Survey of machine learning techniques in the analysis of EEG signals for Parkinson's disease: A systematic review
Background: Parkinson's disease (PD) affects 7–10 million people worldwide. Its diagnosis
is clinical and can be supported by image-based tests, which are expensive and not always …
is clinical and can be supported by image-based tests, which are expensive and not always …
Machine learning approaches for detecting Parkinson's disease from EEG analysis: a systematic review
Background: Diagnosis of Parkinson's disease (PD) is mainly based on motor symptoms
and can be supported by imaging techniques such as the single photon emission computed …
and can be supported by imaging techniques such as the single photon emission computed …
Human attention recognition with machine learning from brain-EEG signals
Emotion recognition has always been a very popular field of research. Recently, EEG brain
waves are used to recognize the emotional states of a person. Attention level also plays an …
waves are used to recognize the emotional states of a person. Attention level also plays an …
Neural Reactivity to Haptics: Virtual Tasks versus Physical Tasks
YH Liu, R Vaitheeshwari, SC Yeh - IEEE Sensors Journal, 2024 - ieeexplore.ieee.org
This study investigates the effectiveness of haptic feedback in hand rehabilitation exercises,
within both virtual reality (VR) and real-world settings, to enhance upper limb functionality in …
within both virtual reality (VR) and real-world settings, to enhance upper limb functionality in …
Analysis of EEG signals using open BCI to predict the stress level
In recent days, mental health plays an important role in leading a peaceful life. When we
consider mental health, stress, anxiety, fear comes into picture. Most people experience …
consider mental health, stress, anxiety, fear comes into picture. Most people experience …
[PDF][PDF] Support vector machine approach for human identification based on EEG signals
The signals of the electroencephalogram (EEG) have been applied for detecting as well as
registering the electrical efficiency in the human brain. In this paper, EEG signals have been …
registering the electrical efficiency in the human brain. In this paper, EEG signals have been …
Investigation of Human Brain Waves (EEG) to Recognize Familiar and Unfamiliar Objects Based on Power Spectral Density Features
Research into the application of EEG technology for lie detection during interrogation has
gained significant popularity. However, no EEG method has yet proven to be entirely reliable …
gained significant popularity. However, no EEG method has yet proven to be entirely reliable …
[PDF][PDF] Exploring Non-Euclidean Approaches: A Comprehensive Survey on Graph-Based Techniques for EEG Signal Analysis
Electroencephalogram (EEG) signals are widely applied in emotion recognition, sentiment
analysis, disease classification, sleep disorder identification, and fatigue detection. Recent …
analysis, disease classification, sleep disorder identification, and fatigue detection. Recent …
Optimizing Machine Learning Pipelines: Scalable Mobile-Based Tamil Sign Language Recognition
B Sadhana, DVS Revanth… - 2024 IEEE North …, 2024 - ieeexplore.ieee.org
Signs are used by humans to communicate, bridging the communication barrier among the
general public and bridging the differences between the specially-abled. Human Translators …
general public and bridging the differences between the specially-abled. Human Translators …
[PDF][PDF] A Survey in Implementation and Applications of Electroencephalograph (EEG)-Based Brain-Computer Interface
The ability to control a vehicle using only your brain without moving any muscle contributes
a promising technique for our society [1], not least for people with a movement hindering …
a promising technique for our society [1], not least for people with a movement hindering …