IEEE Transactions on Neural Systems and Rehabilitation Engineering

Surface Electromyography (sEMG) signals are widely used as input to control robotic devices, prosthetic limbs, exoskeletons, among other devices, and provide information about someone's intention to perform a particular movement. However, the redundant action of 32 muscles in the forearm and hand means that the neuromotor system can select different combinations of muscular activities to perform the same grasp, and these combinations could differ among subjects, and even among the trials done by the same subject...

The motor imagery brain-computer interface (MI-BCI) based on electroencephalography (EEG) is a widely used human-machine interface paradigm. However, due to the non-stationarity and individual differences among subjects in EEG signals, the decoding accuracy is limited, affecting the application of the MI-BCI. In this paper, we propose the EISATC-Fusion model for MI EEG decoding, consisting of inception block, multi-head self-attention (MSA), temporal convolutional network (TCN), and layer fusion. Specifically, we design a DS Inception block to extract multi-scale frequency band information...

Exoskeletons are a burgeoning technology with many possible applications to improve human life; focusing the effort of exoskeleton research and development on the most important features is essential for facilitating adoption and maximizing positive societal impact. To identify important focus areas for exoskeleton research and development, we conducted a survey with 154 potential users (older adults) and another survey with 152 clinicians. The surveys were conducted online and to ensure a consistent concept of an exoskeleton across respondents, an image of a hip exoskeleton was shown during exoskeleton-related prompts...

The magnetoencephalogram (MEG) based on array optically pumped magnetometers (OPMs) has the potential of replacing conventional cryogenic superconducting quantum interference device. Phase synchronization is a common method for measuring brain oscillations and functional connectivity. Verifying the feasibility and fidelity of OPM-MEG in measuring phase synchronization will help its widespread application in the study of aforementioned neural mechanisms. The analysis method on source-level time series can weaken the influence of instantaneous field spread effect...

The electroencephalogram-based (EEG) brain-computer interface (BCI) has garnered significant attention in recent research. However, the practicality of EEG remains constrained by the lack of efficient EEG decoding technology. The challenge lies in effectively translating intricate EEG into meaningful, generalizable information. EEG signal decoding primarily relies on either time domain or frequency domain information. There lacks a method capable of simultaneously and effectively extracting both time and frequency domain features, as well as efficiently fuse these features...

Joint hyper-resistance is a common symptom in neurological disorders. It has both neural and non-neural origins, but it has been challenging to distinguish different origins based on clinical tests alone. Combining instrumented tests with parameter identification based on a neuromechanical model may allow us to dissociate the different origins of joint hyper-resistance in individual patients. However, this requires that the model captures the underlying mechanisms. Here, we propose a neuromechanical model that, in contrast to previously proposed models, accounts for muscle short-range stiffness (SRS) and its interaction with muscle tone and reflex activity...

Individuals with Parkinson's disease (PD) are characterized by gait and balance disorders limiting their independence and quality of life. Home-based rehabilitation programs, combined with drug therapy, demonstrated to be beneficial in the daily-life activities of PD subjects. Sensorized shoes can extract balance- and gait-related data in home-based scenarios and allow clinicians to monitor subjects' activities. In this study, we verified the capability of a pair of sensorized shoes (including pressure-sensitive insoles and one inertial measurement unit) in assessing ground-level walking and body weight shift exercises...

Continuous Theta Burst Stimulation (cTBS) has been shown to modulate cortical oscillations and induce cortical inhibitory effects. Electroencephalography (EEG) studies have shown some immediate effects of cTBS on brain activity. To investigate both immediate effects and short-term effects of cTBS on dynamic brain changes, cTBS was applied to 22 healthy participants over their left motor cortex. We recorded eyes-open, resting-state EEG and performance in the Nine-Hole Peg Test (NHPT) before cTBS, immediately after cTBS, and 80 minutes after cTBS...

The primary goal of rehabilitation for individuals with lower limb amputation, particularly those with unilateral transfemoral amputation (uTFA), is to restore their ability to walk independently. Effective control of the center of pressure (COP) during gait is vital for maintaining balance and stability, yet it poses a significant challenge for individuals with uTFA. This study aims to study the COP during gait in individuals with uTFA and elucidate their unique compensatory strategies. This study involved 12 uTFA participants and age-matched non-disabled controls, with gait and COP trajectory data collected using an instrumented treadmill...

Steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs) have gained significant attention in recent years due to their advantages, including high communication rates, short calibration times, and high signal-to-noise ratios. However, one of the major challenges in practical application is performance degradation due to fatigue during continuous and prolonged use. This study aims to mitigate the negative effects of fatigue on SSVEP-BCI performance by adjusting data lengths and updating detection models using dynamic stopping strategy...

