SADIT-MAR COURSE-7: Wearable Technology and Real-Time Health Monitoring for Maritime Workers

SADIT-MAR lecture titled "Wearable Technology and Real-Time Health Monitoring for Maritime Workers" by Dr. Mariel Alfaro Ponce, presenting a state-of-the-art review built on seven recent studies, ranging from low-cost Arduino prototypes to a US Navy deployment of 845 sailors, on how wearables can monitor seafarer health in real time. The lecture emphasizes that maritime work differs fundamentally from land-based settings, with isolation, confined quarters, and environments hostile to electronics, so consumer wearables do not translate cleanly, and it outlines a five-stage Human Digital Healthcare Engineering pipeline covering sensing, transmission, human digital twins, AI-driven diagnostics, and predictive analysis. Drawing on evidence at the engineering, clinical pilot, and fleet scales, it shows that feasibility can be achieved, with user feedback driving sustained use more than battery life. The lecture highlights that challenges remain, including resource constraints, privacy and data governance, and monitoring-induced stress, and that the field is still answering feasibility rather than effectiveness.

Key topics covered in the lecture include

• Health monitoring targets are defined across three categories: physiological vital signs; psychological indicators such as stress and fatigue; and comfort factors like thermal and vibration comfort, with mental health noted as one of the most under-monitored areas among seafarers.
• Maritime-specific device requirements are presented as essential design constraints, including waterproofing, EMI resistance, vibration tolerance, low power consumption, and corrosion resistance, with optical fiber sensing highlighted as a promising next-generation substrate.
• Data transmission is described across two stages: onboard networks such as UWB, Zigbee, Wi-Fi, and Bluetooth, and ship-to-shore communication via low Earth orbit satellites, whose falling costs make continuous monitoring of distant vessels increasingly feasible.
• Human digital twins and artificial intelligence are highlighted as the analytical core, enabling simulation, personalization, and prediction, while very high accuracy figures are treated with caution due to overfitting and limited generalization across populations.
• Field evidence is emphasized across engineering, clinical pilot, and fleet scales, including an offshore diver device, a triboelectric gait-sensing mat, a Korean pilot study, and the US Navy deployment, showing that feasibility can be achieved while effectiveness remains an open question.