Disposable Ai Integrated Cardiac Monitoring Patch For Real Time Detection Of Arrhythmias, Ischemia, And Cardiac Abnormalities With Enhanced Nursing Intervention And Patient Care
Disposable Ai Integrated Cardiac Monitoring Patch For Real Time Detection Of Arrhythmias, Ischemia, And Cardiac Abnormalities With Enhanced Nursing Intervention And Patient Care
Abstract:
The invention pertains to a disposable, AI-integrated cardiac monitoring patch
designed to provide continuous, real-time detection of cardiac abnormalities such
as arrhythmias and ischemia. This innovative wearable device utilizes advanced
artificial intelligence algorithms to analyze electrocardiographic (ECG) data,
facilitating predictive analytics and immediate alerts for healthcare providers. Its
design ensures patient comfort during prolonged wear and enhances nursing
interventions through seamless integration with mobile applications and cloud
based platforms. The patch features high-fidelity sensors for accurate data
collection, a lightweight and water-resistant design, and customizable alert
thresholds tailored to individual patient needs. This solution aims to significantly
improve patient outcomes by enabling early detection and timely medical response,
particularly for high-risk cardiac patients, thereby enhancing overall quality of care
in both clinical and home settings.
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Notices, Deadlines & Correspondence
Senior Tutor, Department of Medical Surgical Nursing, Sharda School of Nursing Science and Research, Sharda University
Inventors
1. IMRAN KHAN
Sharda University
Private university in Greater Noida, Uttar Pradesh PIN 201306.
2. Dr T David Ratna Paul
Associate Professor cum HOD MHN, Department of Mental Health Nursing, Sharda School of Nursing Science and Research, Sharda University
3. Dr Nitika Thakur
Associate Professor, Department of Child Health Nursing, Sharda School of Nursing Science and Research, Sharda University
4. Ms Nongmeikapam Helena
Associate Professor, Department of Child Health Nursing, Sharda School of Nursing Science and Research, Sharda University
5. Ms Soniya Sharma
Senior lecturer Department of Medical Surgical Nursing, Sharda School of Nursing Science and Research, Sharda University
6. Ms Ritu Verma
Assistant Professor, Department of Medical Surgical Nursing, Sharda School of Nursing Science and Research, Sharda University
7. Ms Pallavi Sharma
Assistant Professor, Department of Cardio-Vascular Technology Sharda School of Allied Health Science, Sharda University
8. Ms Subbu Laxshmi
Senior Tutor, Department of Medical Surgical Nursing, Sharda School of Nursing Science and Research, Sharda University
9. Ms M. C. Kniranda
Assistant Professor, Department of Child Health Nursing, Sharda School of Nursing Science and Research, Sharda University
10. Ms Neha Karan
Senior Tutor, Department of Community Health Nursing, Sharda School of Nursing Science and Research, Sharda University
11. Ms Sonia Lawai
Senior Tutor, Department of Obstetrics and Genecology, Sharda School of Nursing Science and Research, Sharda University
12. Ms Ankita Chhikara
Senior Tutor, Department of Medical Surgical Nursing, Sharda School of Nursing Science and Research, Sharda University
Specification
Description:This invention relates to the field of wearable medical devices specifically
designed for continuous cardiac monitoring. It emphasizes the integration of
artificial intelligence to enhance real-time detection of arrhythmias, ischemia, and
other cardiac abnormalities. , Claims:Claim 1: A disposable cardiac monitoring patch comprising an AI-driven
processor for real-time detection of cardiac abnormalities.
Claim 2: The patch of claim 1, wherein the AI system predicts future
cardiac events based on continuous monitoring of ECG data.
Claim 3: The patch of claim 1, further comprising a wireless communication
module for transmitting data to mobile devices or a cloud server.
Claim 4: A method for enhancing nursing intervention through real-time
alerts, wherein the patch monitors a patient’s cardiac activity and notifies
healthcare providers of abnormalities.
Documents
Application Documents
#
Name
Date
1
202411091459-Sequence Listing in PDF [24-11-2024(online)].pdf
2024-11-24
2
202411091459-REQUEST FOR EARLY PUBLICATION(FORM-9) [24-11-2024(online)].pdf