Sheng Quan Xie

University of Leeds

The trajectory tracking and obstacle avoidance problems of autonomous mobile robots are typically solved through the layered planning and tracking method. However, this asynchronous method introduces a temporal lag between the planning stage and the execution of the control command. To solve this problem, this article proposes a simultaneous planni...

The brain-computer interface (BCI) based on rapid serial visual presentation (RSVP) exhibits enhanced accuracy in target recognition in the complex environments by effectively extracting EEG’s features, thereby it may compensate recognition defects of computer vision-based vision measurement systems. Given the current limited comprehension of brain...

Knee joint disorders pose a significant and growing challenge to global healthcare systems. Recent advancements in robotics, sensing technologies, and artificial intelligence have driven the development of robot-assisted therapies, reducing the physical burden on therapists and improving rehabilitation outcomes. This study presents a novel knee exo...

Objectives To explore the diagnostic efficacy of advanced intelligent clear-IQ engine (AiCE) and adaptive iterative dose reduction 3D (AIDR 3D), combination with and without the black blood CT technique (BBCT), for detecting vascular invasion in patients diagnosed with nonmetastatic pancreatic ductal adenocarcinoma (PDAC). Methods A total of 35 co...

This article proposes a novel twisting mechanism with parallel springs (TPS) employing eight parallel springs in 3-D configuration and a ball screw mechanism to achieve space-efficient stiffness regulation. A compact variable stiffness actuator (VSA) prototype, named TPS–VSA, is developed based on the TPS. Two models are established to estimate the...

The widespread application of exoskeletons driven by soft actuators in motion assistance and medical rehabilitation has proven effective for patients who struggle with precise object grasping and suffer from insufficient hand strength due to strokes or other conditions. Repetitive passive flexion/extension exercises and active grasp training are kn...

Traditional rehabilitation training for stroke patients with ankle joint issues typically relies on the expertise of physicians. However, when confronted with complex challenges, such as online decision-making or assessing rehabilitation progress, even seasoned experts may not anticipate all potential hurdles. A novel approach is necessary—one that...

Post-stroke upper limb dysfunction severely impacts patients' daily life quality. Utilizing sEMG signals to predict patients' motion intentions enables more effective rehabilitation by precisely adjusting the assistance level of rehabilitation robots. Employing the muscle synergy (MS) features can establish more accurate and robust mappings between...

The burgeoning advancement of brain-computer interface (BCI) continues to enrich its applications in human-computer interaction (HCI), e.g., assistive robotics, game design, etc. Notwithstanding this progress, the efficacy of BCI remains impeded by classification errors which cause erroneous behavior for controlled devices. In this paper, we propos...

Gait phase detection holds great importance in the field of human activity detection and medical rehabilitation, but at present, gait recognition technology still has the disadvantages of insufficient portability and high cost. Gait recognition based on pressure pad measurement limits the subjects to a small space, while gait recognition based on i...

To investigate the diagnostic performance and complication rates of percutaneous transthoracic CT-guided coaxial core needle biopsy (PTCNB) in persistent consolidations and evaluate its safety in routine clinical practice. A total of 685 patients (404 males, 281 females) underwent PTCNB with coaxial core technique for persisted consolidation were r...

Research on Lower Limb Motion Recognition (LLMR) based on various wearable sensors has been widely applied in exoskeleton robots, exercise rehabilitation, etc. Typically, employing multimodal information tends to yield higher accuracy and stronger robustness compared to using unimodal information. Due to the inevitable reliance on feature engineeri...

This study aimed to propose a portable and intelligent rehabilitation evaluation system for digital stroke-patient rehabilitation assessment. Specifically, the study designed and developed a fusion device capable of emitting red, green, and infrared lights simultaneously for photoplethysmography (PPG) acquisition. Leveraging the different penetrati...

This review aims to provide a systematic analysis of the literature focused on the use of intelligent control systems in robotics for physical rehabilitation, identifying trends in recent research and comparing the effectiveness of intelligence used in control, with the aim of determining important factors in robot-assisted rehabilitation and how i...

Robot-assisted rehabilitation therapy has become a mainstream trend for the treatment of stroke patients. It can not only relieve physiotherapists from heavy physical duties, but also provide patients with effective ankle-foot rehabilitation and walking assistance. Soft ankle-foot exoskeletons have rapidly evolved in the last decade. This article p...

