U. Ha, Yongsu Lee, Hyunki Kim, Taehwan Roh, Joonsung Bae, Changhyeon Kim, H. Yoo
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Measured three-physiology domains such as neural, vascular and autonomic domain signals are combined with canonical correlation analysis (CCA) and temporal kernel canonical correlation analysis (tkCCA) algorithm to find the neural-vascular-autonomic coupling. It supports highly accurate classification with the 19% maximum improvement with multimodal monitoring. For the multi-channel stimulation functionality, after-effects maximization monitoring and sympathetic nerve disorder monitoring, the stimulator is designed as reconfigurable. The 3.37 × 2.25 mm 2 chip has 2-channel EEG sensor front-end, 2-channel NIRS sensor front-end, NIRS current driver to drive dual-wavelength VCSEL and 6-b DAC current source for tES mode. It dissipates 24 mW with 2 mA stimulation current and 5 mA NIRS driver current.","PeriodicalId":13151,"journal":{"name":"IEEE Transactions on Biomedical Circuits and Systems","volume":"9 1","pages":"758-766"},"PeriodicalIF":3.8000,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/TBCAS.2015.2504959","citationCount":"53","resultStr":"{\"title\":\"A Wearable EEG-HEG-HRV Multimodal System With Simultaneous Monitoring of tES for Mental Health Management\",\"authors\":\"U. Ha, Yongsu Lee, Hyunki Kim, Taehwan Roh, Joonsung Bae, Changhyeon Kim, H. Yoo\",\"doi\":\"10.1109/TBCAS.2015.2504959\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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. The multi-loop low-noise amplifier (MLLNA) achieves over 130 dB CMRR for EEG sensing and the capacitive correlated-double sampling transimpedance amplifier (CCTIA) has low-noise characteristics for HEG and HRV sensing. Measured three-physiology domains such as neural, vascular and autonomic domain signals are combined with canonical correlation analysis (CCA) and temporal kernel canonical correlation analysis (tkCCA) algorithm to find the neural-vascular-autonomic coupling. It supports highly accurate classification with the 19% maximum improvement with multimodal monitoring. For the multi-channel stimulation functionality, after-effects maximization monitoring and sympathetic nerve disorder monitoring, the stimulator is designed as reconfigurable. The 3.37 × 2.25 mm 2 chip has 2-channel EEG sensor front-end, 2-channel NIRS sensor front-end, NIRS current driver to drive dual-wavelength VCSEL and 6-b DAC current source for tES mode. 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A Wearable EEG-HEG-HRV Multimodal System With Simultaneous Monitoring of tES for Mental Health Management
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. The multi-loop low-noise amplifier (MLLNA) achieves over 130 dB CMRR for EEG sensing and the capacitive correlated-double sampling transimpedance amplifier (CCTIA) has low-noise characteristics for HEG and HRV sensing. Measured three-physiology domains such as neural, vascular and autonomic domain signals are combined with canonical correlation analysis (CCA) and temporal kernel canonical correlation analysis (tkCCA) algorithm to find the neural-vascular-autonomic coupling. It supports highly accurate classification with the 19% maximum improvement with multimodal monitoring. For the multi-channel stimulation functionality, after-effects maximization monitoring and sympathetic nerve disorder monitoring, the stimulator is designed as reconfigurable. The 3.37 × 2.25 mm 2 chip has 2-channel EEG sensor front-end, 2-channel NIRS sensor front-end, NIRS current driver to drive dual-wavelength VCSEL and 6-b DAC current source for tES mode. It dissipates 24 mW with 2 mA stimulation current and 5 mA NIRS driver current.
期刊介绍：
The IEEE Transactions on Biomedical Circuits and Systems addresses areas at the crossroads of Circuits and Systems and Life Sciences. The main emphasis is on microelectronic issues in a wide range of applications found in life sciences, physical sciences and engineering. The primary goal of the journal is to bridge the unique scientific and technical activities of the Circuits and Systems Society to a wide variety of related areas such as: • Bioelectronics • Implantable and wearable electronics like cochlear and retinal prosthesis, motor control, etc. • Biotechnology sensor circuits, integrated systems, and networks • Micropower imaging technology • BioMEMS • Lab-on-chip Bio-nanotechnology • Organic Semiconductors • Biomedical Engineering • Genomics and Proteomics • Neuromorphic Engineering • Smart sensors • Low power micro- and nanoelectronics • Mixed-mode system-on-chip • Wireless technology • Gene circuits and molecular circuits • System biology • Brain science and engineering: such as neuro-informatics, neural prosthesis, cognitive engineering, brain computer interface • Healthcare: information technology for biomedical, epidemiology, and other related life science applications. General, theoretical, and application-oriented papers in the abovementioned technical areas with a Circuits and Systems perspective are encouraged to publish in TBioCAS. Of special interest are biomedical-oriented papers with a Circuits and Systems angle.
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