Surface EMG signal classification using ternary pattern and discrete wavelet transform based feature extraction for hand movement recognition
Hands are two of the most crucial organs and they play major role for human activities.
Therefore, amputee people experience many difficulties in daily life. To overcome these …
Therefore, amputee people experience many difficulties in daily life. To overcome these …
Automatic diagnosis of glaucoma using two-dimensional Fourier-Bessel series expansion based empirical wavelet transform
PK Chaudhary, RB Pachori - Biomedical Signal Processing and Control, 2021 - Elsevier
Glaucoma is an eye disease in which fluid within the eye rises and puts pressure on optic
nerves. This fluid pressure slowly damages the optic nerves, and if it is left untreated, it may …
nerves. This fluid pressure slowly damages the optic nerves, and if it is left untreated, it may …
Comprehensive Review of Feature Extraction Techniques for sEMG Signal Classification: From Handcrafted Features to Deep Learning Approaches
SM Sid'El Moctar, I Rida, S Boudaoud - IRBM, 2024 - Elsevier
Surface Electromyography (sEMG) has become an essential tool in various fields, including
prosthetic control and clinical evaluation of the neuromusculoskeletal system. In recent …
prosthetic control and clinical evaluation of the neuromusculoskeletal system. In recent …
Automated detection of Parkinson's disease using minimum average maximum tree and singular value decomposition method with vowels
In this study, a novel method to automatically detect Parkinson's disease (PD) using vowels
is proposed. A combination of minimum average maximum (MAMa) tree and singular value …
is proposed. A combination of minimum average maximum (MAMa) tree and singular value …
Bearing fault diagnosis based on combined multi-scale weighted entropy morphological filtering and bi-LSTM
F Zou, H Zhang, S Sang, X Li, W He, X Liu - Applied Intelligence, 2021 - Springer
With the development of industry and technology, mechanical systems' safety has strong
relations with the diagnosis of bearing faults. Accurate fault diagnosis is essential for the …
relations with the diagnosis of bearing faults. Accurate fault diagnosis is essential for the …
Hand movement recognition from sEMG signals using Fourier decomposition method
Surface electromyogram (sEMG) provides a non-invasive way to collect EMG signals. The
sEMG signals acquired from the muscles of the forearm can be used to recognize the hand …
sEMG signals acquired from the muscles of the forearm can be used to recognize the hand …
A new framework for classification of multi-category hand grasps using EMG signals
Electromyogram (EMG) signals have had a great impact on many applications, including
prosthetic or rehabilitation devices, human-machine interactions, clinical and biomedical …
prosthetic or rehabilitation devices, human-machine interactions, clinical and biomedical …
Exploiting feature selection and neural network techniques for identification of focal and nonfocal EEG signals in TQWT domain
MT Sadiq, H Akbari, AU Rehman… - Journal of …, 2021 - Wiley Online Library
For drug resistance patients, removal of a portion of the brain as a cause of epileptic
seizures is a surgical remedy. However, before surgery, the detailed analysis of the epilepsy …
seizures is a surgical remedy. However, before surgery, the detailed analysis of the epilepsy …
Optimization of preprocessing stage in EEG based BCI systems in terms of accuracy and timing cost
E Dagdevir, M Tokmakci - Biomedical Signal Processing and Control, 2021 - Elsevier
Performance of the motor imagery-based brain computer interface (MI-BCI) systems has
been tried to improve by the researchers with novel approaches and methods used on …
been tried to improve by the researchers with novel approaches and methods used on …
A hand-modeled feature extraction-based learning network to detect grasps using sEMG signal
Recently, deep models have been very popular because they achieve excellent
performance with many classification problems. Deep networks have high computational …
performance with many classification problems. Deep networks have high computational …