Upper limb functional impairments persisting after stroke significantly affect patients’ quality of life. Precise adjustment of robotic assistance levels based on patients’ motion intention using sEMG signals is crucial for active rehabilitation. This paper systematically reviews studies over the past decade on continuous prediction of upper limb s...

With the number of people surviving a stroke soaring, automated upper limb impairment assessment has been extensively investigated in the past decades since it lays the foundation for personalised precision rehabilitation. The recent advancement of sensor systems, such as high-precision and real-time data transmission, have made it possible to quan...

The densely cluttered operational environment and the absence of object information hinder mobile manipulators from achieving specific grasping tasks. To address this issue, this paper proposes a task-oriented grasping framework guided by visual semantics for mobile manipulators. With multiple attention mechanisms, we first present a modified DeepL...

With the constant evolution of information technology, the paradigm of human-computer interaction has progressively transitioned from emphasizing command behavior to a novel approach that prioritizes natural language and emotional communication. In response to this trend, the development of an effective model for emotion recognition has become impe...

This paper proposes a progressive learning based assist-as-needed (AAN) control scheme for ankle rehabilitation. To quantify the training performance, a fuzzy logic (FL) system is established to generate a holistic metric based on multiple kinematic and dynamic indicators. Subsequently, a cost function that contains both the tracking error and robo...

This article proposes a lightweight variable stiffness actuator (LVSA) driven by a novel mechanism with four sliders on a shared crank (FS2C). The FS2C mechanism allows the LVSA to simultaneously regulate the preload of four springs using only one motor and hence achieves a wider-range continuous stiffness adaption with reduced weight. A cable tran...

The assessment of implant status and complications of Total Hip Replacement (THR) relies mainly on the clinical evaluation of the X-ray images to analyse the implant and the surrounding rigid structures. Current clinical practise depends on the manual identification of important landmarks to define the implant boundary and to analyse many features...

Objective Digital twins (DTs) have received widespread attention recently, providing new ideas and possibilities for future healthcare. This review aims to provide a quantitative review to analyze specific study contents, research focus, and trends of DT in healthcare. Simultaneously, this review intends to expand the connotation of “healthcare” in...

Background Extremities fractures are a leading cause of death and disability, especially in the elderly. Avulsion fracture are also the most commonly missed diagnosis, and delayed diagnosis leads to higher litigation rates. Therefore, this study evaluates the diagnostic efficiency of the artificial intelligence (AI) model before and after optimizat...

Steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs) have been extensively studied due to many benefits, such as non-invasiveness, high information transfer rate, and ease of use. SSVEP-based BCI has been investigated in various applications by projecting brain signals to robot control commands. However, the movement...

Background Quantification of vertebral arteries can provide insights into basilar curvature and plaque. Therefore, this retrospective study aimed at identifying the dominant vertebral artery (VA) causing basilar artery (BA) curvature and to further quantify the effect of dominant VA angle on BA curvature and BA plaque using high-resolution magnetic...

With the increasing demand for rehabilitation of the elderly population and patients with limb injuries, it is imperative to develop new wearable health monitoring system and assistive rehabilitation equipment. Optical fiber sensing has the advantages of light-weight, anti-electromagnetic interference, higher strain and elastic limit, safety and de...

Although deep learning (DL) techniques have been extensively researched in upper-limb myoelectric control, system robustness in cross-day applications is still very limited. This is largely caused by non-stable and time-varying properties of surface electromyography (sEMG) signals, resulting in domain shift impacts on DL models. To this end, a reco...

Background: Diagnosing persistent pulmonary consolidation still faces challenges. The purpose of this study is to compare the diagnostic yield and the complication rate between percutaneous transthoracic CT-guided coaxial needle biopsy (PTCNB) and transbronchial lung biopsy (TBLB) of persistent pulmonary consolidation. Materials: From January 1,...

Selection of an actuation system for assistive robotic exoskeletons requires careful consideration of various design factors. It is generally the requirement of the system to produce lightweight and power-efficient systems. In some cases, the torque and power requirements could be relaxed by using redundant systems. This paper involves the study of...

Background: The assessment of cerebral blood flow (CBF) is crucial in the evaluation of intracranial atherosclerotic disease. This study was performed to compare single postlabeling delay (PLD) 3-dimensional pseudo-continuous arterial spin labeling (3D-pCASL) and 7-delay 3D-pCASL magnetic resonance imaging in patients with intracranial atheroscler...

