Feature extraction and classification play an important role in brain–computer interface (BCI) systems. In traditional approaches, methods pattern recognition field are adopted to solve these problems. Nowadays, the deep learning theory has developed so fast that researchers have employed it many areas like computer vision speech recognition, which achieved remarkable results. However, few people introduce method into study of biomedical signals, especially EEG signals. this paper, a wavelet...

Brain-machine interface (BMI) can be used to control the robotic arm assist paralysis people for performing activities of daily living. However, it is still a complex task BMI users process objects grasping and lifting with arm. It hard achieve high efficiency accuracy even after extensive trainings. One important reason lacking sufficient feedback information user perform closed-loop control. In this study, we proposed method augmented reality (AR) guiding assistance provide enhanced visual...

Brain computer interface (BCI) adopts human brain signals to control external devices directly without using normal neural pathway. Recent study has explored many applications, such as controlling a teleoperation robot by electroencephalography (EEG) signals. However, utilizing the motor imagery EEG-based BCI perform for reach and grasp task still difficulties, especially in continuous multidimensional of tactile feedback. In this research, system with feedback was proposed. Firstly, mental...

The estimation of the grip force and 3D push-pull (push pull in three dimension space) from electromyogram (EMG) signal is great importance dexterous control EMG prosthetic hand. In this paper, an action method which based on eight channels surface (sEMG) Generalized Regression Neural Network (GRNN) proposed to meet requirements intelligent Firstly, experimental platform, acquisition sEMG, feature extraction sEMG construction GRNN are described. Then, multi-channels when hand moving captured...

Surface electromyography (sEMG) signals are widely used in the recognition of hand gestures. Nowadays, researchers usually increase number sEMG signal measurement positions and extract multiple features to improve accuracy. In this paper, we propose a position feature optimization strategy for gesture based on Analysis Variance (ANOVA) neural networks. Firstly, four channels raw acquired, time-domain extracted. Then different networks trained tested by using data sets which obtained...

Because of the absence visual perception, visually impaired individuals encounter various difficulties in their daily lives. This paper proposes a aid system designed specifically for individuals, aiming to assist and guide them grasping target objects within tabletop environment. The employs perception module that incorporates semantic SLAM algorithm, achieved through fusion ORB-SLAM2 YOLO V5s, enabling construction map In human–machine cooperation module, depth camera is integrated into...

The classification of motor imagery Electroencephalogram (EEG) the same limb is important for natural control neuroprosthesis. Due to close spatial representations on cortex area brain, discrimination different tasks challenging. In this paper, phase synchronization information was proposed classify EEG within limb. addition, non-portable compared with portable acquisition equipment purpose making brain computer interface (BCI) system more practical. case, average accuracy binary and 3-class...

Capturing finger joint angle information has important applications in human–computer interaction and hand function evaluation. In this paper, a novel wearable data glove is proposed for capturing angles. A sensing unit based on grating strip an optical detector specially designed measurement. To measure the angles of joints, 14 units are arranged back glove. There each middle phalange, proximal metacarpal finger, except thumb. For thumb, two distributed phalange metacarpal, respectively....

A novel series of cholesterol-based liquid crystalline (LC) dimers with a menthyl terminal group in the biphenyl base side have been synthesized. The chemical structures and LC properties this compounds are characterized by FT-IR, 1H-NMR, elemental analysis, hot-stage coupled polarizing microscopy differential scanning calorimetry. All exhibit enantiotropic mesophases. These dimesogenic short spacer chiral nematic LCs, while long spacers, they SmA LCs. Some these iridescent colors their...

The synthesis and material properties of a series new liquid crystalline compounds containing thioether cholesteryl, these homologues with different alkyl chain lengths 2–8, are reported. Thermal analysis shows that all oligomers have wide mesophase temperature ranges high thermal stability. were determined by differential scanning calorimetry (DSC) polarising optical microscopy (POM). molecule not only successfully exhibits strong rainbow colours, but also the cholesteric helical pitch...

To improve the control effectiveness and make prosthetic hand not only controllable but also perceivable, an EMG strategy was proposed in this paper. The consists of self-learning motion recognition, backstepping controller with stiffness fuzzy observation, force tactile representation. recognition is used to reduce influence on signals caused by uncertainty contacting position sensors. Backstepping observation realize grasp control. Velocity proportional free space tracking restricted can...

In traditional hand function assessment, patients and physicians always need to accomplish complex activities rating tasks. This paper proposes a novel wearable glove system for assessment. A sensing consisting of 12 nine-axis inertial magnetic unit (IMMU) sensors is used obtain the acceleration, angular velocity, geomagnetic orientation human movements. complementary filter algorithm applied calculate angles joints after sensor calibration. virtual model also developed map with in Unity...

Brain-computer interfaces (BCIs) have achieved successful control of assistive devices, e.g. neuroprosthesis or robotic arm. Previous research based on hand movements Electroencephalogram (EEG) has shown limited success in precise and natural control. In this study, we explored the possibilities decoding movement types kinematic information for three reach-and-execute actions using movement-related cortical potentials (MRCPs). EEG signals were acquired from 12 healthy subjects during...

Grasping is one of the most indispensable functions humans. Decoding reach-and-grasp actions from electroencephalograms (EEGs) great significance for realization intuitive and natural neuroprosthesis control, recovery or reconstruction hand patients with motor disorders. In this paper, we investigated decoding five different movements closely related to daily life using movement-related cortical potentials (MRCPs). experiment, nine healthy subjects were asked naturally execute on designed...

This paper introduces a novel capacitive sensor array designed for tactile perception applications. Utilizing an all-in-one inkjet deposition printing process, the exhibited exceptional flexibility and accuracy. With resolution of up to 32.7 dpi, was capable capturing fine details touch inputs, making it suitable applications requiring high spatial resolution. The design incorporates two multiplexers achieve scanning rate 100 Hz, ensuring rapid responsive data acquisition that is essential...