solve the course scheduling problem in the background of Chinese College Entrance Examination Reform, which means that students of high school should learn 3 co...
Article
This article proposes a distributed cooperative manipulation control scheme for multirobot systems to track reference trajectories with unknown payload dynamics, grasp positions, and external disturbances. An online learning module is established to estimate the payload dynamics. Then a wrench-synthetic trajectory tracking control protocol is there...
Article
Bootstrap aggregating (Bagging) and boosting are two popular ensemble learning approaches, which combine multiple base learners to generate a composite model for more accurate and more reliable performance. They have been widely used in biology, engineering, healthcare, etc. This paper proposes BoostForest, which is an ensemble learning approach us...
Research Proposal
Full-text available
Designing complex control systems with the least amount of information and simplest structure has been one of the main challenging research directions in both academia and potential research applications. It is a significant problem not only from a theoretical perspective, but it also has a great impact on potential applications. is is attributed t...
Article
As an important movement of the daily living activities, sit-to-stand (STS) movement is usually a difficult task facing elderly and dependent people. In this article, a novel impedance modulation strategy of a lower-limb exoskeleton is proposed to provide appropriate power and balance assistance during STS movements while preserving the wearer’s co...
Article
Solid oxide fuel cells are a promising alternative energy source for new energy vehicles, distributed power generation and military equipment. It has the advantages of high efficiency, low noise, low emission and flexible fuel. In order to commercialize solid oxide fuel cells with high efficiency, long life and stable operation, the performance of...
Article
Full-text available
In this paper, an interval type-2 fuzzy disturbance observer (IT2FDO) is proposed for the trajectory tracking control of a flexible joint actuated by a pneumatic artificial muscle (PAM) and a torsion spring. Interval type-2 fuzzy sets are introduced into the fuzzy disturbance observer (FDO) to enhance fuzzy approximation capability. A novel adaptiv...
Article
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Wearable robots have become a prevalent method in the field of human augmentation and medical rehabilitation. Typical wearable robots mainly include exoskeletons and prostheses. However, their functions are limited due to dedicated design. In recent years, Supernumerary Robotic Limbs (SRLs) have become a hot spot in the field of wearable robots. Di...
Article
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Robotic odor/gas source localization is a widely studied field, but most of the existing works are about rule-based algorithms. In this paper, the Deep Q-Network algorithm is applied to solve the odor source localization problem. An odor hits distribution model is proposed to model the odor concentration distribution in indoor environments, taking...
Article
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Assisting and supervising daily long-durational walking is very crucial for patients with lower extremity dysfunction, especially in the stage of recovery towards a state of walking independently. However, due to the shortage of caregivers and high-cost of nursing, long-term manual assistance and supervision is costly. Thus, in this paper, we propo...
Article
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This paper presents a tracking control method for pneumatic muscle actuators (PMAs). Considering that the PMA platform only feedbacks position, and the velocity and disturbances cannot be observed directly, we use the extended-state-observer (ESO) for simultaneously estimating the system states and disturbances by using measurable variables. Integr...
Article
Full-text available
Human activity recognition (HAR) based on the wearable device has attracted more attention from researchers with sensor technology development in recent years. However, personalized HAR requires high accuracy of recognition, while maintaining the model’s generalization capability is a major challenge in this field. This paper designed a compact wir...
Article
The effectiveness of rehabilitation treatment with the Body Weight Support (BWS) system has been demonstrated in patients with stroke and spinal cord injury. Many recent studies used expensive force sensors to realize the force control, which plays an important role in a BWS system. To reduce the system cost and complexity, and overcome some shortc...
Preprint
Full-text available
Bootstrap aggregating (Bagging) and boosting are two popular ensemble learning approaches, which combine multiple base learners to generate a composite model for more accurate and more reliable performance. They have been widely used in biology, engineering, healthcare, etc. This article proposes BoostForest, which is an ensemble learning approach...
Preprint
Eye movement is closely related to limb actions, so it can be used to infer movement intentions. More importantly, in some cases, eye movement is the only way for paralyzed and impaired patients with severe movement disorders to communicate and interact with the environment. Despite this, eye-tracking technology still has very limited application s...
Article
This paper designed a soft bending actuator (SBA) and presented a neural-network-based tracking control strategy for such an actuator. To achieve high-precision control, a visual feedback system was established by using a high-speed camera to dynamically compute the corresponding central angle which described the curvature of the SBA. Considering i...
Article
Pneumatic muscle actuators (PMAs) are compliant and suitable for robotic devices that have been shown to be effective in assisting patients with neurologic injuries, such as strokes, spinal cord injuries, etc., to accomplish rehabilitation tasks. However, because PMAs have nonlinearities, hysteresis, and uncertainties, etc., complex mechanisms are...
Preprint
Full-text available
Research and development of electroencephalogram (EEG) based brain-computer interfaces (BCIs) have advanced rapidly, partly due to the wide adoption of sophisticated machine learning approaches for decoding the EEG signals. However, recent studies have shown that machine learning algorithms are vulnerable to adversarial attacks, e.g., the attacker...
Article
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The time spent in collecting current samples for decoder calibration and the computational burden brought by high-dimensional neural recordings remain two challenging problems in intracortical brain-machine interfaces (iBMIs). Decoder calibration optimization approaches have been proposed, and neuron selection methods have been used to reduce compu...
Article
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The human-centered robotic systems demand safe and robust controllers in many applications. This paper proposes an adaptive proxy-based sliding mode control approach for a class of typical second-order nonlinear systems. A new PID-type virtual coupling is designed between a virtual proxy and the physical object. Considering the unknown bound of lum...
