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Introduction
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January 2014 - present
Publications
Publications (282)
Pneumatic soft robots are promising in diverse applications while they typically require additional electronics or components for pressure control. Fusing pneumatic actuation and control capabilities into a simple soft module remains challenging. Here, we present a class of bistable fabric mechanisms (BFMs) that merge soft bistable actuators and va...
Hydrogel-based soft machines are promising in diverse applications, such as biomedical electronics and soft robotics. However, current fabrication techniques generally struggle to construct multimaterial three-dimensional hydrogel architectures for soft machines and robots, owing to the inherent hydrogel softness from the low-density polymer networ...
Objective. The application of electromyography (EMG) decomposition techniques in myoelectric control has gradually increased. However, most decomposition-based control schemes rely on machine learning, lacking interpretation of the biological mechanisms underlying movement generation and requiring large datasets for training. As neuromusculoskeleta...
Objective:
The Motor Imagery (MI) paradigm has been widely used in brain-computer interface (BCI) for device control and motor rehabilitation. However, the MI paradigm faces challenges such as comprehension difficulty and limited decoding accuracy. Therefore, we propose the Action Observation with Rhythm Imagery (AORI) as a natural paradigm to pro...
Numerical models of electromyography (EMG) signals have provided a huge contribution to our fundamental understanding of human neurophysiology and remain a central pillar of motor neuroscience and the development of human–machine interfaces. However, while modern biophysical simulations based on finite element methods (FEMs) are highly accurate, th...
Objective. Brain switches provide a tangible solution to asynchronized brain-computer interface, which decodes user intention without a pre-programmed structure. However, most brain switches based on electroencephalography signals have high false positive rates (FPRs), resulting in less practicality. This research aims to improve the operating mode...
Pinch is an indispensable grasping primitive of human hands and traditional rigid grippers, eminently suitable for handling small-sized and dense objects, but it is rather under-researched in the context of soft robotics. In this article, with the aim of combining the inherent advantages of soft materials and the pinch grasp primitive to enable del...
Neuromechanical studies investigate how the nervous system interacts with the musculoskeletal (MSK) system to generate volitional movements. Such studies have been supported by simulation models that provide insights into variables that cannot be measured experimentally and allow a large number of conditions to be tested before the experimental ana...
Variational integrators play a pivotal role in the simulation and control of constrained mechanical systems. Recognizing the need for a Lagrange-multiplier-free approach in such systems, this study introduces a novel method for constructing variational integrators on manifolds. Our approach unfolds in three key steps: (1) local parameterization of...
Soft pneumatic actuators (SPAs), due to their compliance and adaptiveness, are promising solutions for manipulation. However, most SPAs have only simple motion modes and cannot perform the compound motion required for complex manipulation. In this work, we propose a parallel-chamber actuator capable of multidirectional compound bending, short for C...
For redundantly actuated overconstrained parallel robots (ROPRs), the existing general error models for kinematic calibration often omit their redundantly actuated and overconstrained characteristics, affecting the precision of the calibration. To address this issue, a general redundancy-aware error model (RAEM) is proposed. First, the configuratio...
Brain-computer interfaces (BCIs) have emerged as one of the most promising techniques for individuals with motor disabilities to control external devices directly without peripheral pathways. While the discrete control strategy is widely adopted in BCI systems, the continuous control strategy provides intuitive and fluent control of robotic devices...
The brain switch improves the reliability of asynchronous brain-computer interface (aBCI) systems by switching the control state of the BCI system. Traditional brain switch research focuses on extracting advanced electroencephalography (EEG) features. However, a low signal-to-noise ratio (SNR) of EEG signals resulted in limited feature information...
Steady-state visual evoked potential (SSVEP) based brain-computer interfaces (BCIs) have achieved an information transfer rate (ITR) of over 300 bits/min, but abundant training data is required. The performance of SSVEP algorithms deteriorates greatly under limited data, and the existing time-shift data augmentation method fails to improve it becau...
Neuromechanical studies investigate how the nervous system interacts with the musculoskeletal (MSK) system to generate volitional movements. Such studies have been supported by simulation models that provide insights into variables that cannot be measured experimentally and allow a large number of conditions to be tested before the experimental ana...
Objective:
While SSVEP-BCI has been widely developed to control external devices, most of them rely on the discrete control strategy. The continuous SSVEP-BCI enables users to continuously deliver commands and receive real-time feedback from the devices, but it suffers from the transition state problem, a period the erroneous recognition, when use...
Redundantly actuated parallel manipulators with two rotations and one translation (2R1T RAPMs) have the potential for machining complex surfaces, where a large orientation workspace and high stiffness are required. Considering the advantages of an offset moving platform, such as enlarged orientation workspace and improved stiffness, a novel 2R1T (2...
Dexterous prosthetic hand is an essential rehabilitation assistant device to improve the life quality of amputee patients. Despite the continuous emergence of commercial prostheses and laboratory prototypes, the rejection rate remains high caused by the poor neural interaction performance and excessive cognitive burden, especially for the usage of...
