التفاصيل البيبلوغرافية
| العنوان: |
An ECG Signal Acquisition and Analysis System Based on Machine Learning with Model Fusion |
| المؤلفون: |
Shi Su, Zhihong Zhu, Shu Wan, Fangqing Sheng, Tianyi Xiong, Shanshan Shen, Yu Hou, Cuihong Liu, Yijin Li, Xiaolin Sun, Jie Huang |
| المصدر: |
Sensors ; Volume 23 ; Issue 17 ; Pages: 7643 |
| بيانات النشر: |
Multidisciplinary Digital Publishing Institute |
| سنة النشر: |
2023 |
| المجموعة: |
MDPI Open Access Publishing |
| مصطلحات موضوعية: |
electrocardiogram, machine learning, model fusion, ECG, CNN |
| الوصف: |
Recently, cardiovascular disease has become the leading cause of death worldwide. Abnormal heart rate signals are an important indicator of cardiovascular disease. At present, the ECG signal acquisition instruments on the market are not portable and manual analysis is applied in data processing, which cannot address the above problems. To solve these problems, this study proposes an ECG acquisition and analysis system based on machine learning. The ECG analysis system responsible for ECG signal classification includes two parts: data preprocessing and machine learning models. Multiple types of models were built for overall classification, and model fusion was conducted. Firstly, traditional models such as logistic regression, support vector machines, and XGBoost were employed, along with feature engineering that primarily included morphological features and wavelet coefficient features. Subsequently, deep learning models, including convolutional neural networks and long short-term memory networks, were introduced and utilized for model fusion classification. The system’s classification accuracy for ECG signals reached 99.13%. Future work will focus on optimizing the model and developing a more portable instrument that can be utilized in the field. |
| نوع الوثيقة: |
text |
| وصف الملف: |
application/pdf |
| اللغة: |
English |
| العلاقة: |
https://dx.doi.org/10.3390/s23177643Test |
| DOI: |
10.3390/s23177643 |
| الإتاحة: |
https://doi.org/10.3390/s23177643Test |
| حقوق: |
https://creativecommons.org/licenses/by/4.0Test/ |
| رقم الانضمام: |
edsbas.F9041956 |
| قاعدة البيانات: |
BASE |