Background: The reaching test is widely adapted in motor function assessment of stroke rehabilitation. To evaluate the motor disorder quantitatively, it is important to measure the differences between reaching movements made by healthy people and patients. Thus a movement prediction model should be firstly established on healthy people as a customi...

Background: The aim of a robotic exoskeleton is to match the torque and angular profile of a healthy human subject in performing activities of daily living. Power and mass are the main requirements considered in the robotic exoskeletons that need to be reduced so that portable designs to perform independent activities by the elderly users could be...

Myoelectric control methods aim at driving electric prostheses in restoring functionality in daily life for amputees. To achieve the simultaneous and proportional estimation of multiple kinematics of the wrist joint, model-free approaches are broadly developed but rely on the abundant training data and the numerical functions that omit neuro-mechan...

Steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs) have been substantially studied in recent years due to their fast communication rate and high signal-to-noise ratio. The transfer learning is typically utilized to improve the performance of SSVEP-based BCIs with auxiliary data from the source domain. This study pro...

This paper presents a novel ankle rehabilitation exoskeleton with two rotational degrees of freedom, which is suitable for dynamical rehabilitation for patients with neurological impairments. Its stiffness performance is assessed in consideration that the interaction between the footplate and the ground may deflect the mechanism away from the desir...

The brain-computer interface (BCI) enables paralyzed people to directly communicate with and operate peripheral equipment. The steady-state visual evoked potential (SSVEP)-based BCI system has been extensively investigated in recent years due to its fast communication rate and high signal-to-noise ratio. Many present SSVEP recognition methods deter...

Upper limb rehabilitation robot can assist stroke patients to complete daily activities to promote the recovery of upper-limb motor functions. However, the robot uncertainty and the patient’s unconscious disturbance impose great difficulties on the high-performance trajectory tracking of the rehabilitation robot. In this paper, an uncertainty compe...

Objectives This study aimed to identify whether apparent diffusion coefficient (ADC) values and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) parameters are helpful in distinguishing mesorectal tumor deposits (TD) from metastatic lymph nodes (MLN) in rectal cancer (RC).Methods Thirty patients (59 lesions, including 30 TD and 29 MLN...

This paper investigates the repetitive range of motion (ROM) training control for a compliant ankle rehabilitation robot (CARR). The CARR utilizes four pneumatic muscle (PM) actuators to manipulate the ankle with three rational degree-of-freedoms (DoFs) and soft human-robot interaction, but the strong-nonlinearity of the PM actuator makes precise t...

Musculoskeletal models have been widely used for detailed biomechanical analysis to characterise various functional impairments given their ability to estimate movement variables (i.e., muscle forces and joint moments) which cannot be readily measured in vivo. Physics-based computational neuromusculoskeletal models can interpret the dynamic interac...

Data-driven methods have become increasingly more prominent for musculoskeletal modelling due to their conceptually intuitive simple and fast implementation. However, the performance of a pre-trained data-driven model using the data from specific subject(s) may be seriously degraded when validated using the data from a new subject, hindering the ut...

Myoelectric control has gained much attention which translates the human intentions into control commands for exoskeletons. The electromyogram (EMG)-driven musculoskeletal (MSK) model shows prominent performance given its ability to interpret the underlying neuromechanical processes among the musculoskeletal system. This model-based scheme contains...

Data-driven methods have become increasingly more prominent for musculoskeletal modelling due to their conceptually intuitive simple and fast implementation. However, the performance of a pre-trained data-driven model using the data from specific subject(s) may be seriously degraded when validated using the data from a new subject, hindering the ut...

Wrist rehabilitation exoskeletons have gained much attention over the last decades, striving to restore motor functions for patients with neuromuscular disorders. Electromyography signal has been employed to estimate the motion intention to achieve interactive training schemes. However, it is a challenging task to estimate the joint impedance in re...

Background: Spinal Cord Injury (SCI) or Acquired Brain Injury (ABI) leads to disability, unemployment, loss of income, decreased quality of life and increased mortality. The impact is worse in Low-and Middle-Income Countries (LMICs) due to a lack of efficient long-term rehabilitative care. This study aims to explore the feasibility and acceptabili...

Brain-computer interface (BCI) can provide a direct communication path between the human brain and an external device. The steady-state visual evoked potential (SSVEP)-based BCI has been widely explored in the past decades due to its high signal-to-noise ratio and fast communication rate. Several spatial filtering methods have been developed for fr...

