Key result
Advancements in respiratory sensor technologies, including AI, IoT, and non-contact solutions like RIP and mmTAA, demonstrate transformative potential for patient diagnosis and monitoring.
Systematic Review
Recent advancements in respiratory sensor technologies, including wearables and non-contact systems, offer precise monitoring capabilities for diagnostics and healthcare optimization.
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Advanced sensors enable real-time monitoring; extends integration into cardiovascular diagnostics and trials.
Between 2018 and 2024, the global market has experienced significant advancements in sensor technologies for monitoring patients' health conditions, which have demonstrated a pivotal role in diagnostics, treatment monitoring, and healthcare optimization. Progress in microelectronics, device miniaturization, and wireless communication technologies has facilitated the development of sophisticated sensors, including wearable devices such as smartwatches and fitness trackers, enabling the real-time monitoring of key health parameters. These devices are widely employed across clinical settings, nursing care, and daily life to collect critical data on vital signs, including heart rate, blood pressure, oxygen saturation, and respiratory rate. A systematic review of the developments within this period highlights the transformative potential of AI and IoT-based technologies in healthcare personalization, particularly in disease symptom prediction and public health management. Furthermore, innovative techniques such as respiratory inductive plethysmography (RIP) and millimeter-wave radar systems (mmTAA) have emerged as precise, non-contact solutions for respiratory monitoring, with applications spanning diagnostics, therapeutic interventions, and enhanced safety in daily life.
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Karpiel et al. (2025) conducted a systematic review in Respiratory monitoring. Respiratory sensor solutions (wearables, AI, IoT, RIP, mmTAA) was evaluated. Advancements in respiratory sensor technologies, including AI, IoT, and non-contact solutions like RIP and mmTAA, demonstrate transformative potential for patient diagnosis and monitoring.
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