Diseño de un sistema de monitoreo de salud para astronautas basado en inteligencia artificial

Objective. To design a health monitoring system for astronauts through the integration of the artificial intelligence (AI) and biomedical sensors. Methods. A experimental type study was developed. The population consisted of simulated data of astronauts and the sample was obtained through the intentioned selection of critical biometric parameters. The data was collected using a set of sensors EEG, EMG, and optics, integrated in a smart suit. The signals were processed in real time through a central module with technology ESP32 and the use of neural networks RNN-CNN for the analysis were proposed. Results. An AI architecture is proposed that, theoretically, it could achieve 90% accuracy in detecting potential diseases. The system presented a data transmission rate of 1.5 kbps and a latency of < 100 ms, which would allow real-time monitoring. Conclusions. The system developed has the potential to be effective for the early detection of alterations in the health of astronauts, showing its capacity for safeguarding the safety of space missions

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Publication Details

Journal
Revista Peruana de Ingeniería Arquitectura y Medio Ambiente
Published
2024-08-12
DOI
https://doi.org/10.37711/repiama.2024.1.2.4
Primary Topic
Space Exploration and Technology
Type
article
Field-Weighted Citation Impact
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article

Diseño de un sistema de monitoreo de salud para astronautas basado en inteligencia artificial

Nataly Andrea Rojas Barnett, Hanks Jeremy Reyes Huaman, Rivaldo Carlos Duran Aquino
Revista Peruana de Ingeniería Arquitectura y Medio Ambiente
Space Exploration and Technology
article

Diseño de un sistema de monitoreo de salud para astronautas basado en inteligencia artificial

Nataly Andrea Rojas Barnett, Hanks Jeremy Reyes Huaman, Rivaldo Carlos Duran Aquino
article en

Abstract

Objective. To design a health monitoring system for astronauts through the integration of the artificial intelligence (AI) and biomedical sensors. Methods. A experimental type study was developed. The population consisted of simulated data of astronauts and the sample was obtained through the intentioned selection of critical biometric parameters. The data was collected using a set of sensors EEG, EMG, and optics, integrated in a smart suit. The signals were processed in real time through a central module with technology ESP32 and the use of neural networks RNN-CNN for the analysis were proposed. Results. An AI architecture is proposed that, theoretically, it could achieve 90% accuracy in detecting potential diseases. The system presented a data transmission rate of 1.5 kbps and a latency of < 100 ms, which would allow real-time monitoring. Conclusions. The system developed has the potential to be effective for the early detection of alterations in the health of astronauts, showing its capacity for safeguarding the safety of space missions

Revista Peruana de Ingeniería Arquitectura y Medio AmbienteVol. 1(2)
National University of San Marcos (PE)
Openalex Percentile: Top 47%
Space Exploration and Technology
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