From classic motor imagery to complex movement intention decoding: the noninvasive Graz-BCI approach
In this chapter, we give an overview of the Graz-BCI research, from the classic motor
imagery detection to complex movement intentions decoding. We start by describing the …
imagery detection to complex movement intentions decoding. We start by describing the …
Selection of features and classifiers for EMG-EEG-based upper limb assistive devices—A review
Bio-signals are distinctive factors in the design of human-machine interface, essentially
useful for prosthesis, orthosis, and exoskeletons. Despite the progress in the analysis of …
useful for prosthesis, orthosis, and exoskeletons. Despite the progress in the analysis of …
Attempted arm and hand movements can be decoded from low-frequency EEG from persons with spinal cord injury
We show that persons with spinal cord injury (SCI) retain decodable neural correlates of
attempted arm and hand movements. We investigated hand open, palmar grasp, lateral …
attempted arm and hand movements. We investigated hand open, palmar grasp, lateral …
Temporal-spatial convolutional residual network for decoding attempted movement related EEG signals of subjects with spinal cord injury
Abstract Brain Computer Interface (BCI) offers a promising approach to restoring hand
functionality for people with cervical spinal cord injury (SCI). A reliable classification of brain …
functionality for people with cervical spinal cord injury (SCI). A reliable classification of brain …
Sitting and standing intention can be decoded from scalp EEG recorded prior to movement execution
Low frequency signals recorded from non-invasive electroencephalography (EEG), in
particular movement-related cortical potentials (MRPs), are associated with preparation and …
particular movement-related cortical potentials (MRPs), are associated with preparation and …
Decoding imagined 3D hand movement trajectories from EEG: evidence to support the use of mu, beta, and low gamma oscillations
Objective: To date, motion trajectory prediction (MTP) of a limb from non-invasive
electroencephalography (EEG) has relied, primarily, on band-pass filtered samples of EEG …
electroencephalography (EEG) has relied, primarily, on band-pass filtered samples of EEG …
A framework for interactive mindfulness meditation using attention-regulation process
K Salehzadeh Niksirat, C Silpasuwanchai… - Proceedings of the …, 2017 - dl.acm.org
We are often overwhelmed by everyday stressors. Mindfulness meditation can help slow
things down and bring one's attention into the present moment. Given the prevalence of …
things down and bring one's attention into the present moment. Given the prevalence of …
Compartmentalized dynamics within a common multi-area mesoscale manifold represent a repertoire of human hand movements
The human hand is unique in the animal kingdom for unparalleled dexterity, ranging from
complex prehension to fine finger individuation. How does the brain represent such a …
complex prehension to fine finger individuation. How does the brain represent such a …
Global cortical activity predicts shape of hand during grasping
Recent studies show that the amplitude of cortical field potentials is modulated in the time
domain by grasping kinematics. However, it is unknown if these low frequency modulations …
domain by grasping kinematics. However, it is unknown if these low frequency modulations …
Early prediction model for coronary heart disease using genetic algorithms, hyper-parameter optimization and machine learning techniques
SV Jinny, YV Mate - Health and Technology, 2021 - Springer
Abstract Coronary Heart Disease (CHD) is one of the major causes of morbidity and
mortality worldwide. According to the World Health Organization (WHO) survey, Cardiac …
mortality worldwide. According to the World Health Organization (WHO) survey, Cardiac …