Making hand movements in response to visual cues is common in daily life. It has been well known that this process activates multiple areas in the brain, but how these neural activations progress across space and time remains largely unknown. Taking advantage of intracranial electroencephalographic (iEEG) recordings using depth and subdural electro...
Objective. Slow-wave modulation occurs during states of unconsciousness and is a large-scale indicator of underlying brain states. Conventional methods typically characterize these large-scale dynamics by assuming that slow-wave activity is sinusoidal with a stationary frequency. However, slow-wave activity typically has an irregular waveform shape...
Anthropomorphic robotic hands have been widely investigated to dexterously manipulate objects because of their anatomical similarity to the human hand. However, the large dimension of configuration space challenges the real-time performance of existing grasp planning methods and drastically limits the application of anthropomorphic hands. In this l...
Development and implementation of neuroprosthetic hands is a multidisciplinary field at the interface between humans and artificial robotic systems, which aims at replacing the sensorimotor function of the upper-limb amputees as their own. Although prosthetic hand devices with myoelectric control can be dated back to more than 70 years ago, their a...
A decade ago, a group of researchers from academia and industry identified a dichotomy between the industrial and academic state-of-the-art in upper-limb prosthesis control, a widely used bio-robotics application. They proposed four key technical challenges, if addressed, could bridge this gap and translate academic research into clinically and com...
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Surface electromyography (EMG) decomposition techniques have been developed to decode motor neuron activities non-invasively in the past decades, showing superior performance in human-machine interfaces such as gesture recognition and propor...
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. The surface electromyography (EMG) decomposition techniques provide access to motor neuron activities and have been applied to myoelectric control schemes. However, the current decomposition-based myoelectric control mainly focuses on discr...
Objective. The primary purpose of this study was to investigate the electrophysiological mechanism underlying different modalities of sensory feedback and multi-sensory integration in typical prosthesis control tasks. Approach. We recruited 15 subjects and developed a closed-loop setup for three prosthesis control tasks which covered typical activi...
In the cooperative transportation task with a
mobile manipulator (MM), the mobile robot and the manipulator must move simultaneously to adapt to the human
motion. In addition, the motion of the MM is underconstrained due to redundancy, which makes MM real-time motion planning challenging. In this article, a capability mapbased framework was propose...
Simulations of biophysical systems have provided a huge contribution to our fundamental understanding of human physiology and remain a central pillar for developments in medical devices and human machine interfaces. However, despite their successes, such simulations usually rely on highly computationally expensive numerical modelling, which is ofte...
Motor function assessment is essential for post-stroke rehabilitation, while the requirement for professional therapists’ participation in current clinical assessment limits its availability to most patients. By means of sensors that collect the motion data and algorithms that conduct assessment based on such data, an automated system can be built...
Motor unit spike trains (MUSTs) decomposed from surface electromyography (sEMG) have been an emerging solution for neural interfacing, especially for the control of upper limb prosthetics. Accurate and efficient decomposition techniques are essential and desirable. However, most decomposition methods are designed for motor units (MUs) with global m...
Multiple mobile manipulators show superiority in the tasks requiring mobility and dexterity compared with a single robot, especially when manipulating/transporting bulky objects. When the object and the manipulators are rigidly connected, closed-chain will form and the motion of the whole system will be restricted onto a lower-dimensional manifold....
Objective. Accurate identification of functional cortical regions is essential in neurological resection. The central sulcus (CS) is an important landmark that delineates functional cortical regions. Median nerve stimulation (MNS) is a standard procedure to identify the position of the CS intraoperatively. In this paper, we introduce an automated p...
Current myoelectric hands are limited in their ability to provide effective sensory feedback to the users, which highly affects their functionality and utility. Although the sensory information of a myoelectric hand can be acquired with equipped sensors, transforming the sensory signals into effective tactile sensations on users for functional task...
It is vital to recognize the intention of finger motions for human-machine interaction (HMI). The latest research focuses on fine myoelectric control through the decoding of neural motor unit action potential trains (MUAPt) from high-density surface electromyographic (sEMG) signals. However, the existing EMG decoding algorithms rarely obtain the sp...
Objective. Revealing the relationship between simultaneous scalp electroencephalography (EEG) and intracranial electroencephalography (iEEG) is of great importance for both neuroscientific research and translational applications. However, whether prominent iEEG features in the high-gamma band can be reflected by scalp EEG is largely unknown. To add...
As a minimally invasive recording technique, stereo-electroencephalography (SEEG) measures intracranial signals directly by inserting depth electrodes shafts into the human brain, and thus can capture neural activities in both cortical layers and subcortical structures. Despite gradually increasing SEEG-based brain-computer interface (BCI) studies,...
Invasive brain-computer interfaces (BCI) have made great progress in the reconstruction of fine hand movement parameters for paralyzed patients, where superficial measurement modalities including electrocorticography (ECoG) and micro-array recordings are mostly used. However, these recording techniques typically focus on the signals from the sensor...
Although significant advances in the design of soft robotic hands have been made to mimic the structure of the human hands, there are great challenges to control them for coordinated and human-like postures. Based on the principle of postural synergies in the human hand, we present a synergistic approach for coordinated control of a soft robotic ha...
