DETECTION OF CARDIAC ARREST BY WRIST WORN SENSOR (BLOOD FLOW SENSOR).

Registration ID: IJNRD_216913

Published ID: IJNRD2403672

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Y.Bhupesh, D.Srikanth

ECG, NON-INVASIVE BLOOD PRESSURE SENSOR, WRIST WORN, MACHINE LEARNING.

Cardiac arrest is a critical medical emergency that demands prompt intervention to prevent fatal outcomes. Timely detection of cardiac arrest is crucial for initiating life-saving measures. In recent years, wearable health monitoring devices have gained popularity due to their potential to continuously monitor vital signs and detect anomalies. This study presents a novel approach to detecting cardiac arrest using a wrist-worn sensor. The proposed system utilizes a combination of Heart Rate data, Blood pressure and ECG signals. By using Machine learning algorithms, such as neural networks and support vector machines, are employed to train the detection model using a dataset of simulated cardiac arrest events. The model is optimized to achieve high sensitivity and specificity in distinguishing between normal cardiac activity and sudden cardiac arrest episodes. Furthermore, the system incorporates a user-friendly interface and wireless connectivity features to facilitate seamless communication with healthcare providers and emergency services. Preliminary testing of the proposed detection system demonstrates promising results in terms of accuracy and reliability. However, further validation through clinical trials involving real-world scenarios is necessary to assess its efficacy in practical settings. If successful, the wrist-worn sensor could serve as a valuable tool for early detection and intervention in cases of cardiac arrest, potentially saving numerous lives by improving response times and outcomes.

Published Paper   E-Certificate

Y.Bhupesh & D.Srikanth (March-2024). DETECTION OF CARDIAC ARREST BY WRIST WORN SENSOR (BLOOD FLOW SENSOR).. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(3), g577-g613. https://ijnrd.org/papers/IJNRD2403672.pdf

Volume 9 Issue 3, March-2024

Pages : g577-g613

Paper Reg. ID: IJNRD_216913

Published Paper Id: IJNRD2403672

Downloads: 000122002

Research Area: Bio Medical Engineering 

Author Type: Indian Author

Country: Chennai, Tamil Nadu, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2403672.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2403672

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