Cardiac Arrhythmia Detection using Artificial Neural Network
원문 초록
The prime purpose of this project is to develop a portable cardiac abnormality monitoring device which can drastically improvise the quality of the monitoring and the overall safety of the device. While a generic, low cost, wearable battery powered device for such applications may not yield sufficient performance, such devices combined with the capabilities of Artificial Neural Network algorithms can however, prove to be as competent as high end flexible and wearable monitoring devices fabricated using advanced manufacturing technologies. This paper evaluates the feasibility of the Levenberg-Marquardt ANN algorithm for use in any generic low power wearable devices implemented either as a pure real-time embedded system or as an IoT device capable of uploading the monitored readings to the cloud.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Enhancing Visual Inspection Capability of Multi-Modal Large Language Models on Medical Time Series with Supportive Conformalized and Interpretable Small Specialized Models
Finding "Good Views" of Electrocardiogram Signals for Inferring Abnormalities in Cardiac Condition
ECG Semantic Integrator (ESI): A Foundation ECG Model Pretrained with LLM-Enhanced Cardiological Text
Leveraging Visibility Graphs for Enhanced Arrhythmia Classification with Graph Convolutional Networks
Alternative Telescopic Displacement: An Efficient Multimodal Alignment Method
Evaluating Feature Attribution Methods for Electrocardiogram
토론
이 논문과 연결된 포럼 글이 아직 없습니다.