Objective. The somatotopic interface (SI) and non-somatotopic interface (NI) are commonly used to provide non-invasive sensory feedback. Nevertheless, differences between somatotopic and non-somatotopic feedbacks are rarely reported, and objective evaluations of the corresponding brain response are missing as well. Few studies have reported how to...
Motor imagery-based brain-computer interfaces (BCIs) have been studied without controlling subjects’ gaze fixation position previously. The effect of gaze fixation and covert attention on the behavioral performance of BCI is still unknown. This study designed a gaze fixation controlled experiment. Subjects were required to conduct a secondary task...
Objective. Musculoskeletal model (MM) driven by electromyography (EMG) signals has been identified as a promising approach to predicting human motions in the control of prostheses and robots. However, muscle excitations in MMs are generally derived from the EMG signals of the targeted sensor covering the muscle, inconsistent with the fact that sign...
Objective:
The surface electromyography (EMG) decomposition techniques have shown promising results in neurophysiologic investigations, clinical diagnosis, and human-machine interfacing. However, current decomposition methods could only decode a limited number of motor units (MUs) because of the local convergence. The number of identified MUs rema...
Surface electromyography (EMG) signals have shown promising applications in human-machine interfacing (HMI) systems such as orthotics, prosthetics, and exoskeletons. Nevertheless, existing myoelectric control methods, generally based on time-domain or frequency-domain features, could not directly interpret neural commands. EMG decomposition techniq...
Elastic inflatable actuators (EIAs) are widely used
in the emerging field of soft robotics. Although integrating
multiple EIAs in soft robots has been demonstrated successful,
these EIAs typically require independent control inputs that
results in a complex actuation process. This paper proposes a
single-input pneumatic mechanisms (SIPM) to generat...
High-density surface electromyography (EMG) has been proposed to overcome the lower selectivity with respect to needle EMG and to provide information on a wide area over the considered muscle. Motor units decomposed from surface EMG signal of different depths differ in the distribution of action potentials detected in the skin surface. We propose a...
It is evident that surface electromyography (EMG) based human-machine interface (HMI) is limited by muscle fatigue. This paper investigated the effect of muscular fatigue on HMI performance using hybrid EMG and near-infrared spectroscopy (NIRS). Muscle fatigue inducing experiments were performed with eight subjects via sustained isometric contracti...
Objective:
Mathematical modelling of surface electromyographic (EMG) signals has been proven a valuable tool to interpret experimental data and to validate signal processing techniques. Most analytical EMG models only consider muscle fibers with specific arrangements. However, the fiber orientation may change along the fiber paths and differ from...
Neuroprosthetic hands are typically heavy (over 400 g) and expensive (more than US$10,000), and lack the compliance and tactile feedback of human hands. Here, we report the design, fabrication and performance of a soft, low-cost and lightweight (292 g) neuroprosthetic hand that provides simultaneous myoelectric control and tactile feedback. The neu...
Touch sensing has a central role in robotic grasping and emerging human–machine interfaces for robot‐assisted prosthetics. Although advancements in soft conductive polymers have promoted the creation of diverse pressure sensors, these sensors are difficult to be employed as touch skins for robotics and prostheses due to their limited sensitivity, n...
Objective. White matter tissue takes up approximately 50% of the human brain volume and it is widely known as a messenger conducting information between areas of the central nervous system. However, the characteristics of white matter neural activity and whether white matter neural recordings can contribute to movement decoding are often ignored an...
Myoelectric controlled interfaces driven by muscle activities have achieved good performance in ideal conditions and showed many potential medical-related and industrial applications. However, in practical applications, the performance could be drastically degraded due to the electrode (sensor) shift, which is inevitable in donning and doffing the...
One of the biggest challenges hindering a table tennis robot to play as well as a professional player is the ball’s accurate motion control, which depends on various factors such as the incoming ball’s position, linear, spin velocity and so forth. Unfortunately, some factors are almost impossible to be directly measured in real practice, such as th...
This work develops a compliant control strategy for the aerial manipulation of high-precision, which is easy to deploy and transplant between the simulation and the real system. To facilitate this development, a nominal dynamic model of the aerial manipulation system is first formulated by taking the attitude as a low-level control loop. On this ba...
Motor attempt (MA)/motor imagery (MI)-based brain–computer interface (BCI) is a newly developing rehabilitation technology for motor impairment. This study aims to explore the relationship between electroencephalography sensorimotor rhythm and motor impairment to provide reference for a BCI design. Twenty-eight stroke survivors with varying levels...
Name recognition plays important role in self-related cognitive processes and also contributes to a variety of clinical applications, such as autism spectrum disorder diagnosis and consciousness disorder analysis. However, most previous name-related studies usually adopted noninvasive EEG or fMRI recordings, which were limited by low spatial resolu...
Proper training is essential to achieve reliable pattern recognition (PR) based myoelectric control. The amount of training is commonly determined by experience. The purpose of this study is to provide an offline validation method that makes the offline performance transferable to online control and find the proper amount of training that achieves...
