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• W4313546989 abstract "IoT-empowered wearable multimodal monitoring system (IEMS), an IEMS for neurocritical care is developed to perform simultaneous monitoring of 8-channel electroencephalogram (EEG), 2-channel regional cerebral oxygen saturation (rSO2) based on near-infrared spectrum (NIRS), body surface temperature, electrocardiogram (ECG), photoplethysmography (PPG), and bioimpedance (Bio-Z). The IoT platform and wireless devices enable the patients’ signals available for remote diagnosis. Besides, analysis functions and artificial intelligence (AI) algorithms could be embedded in both the bedside platform and the cloud server to support physicians with clinical decisions. In the multimodal neural monitoring device, the following designs are adopted to face the neurological intensive care unit (NICU) application. Active electrodes and preamplifying free topology provide better signal quality and a larger dynamic range (DR). Dedicated low-power designs ensure the device lasts 10 h of operation. A nonwoven headset improves long-term wearability, which is also quick and easy to install. In the cardiovascular patch, the disposable electrode patch based on elastic materials ensures tight and comfortable contact with skin. Besides, the reusable wireless sensing module is tiny (20 mm <inline-formula xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink> <tex-math notation=LaTeX>$times16$ </tex-math></inline-formula> mm <inline-formula xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink> <tex-math notation=LaTeX>$times9$ </tex-math></inline-formula> mm) but could measure ECG, PPG, and Bio-Z simultaneously. Electrical tests and human subject (healthy volunteers and NICU patients) studies were conducted to examine the performance. The EEG channels show 130.75-dB DR and 0.84- <inline-formula xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink> <tex-math notation=LaTeX>$mu {}text{V}_{mathrm{ RMS}}$ </tex-math></inline-formula> input-referred noise, which also yields signals with high quality during human EEG monitoring. The NIRS channels exhibit good linearity and are able to operate under severe ambient interference. The temperature sensors show ±0.2 °C accuracy. Moreover, the system complies with mandatory standards for medical equipment. Overall, an IEMS can meet the requirements for NICU applications and could provide better comfort during long-term wearing." @default.
• W4313546989 created "2023-01-06" @default.
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• W4313546989 date "2023-01-15" @default.
• W4313546989 modified "2023-10-10" @default.
• W4313546989 title "IEMS: An IoT-Empowered Wearable Multimodal Monitoring System in Neurocritical Care" @default.
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• W4313546989 doi "https://doi.org/10.1109/jiot.2022.3210930" @default.
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