Research suggests that structural and functional changes within the brain are associated with chronic low back pain, and these cortical alterations might contribute to impaired sensorimotor control of the trunk and hips in this population. However, linking sensorimotor brain changes with altered movement of the trunk and hips during task-based neuroimaging presents significant challenges. An MRI-safe pressure measurement system was developed to ensure proper task completion during neuroimaging by capturing movement patterns of the trunk (sensors under the lower back) and hips (sensors embedded in the foam roll under the knees)...

Sensorimotor impairment is a prevalent condition requiring effective rehabilitation strategies. This study introduces a novel wearable device for Mindful Sensorimotor Training (MiSMT) designed for sensory and motor rehabilitation. Our MiSMT device combines motor training using myoelectric pattern recognition along sensory training using two tactile displays. This device offers a comprehensive solution, integrating electromyography and haptic feedback, lacking in existing devices. The device features eight electromyography channels, a rechargeable battery, and wireless Bluetooth or Wi-Fi connectivity for seamless communication with a computer or mobile device...

Brain-computer interfaces (BCIs) are anticipated to improve the efficacy of rehabilitation for people with motor disabilities. However, applying BCI in clinical practice is still a challenge due to the great diversity of patients. In the current study, a novel action observation (AO) based BCI was proposed and tested on stroke patients. Ten non-hemineglect patients and ten hemineglect patients were recruited. Four AO stimuli were designed, each presenting a decomposed action to complete the reach-and-grasp task...

Depression ranks among the most prevalent mood-related psychiatric disorders. Existing clinical diagnostic approaches relying on scale interviews are susceptible to individual and environmental variations. In contrast, the integration of neuroimaging techniques and computer science has provided compelling evidence for the quantitative assessment of major depressive disorder (MDD). However, one of the major challenges in computer-aided diagnosis of MDD is to automatically and effectively mine the complementary cross-modal information from limited datasets...

Reducing energy consumption during walking is a critical goal for transtibial amputees. The study presents the evaluation of a semi-active prosthesis with five transtibial amputees. The prosthesis has a low-power actuator integrated in parallel into an energy-storing-and-releasing foot. The actuator is controlled to compress the foot during the stance phase, supplementing the natural compression due to the user's dynamic interaction with the ground, particularly during the ankle dorsiflexion phase, and to release the energy stored in the foot during the push-off phase, to enhance propulsion...

Motor brain-computer interfaces (BCIs) have gained growing research interest in motor rehabilitation, restoration, and prostheses control. Decoding upper-limb movement direction with noninvasive BCIs has been extensively investigated. However, few of them address the intervention of cognitive distraction that impairs decoding performance in practice. In this study, we propose a novel decoding model with invariant patterns in embedding manifold on a mixed dataset pooled from electroencephalograph (EEG) signals under different attentional states...

Nowadays, numerous countries are facing the challenge of aging population. Additionally, the number of people with reduced mobility due to physical illness is increasing. In response to this issue, robots used for walking assistance and sit-to-stand (STS) transition have been introduced in nursing to assist these individuals with walking. Given the shared characteristics of these robots, this paper collectively refers to them as Walking Support Robots (WSR). Additionally, service robots with assisting functions have been included in the scope of this review...

BACKGROUND: Cognitive impairment is one of the most common non-motor symptoms of Parkinson's disease (PD). Previous studies have demonstrated that low-intensity transcranial ultrasound stimulation can significantly suppress the motor symptoms of PD. However, whether ultrasound stimulation can improve cognitive ability in PD and the related neural oscillation mechanism remain unclear to date. OBJECTIVE: To evaluate the effect of ultrasound stimulation on memory ability in PD and explore its neural oscillation mechanism...

Functional near-infrared spectroscopy (fNIRS) seems opportune for neurofeedback in robot-assisted rehabilitation training due to its noninvasive, less physical restriction, and no electromagnetic disturbance. Previous research has proved the cross-session reliability of fNIRS responses to non-motor tasks (e.g., visual stimuli) and fine-motor tasks (e.g., finger tapping). However, it is still unknown whether fNIRS responses remain reliable 1) in gross-motor tasks, 2) within a training session, and 3) for different training parameters...

Depression is one of the most serious mental disorders affecting modern human life and is often caused by chronic stress. Dopamine system dysfunction is proposed to contribute to the pathophysiology of chronic stress, especially the ventral tegmental area (VTA) which mainly consists of dopaminergic neurons. Focused ultrasound stimulation (FUS) is a promising neuromodulation modality and multiple studies have demonstrated effective ultrasonic activation of cortical, subcortical, and related networks. However, the effects of FUS on the dopamine system and the potential link to chronic stress-induced depressive behaviors are relatively unknown...