17757671. Electrocardiosignal Prediction Method and Apparatus, Terminal, and Storage Medium simplified abstract (HUAWEI TECHNOLOGIES CO., LTD.)
Electrocardiosignal Prediction Method and Apparatus, Terminal, and Storage Medium
Organization Name
Inventor(s)
Guangming Guo of Shenzhen (CN)
Electrocardiosignal Prediction Method and Apparatus, Terminal, and Storage Medium - A simplified explanation of the abstract
This abstract first appeared for US patent application 17757671 titled 'Electrocardiosignal Prediction Method and Apparatus, Terminal, and Storage Medium
Simplified Explanation
The patent application describes a method for predicting the occurrence of atrial fibrillation (AF) attacks in a target user based on their electrocardiosignal. Here is a simplified explanation of the abstract:
- The method involves obtaining the electrocardiosignal of a target user.
- The electrocardiosignal is then imported into a pre-trained atrial fibrillation signal classification model.
- The model determines the signal type of the electrocardiosignal, indicating whether it is indicative of atrial fibrillation or not.
- Based on the signal type, the method calculates a risk level of an atrial fibrillation occurrence.
- This risk level is used to predict whether the target user is likely to have an atrial fibrillation attack.
Potential applications of this technology:
- Medical diagnosis: The method can be used by healthcare professionals to predict the occurrence of atrial fibrillation attacks in patients, allowing for early intervention and treatment.
- Remote monitoring: The method can be implemented in wearable devices or remote monitoring systems to continuously monitor the electrocardiosignal of individuals at risk of atrial fibrillation, providing real-time alerts and improving patient care.
Problems solved by this technology:
- Early detection: By analyzing the electrocardiosignal, the method can identify the risk of atrial fibrillation attacks before they occur, enabling timely medical intervention and potentially preventing serious complications.
- Non-invasive monitoring: The method eliminates the need for invasive procedures or continuous hospitalization, allowing for convenient and cost-effective monitoring of atrial fibrillation.
Benefits of this technology:
- Improved patient care: By predicting atrial fibrillation attacks, healthcare providers can proactively manage patients' conditions, reducing the risk of complications and improving overall patient outcomes.
- Cost-effective monitoring: The method enables remote monitoring of atrial fibrillation, reducing the need for frequent hospital visits and lowering healthcare costs.
- Enhanced quality of life: Early detection and intervention can help individuals with atrial fibrillation lead a better quality of life by minimizing the impact of the condition on their daily activities.
Original Abstract Submitted
A method includes: obtaining an electrocardiosignal of a target user; importing the electrocardiosignal into a preset atrial fibrillation signal classification model, to obtain a signal type, of the electrocardiosignal, output by the atrial fibrillation signal classification model, where the atrial fibrillation signal classification model is obtained through training with an atrial fibrillation patient being a model training sample; and calculating, based on the signal type of the electrocardiosignal, a risk level of an atrial fibrillation occurrence, to predict whether the target user is to have an atrial fibrillation attack.
