Oğul ÜNAL - Academia.edu (original) (raw)

Papers by Oğul ÜNAL

Research paper thumbnail of Analysis of Acute Myocardial Infarction using ECG Signals and Machine Learning Algorithms

Annals of DAAAM for ... & proceedings of the ... International DAAAM Symposium .., 2022

Heart attack, alternatively known as myocardial infarction (MI), covers various conditions that i... more Heart attack, alternatively known as myocardial infarction (MI), covers various conditions that impact the heart and is one of the most common causes of death worldwide. Electrocardiogram (ECG) can be used as a way to examine the functionality of the cardiovascular system. Researchers apply several machine learning techniques to analyze medical data, helping healthcare professionals to predict heart diseases. The focus of most studies has been on classifying heartbeats or classifying healthy ECG signals on a dataset. In this paper, we propose two methods based on machine learning algorithms for the classification of healthy subjects, subjects who have a myocardial infarction, and analysis of ST elevated (STEMI) or non-ST elevated MI (NSTEMI). We evaluated the proposed method on PhysionNet's PTB Diagnostics dataset. The suggested method can make predictions with accuracies of 95.29% and 82.93% on healthy-MI classification and STEMI-NSTEMI classification, respectively.

Research paper thumbnail of Analysis of Emotions using EEG Data and Machine Learning

Proceedings of the 32nd International DAAAM Symposium 2021, 2021

Emotions might be one of the most significant differences between a machine and a human being. Cu... more Emotions might be one of the most significant differences between a machine and a human being. Currently, Machine Learning can learn and make predictions using Data in many different fields such as Medicine. In this paper, the goal is to evaluate how human emotions are being executed then test the performance of ML in terms of Emotion analysis. DREAMER Data was used to perform all the tasks. The classification of rankings for 23 subjects' was done. The reactions of subjects and EEG data were recorded while 23 participants were watching 18 different short movies. Each candidate has a ranking, between one to five, based on their affective state after each stimuli in terms of valence, arousal, and dominance. Afterward, Using Generative Adversarial Network (GAN), synthetic data will be created and analysed using supervised and unsupervised learning algorithms. Finally, all results will be compared. The research can help to evaluate the basic human emotions for robots or devices in Medicine. Robotics or cyber-physical machines in healthcare are already growing every day therefore, the quality of surgeries, treatments, or medical assistance can be improved.

Research paper thumbnail of Development of Machine Learning Models to Determine Hand Gestures using EMG Signals

DAAAM Proceedings, 2020

The connection between the human body and science is still growing exponentially. The human body ... more The connection between the human body and science is still growing exponentially. The human body has many mysteries. The more we learn about them, the better we improve our scientific perspectives. In this case, the analysis of EMG (Electromyographic) signals gives the possibility the use the EMG data to perform classification tasks. Machine Learning models and Neural Networks are the best tools to classify different hand gestures using the dataset. This work aims to analyse the characteristics of EMG signals and use the EMG dataset to perform different ML models. The results will be used in robotic fields and control systems as future work. In this project, the Python programming language is used. The dataset was recorded using an MYO Thalmic bracelet. The number of instances is about 40000-50000 recordings in each column (channels). There are six different hand gestures tasks recorded in the dataset that are; hand clenched in a fist, wrist extension, wrist flexion, hand radial deviations, hand ulnar deviations, hand extended palm. The study of ML models and using gestures to control robotic devices could be useful in industrial spheres. A person may use a forearm bracelet to use it in industrial operations. Another purpose of this paper is; helping people who lost their hands. With the help of robotic arm plugged-in to their forearm and EMG device, they might be able to perform several hand-gestures.

Research paper thumbnail of Analysis of Acute Myocardial Infarction using ECG Signals and Machine Learning Algorithms

Annals of DAAAM for ... & proceedings of the ... International DAAAM Symposium .., 2022

Heart attack, alternatively known as myocardial infarction (MI), covers various conditions that i... more Heart attack, alternatively known as myocardial infarction (MI), covers various conditions that impact the heart and is one of the most common causes of death worldwide. Electrocardiogram (ECG) can be used as a way to examine the functionality of the cardiovascular system. Researchers apply several machine learning techniques to analyze medical data, helping healthcare professionals to predict heart diseases. The focus of most studies has been on classifying heartbeats or classifying healthy ECG signals on a dataset. In this paper, we propose two methods based on machine learning algorithms for the classification of healthy subjects, subjects who have a myocardial infarction, and analysis of ST elevated (STEMI) or non-ST elevated MI (NSTEMI). We evaluated the proposed method on PhysionNet's PTB Diagnostics dataset. The suggested method can make predictions with accuracies of 95.29% and 82.93% on healthy-MI classification and STEMI-NSTEMI classification, respectively.

Research paper thumbnail of Analysis of Emotions using EEG Data and Machine Learning

Proceedings of the 32nd International DAAAM Symposium 2021, 2021

Emotions might be one of the most significant differences between a machine and a human being. Cu... more Emotions might be one of the most significant differences between a machine and a human being. Currently, Machine Learning can learn and make predictions using Data in many different fields such as Medicine. In this paper, the goal is to evaluate how human emotions are being executed then test the performance of ML in terms of Emotion analysis. DREAMER Data was used to perform all the tasks. The classification of rankings for 23 subjects' was done. The reactions of subjects and EEG data were recorded while 23 participants were watching 18 different short movies. Each candidate has a ranking, between one to five, based on their affective state after each stimuli in terms of valence, arousal, and dominance. Afterward, Using Generative Adversarial Network (GAN), synthetic data will be created and analysed using supervised and unsupervised learning algorithms. Finally, all results will be compared. The research can help to evaluate the basic human emotions for robots or devices in Medicine. Robotics or cyber-physical machines in healthcare are already growing every day therefore, the quality of surgeries, treatments, or medical assistance can be improved.

Research paper thumbnail of Development of Machine Learning Models to Determine Hand Gestures using EMG Signals

DAAAM Proceedings, 2020

The connection between the human body and science is still growing exponentially. The human body ... more The connection between the human body and science is still growing exponentially. The human body has many mysteries. The more we learn about them, the better we improve our scientific perspectives. In this case, the analysis of EMG (Electromyographic) signals gives the possibility the use the EMG data to perform classification tasks. Machine Learning models and Neural Networks are the best tools to classify different hand gestures using the dataset. This work aims to analyse the characteristics of EMG signals and use the EMG dataset to perform different ML models. The results will be used in robotic fields and control systems as future work. In this project, the Python programming language is used. The dataset was recorded using an MYO Thalmic bracelet. The number of instances is about 40000-50000 recordings in each column (channels). There are six different hand gestures tasks recorded in the dataset that are; hand clenched in a fist, wrist extension, wrist flexion, hand radial deviations, hand ulnar deviations, hand extended palm. The study of ML models and using gestures to control robotic devices could be useful in industrial spheres. A person may use a forearm bracelet to use it in industrial operations. Another purpose of this paper is; helping people who lost their hands. With the help of robotic arm plugged-in to their forearm and EMG device, they might be able to perform several hand-gestures.