Publications by authors named "Taehwan Roh"

Background: Cardiovascular disease is the leading cause of death worldwide. Early recognition, diagnosis, and reperfusion are the key elements of treatment for ST-segment elevation myocardial infarction. The absence of a prehospital 12-lead electrocardiogram (P12ECG) can cause definitive treatment delay and repeated transfer.

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The wrist patch-type ECG/APW sensor system is proposed for continuous and comprehensive monitoring of the patient's cardiovascular system. The wrist patch-type ECG/APW sensor system is consists of ECG/APW sensor, ECG/APW electrodes, and base station for real-time monitoring of the patient's status. The ECG/APW sensor and electrodes are composed of wrist patch, bandage-type ECG electrode and fabric APW electrode, respectively so that the patient's cardiovascular system can be continuously monitored in daily life with free hand-movement.

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A multimodal mental management system in the shape of the wearable headband and earplugs is proposed to monitor electroencephalography (EEG), hemoencephalography (HEG) and heart rate variability (HRV) for accurate mental health monitoring. It enables simultaneous transcranial electrical stimulation (tES) together with real-time monitoring. The total weight of the proposed system is less than 200 g.

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The multimodal stress monitoring headband is proposed for mobile stress management system. It is composed of headband and earplugs. Electroencephalography (EEG), hemoencephalography (HEG) and heart-rate variability (HRV) can be achieved simultaneously in the proposed system for user status estimation.

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A system-on-chip (SoC) with nonlinear chaotic analysis (NCA) is presented for mental task monitoring. The proposed processor treats both heart rate variability (HRV) and electroencephalography (EEG). An independent component analysis (ICA) accelerator decreases the error of HRV extraction from 5.

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A wearable neuro-feedback system is proposed with a low-power neuro-feedback SoC (NFS), which supports mental status monitoring with encephalography (EEG) and transcranial electrical stimulation (tES) for neuro-modulation. Self-configured independent component analysis (ICA) is implemented to accelerate source separation at low power. Moreover, an embedded support vector machine (SVM) enables online source classification, configuring the ICA accelerator adaptively depending on the types of the decomposed components.

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A wearable depression monitoring system is proposed with an application-specific system-on-chip (SoC) solution. The SoC is designed to accelerate the filtering and feature extraction of heart-rate variability (HRV) from the electrocardiogram (ECG). Thanks to the SoC solution and planar-fashionable circuit board (P-FCB), the monitoring system becomes a low-power wearable system.

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The wearable mental-health monitoring platform is proposed for mobile mental healthcare system. The platform is headband type of 50 g and consumes 1.1 mW.

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The Smart Patches and Wearable Band (W-Band) are proposed for comfortable sleep monitoring system which recognizes and diagnoses sleep disorders. By using Planar Fashionable Circuit Board (P-FCB) techniques, the Smart Patches are implemented with the plain fabric patch so that it can have light weight and small size. And the stretchability of the W-Band can achieve user convenience, low manufacturing cost, and low power consumption all at once.

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