Article
Full-text available
Background: For the nonstationarity of neural recordings in intracortical brain-machine interfaces, daily retraining in a supervised manner is always required to maintain the performance of the decoder. This problem can be improved by using a reinforcement learning (RL) based self-recalibrating decoder. However, quickly exploring new knowledge whi...
Article
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To improve the reliability and safety of myoelectric prosthetic control, many researchers tend to use multi-modal signals. The combination of electromyography (EMG) and forcemyography (FMG) has been proved to be a practical choice. However, an integrative and compact design of this hybrid sensor is lacking. This paper presents a novel modular EMG–F...
Poster
Full-text available
The following special issue of which I am the guest editor will be published in Sensors (ISSN 1424-8220, IF 3.031, http://www.mdpi.com/journal/sensors), and is now open to receive submissions of full research articles and comprehensive review papers for peer-review and possible publication: Special Issue: Wearable Sensor for Activity Analysis and...
Preprint
Transfer learning (TL) has been widely used in electroencephalogram (EEG) based brain-computer interfaces (BCIs) to reduce the calibration effort for a new subject, and demonstrated promising performance. After EEG signal acquisition, a closed-loop EEG-based BCI system also includes signal processing, feature engineering, and classification/regress...
Article
Full-text available
In this paper we tackle the problem of finding the source of particulate matter with a mobile robot equipped with a low-cost multi-channel optical particle counting sensor. The proposed method is based on the Infotaxis odor source localization algorithm and makes multiple modifications to adapt it to particle plumes. In particular, we propose three...
Article
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In Pneumatic Muscle Actuators (PMAs)-driven robotic applications, there might exist unpredictable shocks which lead to the sudden change of desired trajectories and large tracking errors. This is dangerous for physical systems. In this paper, we propose a novel adaptive proxy-based robust controller (APRC) for PMAs, which is effective in realizing...
Preprint
Bootstrap aggregation (Bagging) and boosting are two popular ensemble learning approaches, which combine multiple base learners to generate a composite learner. This article proposes BoostForest, which is an ensemble learning approach using BoostTree as base learners and can be used for both classification and regression. BoostTree constructs a tre...
Article
The smoke source localization robot is a safe substitution of human and animal rescuers in many dangerous search and rescue mission. In this paper, we propose an anemotaxis – particle filter based smoke plume path tracking method and presented a smoke source localization robot. A modified firefly algorithm is applied in the resampling step of parti...
Article
This paper presents a single-layer learning based predictive control strategy for Pneumatic Muscle Actuators (PMAs)-driven lower limb exoskeleton. Although PMAs are promising for rehabilitation robots, they suffer from nonlinearities, unmodeled uncertainties, and hysteresis, etc. As a consequence, the mechanism actuated by PMAs rarely involves comp...
Article
Full-text available
Since manual inspection of analog instruments is inefficient, many computer vision-based automatic reading systems have been proposed recently. However, most of them use fixed cameras, which are costly due to the large number of used cameras. Although some other systems adopting the pan-tiltzoom camera and the movable inspection robot can avoid usi...
Article
Takagi-Sugeno-Kang (TSK) fuzzy systems are flexible and interpretable machine learning models; however, they may not be easily optimized when the data size is large, and/or the data dimensionality is high. This paper proposes a mini-batch gradient descent (MBGD) based algorithm to efficiently and effectively train TSK fuzzy classifiers. It integrat...
Article
Takagi-Sugeno-Kang (TSK) fuzzy systems are very useful machine learning models for regression problems. However, to our knowledge, there has not existed an efficient and effective training algorithm that ensures their generalization performance, and also enables them to deal with big data. Inspired by the connections between TSK fuzzy systems and n...
Article
This study addresses the set-membership estimation problem for a class of discrete time-varying systems with incomplete observations. A set-membership filter is developed and a recursive algorithm is proposed to calculate the state estimate ellipsoid which contains the true value. To solve the problem that the conventional set-membership filter can...
Article
Peripheral nervous system, widely spread in the whole body, is the important bridge for the transmission of neural signals. Signals from the central nervous system (brain and spinal cord) are transmitted to different parts of the body by the peripheral nerves, while along the way they also feedback all kinds of sensory information. Certain level of...
Article
Fuzzy systems have achieved great success in numerous applications. However, there are still many challenges in designing an optimal fuzzy system, e.g., how to efficiently optimize its parameters, how to balance the trade-off between cooperations and competitions among the rules, how to overcome the curse of dimensionality, how to increase its gene...
Article
Full-text available
The fingertip sensor is essential for the closed loop control of prosthetic hand, while the development of a tactile sensor with a balance in the cost and performance is still a challenge. This paper presents the development of an anthropomorphic fingertip sensor for prosthetic hands. The structure of our sensor mainly consists of a force sensing r...
Article
Full-text available
Robot-assisted walking has become a popular research field for helping mobility-limited people to walk more easily. Different from other walking-aid devices (e.g. exoskeletons and prosthesis), intelligent mobile walking-aids (IMWs) are invented for helping the visually impaired or people in need (e.g. the elderly) to walk in daily life. This paper...
Article
Full-text available
Rehabilitation and nursing-care robots have become one of the prevalent methods for assistant treatment of motor disorder patients in the field of medical rehabilitation. Traditional rehabilitation robots are mostly made of rigid materials, which significantly limits their application for medical rehabilitation and nursing-care. Soft robots show gr...