Biomedical signals and machine learning in amyotrophic lateral sclerosis: a systematic review
Introduction The use of machine learning (ML) techniques in healthcare encompasses an
emerging concept that envisages vast contributions to the tackling of rare diseases. In this …
emerging concept that envisages vast contributions to the tackling of rare diseases. In this …
Multivariate approach for Alzheimer's disease detection using stationary wavelet entropy and predator-prey particle swarm optimization
Background: The number of patients with Alzheimer's disease is increasing rapidly every
year. Scholars often use computer vision and machine learning methods to develop an …
year. Scholars often use computer vision and machine learning methods to develop an …
[PDF][PDF] Classification of hand movements based on discrete wavelet transform and enhanced feature extraction
Extraction of potential electromyography (EMG) features has become one of the important
roles in EMG pattern recognition. In this paper, two EMG features, namely, enhanced …
roles in EMG pattern recognition. In this paper, two EMG features, namely, enhanced …
Wearable multi-sensor data fusion approach for human activity recognition using machine learning algorithms
B Vidya, P Sasikumar - Sensors and Actuators A: Physical, 2022 - Elsevier
Wearable sensor based human activity recognition (HAR) has a broad range of applications
in healthcare, fitness, smart home, and surveillance. In spite of the substantial amount of …
in healthcare, fitness, smart home, and surveillance. In spite of the substantial amount of …
Single-channel EMG classification with ensemble-empirical-mode-decomposition-based ICA for diagnosing neuromuscular disorders
An accurate and computationally efficient quantitative analysis of electromyography (EMG)
signals plays an inevitable role in the diagnosis of neuromuscular disorders, prosthesis, and …
signals plays an inevitable role in the diagnosis of neuromuscular disorders, prosthesis, and …
Neuromuscular disorders detection through time-frequency analysis and classification of multi-muscular EMG signals using Hilbert-Huang transform
JR Torres-Castillo, CO Lopez-Lopez… - … Signal Processing and …, 2022 - Elsevier
Electromyographic (EMG) signal analysis plays a vital role in diagnosing neuromuscular
disorders (NMD). It is based on the clinician's experience in interpreting the signal's shape …
disorders (NMD). It is based on the clinician's experience in interpreting the signal's shape …
Classification of amyotrophic lateral sclerosis disease based on convolutional neural network and reinforcement sample learning algorithm
Electromyogram (EMG) signals contain useful information of the neuromuscular diseases
like amyotrophic lateral sclerosis (ALS). ALS is a well-known brain disease, which can …
like amyotrophic lateral sclerosis (ALS). ALS is a well-known brain disease, which can …
[HTML][HTML] Machine learning-based diabetic neuropathy and previous foot ulceration patients detection using electromyography and ground reaction forces during gait
Diabetic neuropathy (DN) is one of the prevalent forms of neuropathy that involves
alterations in biomechanical changes in the human gait. Diabetic foot ulceration (DFU) is …
alterations in biomechanical changes in the human gait. Diabetic foot ulceration (DFU) is …
Feature extraction of surface electromyography (sEMG) and signal processing technique in wavelet transform: A review
N Burhan, R Ghazali - 2016 IEEE International Conference …, 2016 - ieeexplore.ieee.org
Electromyography (EMG) is used to measure and keep information of the electrical activity
that produced by muscles during contract and relax. The electrical activity is detected with …
that produced by muscles during contract and relax. The electrical activity is detected with …
An embedded, eight channel, noise canceling, wireless, wearable sEMG data acquisition system with adaptive muscle contraction detection
M Ergeneci, K Gokcesu, E Ertan… - IEEE transactions on …, 2017 - ieeexplore.ieee.org
Wearable technology has gained increasing popularity in the applications of healthcare,
sports science, and biomedical engineering in recent years. Because of its convenient …
sports science, and biomedical engineering in recent years. Because of its convenient …