Astronautics also outlines unique biological and cognitive obstacles that demand advancements in health monitoring and techniques for risk prevention for space travellers. This study investigates the consequences of microgravity, space radiation and persistent confinement on astronaut well-being, focusing on cardiovascular, musculoskeletal, neurological and immune system vulnerability. Cardiovascular ailment, a major concern, is monitored using clinical prediction models (CPMs) that combine traditional risk factors, biomarkers and machine learning techniques. Additionally, AI-powered methods consisting of GPT-based models and time series transformers are required for real-time health monitoring and analytical assessment. Test-based outcomes illustrate that models such as logistic regression, random forest and support vector machines attain high designation accuracy in defining astronauts’ health hazards from non-astronaut data. Furthermore, wearable medical trackers and space-sourced clinical techniques are detected as an alternative solution for both space missions and terrestrial well-being. The study also highlights the need for perpetual advancements in zero gravity to protect astronauts’ well-being and enhance medicinal solutions for upcoming space travels.

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Advancements in Astronaut Health Monitoring Technologies

  • Gunjan Shinde,
  • Garima Anand,
  • Prateek Singhal

摘要

Astronautics also outlines unique biological and cognitive obstacles that demand advancements in health monitoring and techniques for risk prevention for space travellers. This study investigates the consequences of microgravity, space radiation and persistent confinement on astronaut well-being, focusing on cardiovascular, musculoskeletal, neurological and immune system vulnerability. Cardiovascular ailment, a major concern, is monitored using clinical prediction models (CPMs) that combine traditional risk factors, biomarkers and machine learning techniques. Additionally, AI-powered methods consisting of GPT-based models and time series transformers are required for real-time health monitoring and analytical assessment. Test-based outcomes illustrate that models such as logistic regression, random forest and support vector machines attain high designation accuracy in defining astronauts’ health hazards from non-astronaut data. Furthermore, wearable medical trackers and space-sourced clinical techniques are detected as an alternative solution for both space missions and terrestrial well-being. The study also highlights the need for perpetual advancements in zero gravity to protect astronauts’ well-being and enhance medicinal solutions for upcoming space travels.