A Novel and Efficient Framework for Diagnosing ECG Signals Based on the Digital Signal Processing and Optimized Transformer Model

Дилемма массивных параметров сигналов ЭКГ является проблемой для современных методов их классификации. Большинство последних методов демонстрируют недостаточную эффективность диагностики сигналов ЭКГ в межпациентном режиме. В попытке справиться с вышеуказанными ограничениями данное исследование предлагает модель, которая использует оптимизированную структуру преобразователя для классификации сердечных сокращений в соответствии с «Ассоциацией по развитию медицинского оборудования, AAMI» и подчиняется условиям приема пациентов. Построена архитектура, названная оптимизированной сетью, для замены блока самообслуживания (SAU) в кодирующей части модели трансформера. Предлагаемая модель, включающая оптимизированную сеть, превосходит модель трансформера на основе САУ и требует меньше вычислений. Представлена надежная архитектура внедрения, основанная на сверточной нейронной сети (CNN) со схемой внимания на основе сети сжатия и возбуждения (SE), которая использовалась для взвешивания функций шаблона формы локального сердцебиения (LHSP). Проведено обширное тестирование для сравнения предложенной модели с существующими схемами. Тесты показали близость их результатов.

• Publication year

  2024

• Venue

  Radioelectronics Nanosystems Information Technologies

• Publication date

  2024-04-24

• Fields of study

  Not labeled

• Identifiers
  DOI 10.17725/rensit.2024.16.239
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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