Objective The purpose of this study was to evaluate the usefulness of intraprocedural CT and prior PET/CT fusion imaging in improving the diagnostic yield of CT-guided transthoracic core-needle biopsy (CNB) in lung masses. Methods In total, 145 subjects with lung masses suspicious for malignancy underwent image-guided transthoracic CNB. According...

In order to realize gait assessment and robot-assisted control in lower extremity rehabilitation scenarios, prevention and diagnosis of lower extremity diseases, a sensitivity-enhanced array fiber optic sensing insole for plantar pressure monitoring was designed by taking advantage of the characteristics of fiber optic sensor, such as lightness, an...

Multiple strain sensors are required to identify individual forces/stresses on human joints and recognize how they work together in order to determine the motion’s direction and trajectory. However, current sensors cannot detect and differentiate the individual forces/stresses and their contributions to the motion from the sensors’ electrical signa...

With the rapid development of soft exoskeletons, traditional cylindrical pneumatic artificial muscles (PAM) can no longer meet people's needs of wearable exoskeleton for hand rehabilitation. We propose a novel flat pneumatic artificial muscle with the advantage of lightweight, small size, and fitting on the skin without squeezing, made of silicone...

Musculoskeletal models have been widely used for detailed biomechanical analysis to characterise various functional impairments given their ability to estimate movement variables (i.e., muscle forces and joint moment) which cannot be readily measured in vivo. Physics-based computational neuromusculoskeletal models can interpret the dynamic interact...

Ankle rehabilitation for increasing number of strokes is highly demanded, and robot-assisted approach has shown great potential. Since the required movement and force assistances will concurrently change during rehabilitation sessions, the robotic assistances are supposed to be adjusted accordingly. In order to achieve both adaptive torque and sync...

A dramatic proliferation of research is placed on wearable and skin-mountable sensing devices because of the prominent serviceability in motion and health recognition, man-machine interaction, as well as artificial intelligence. State-of-the-art wearable sensors, however, lack sensing reliability towards either fickle wearable microclimate or multi...

Dynamic behavior of the pneumatic muscle actuator (PMA) is conventionally modeled as a pressure-based first-order equation under discrete loads, which cannot exactly describe its dynamic features. Considering PMA’s nonlinear, time-varying and hysteresis characteristics, we propose a novel high-order modified dynamic model of PMA based on its physic...

Purpose: To quantitatively identify abnormal lung motion in chronic obstructive pulmonary disease (COPD) using strain analysis, and further clarify the potential differences of deformation in COPD with different severity of airflow limitation. Materials and methods: Totally, 53 patients at high-risk for COPD were enrolled in this study. All CT e...

Aims: The basilar artery (BA) geometry and plaque characteristics may play an important role in the development of atherosclerosis. This study was performed to explore the relationship between the mid-BA angle and plaque characteristics and its effect on pontine infarction using high-resolution magnetic resonance imaging and three-dimensional time...

Conventional measurement of spasticity in stroke patients, e.g., modified Ashworth scale (MAS), has been challenged about its reliability issues. Surface electromyography (sEMG) has been used to identify neuromuscular abnormalities since it directly measures electrical activity in the muscle, however its performance is affected by the placement of...

Monocular depth estimation and semantic segmentation are two fundamental goals of scene understanding. Due to the advantages of task interaction, many works have studied the joint-task learning algorithm. However, most existing methods fail to fully leverage the semantic labels, ignoring the provided context structures and only using them to superv...

To develop multi-functional human-machine interfaces that can help disabled people reconstruct lost functions of upper-limbs, machine learning (ML) and deep learning (DL) techniques have been widely implemented to decode human movement intentions from surface electromyography (sEMG) signals. However, due to the high complexity of upper-limb movemen...

The four-wheel-steering mobile robot (FMR) is widely applied in the manufacturing industry, where accurate and stable lateral motion control is a prerequisite for ensuring manufacturing quality and efficiency. However, serious time-varying perturbations such as system uncertainties and external disturbances usually lead to unsatisfactory control pe...

In this article, we propose a new iterative learning control (ILC) scheme for trajectory tracking of pneumatic muscle (PM) actuators with state constraints. A PM model is constructed in three-element form with both parametric and nonparametric uncertainties, while full state constraints are considered for enhancing operational safety. To ensure tha...