Literature DB >> 30167826

BRAINsens: Body-Worn Reconfigurable Architecture of Integrated Network Sensors.

Ruhi Mahajan1, Bashir I Morshed2, Gavin M Bidelman3.   

Abstract

Body sensor network (BSN) is a promising human-centric technology to monitor neurophysiological data. We propose a fully-reconfigurable architecture that addresses the major challenges of a heterogenous BSN, such as scalabiliy, modularity and flexibility in deployment. Existing BSNs especially with Electroencephalogarm (EEG) have these limitations mainly due to the use of driven-right-leg (DRL) circuit. We address these limitations by custom-designing DRL-less EEG smart sensing nodes (SSN) for modular and spatially distributed systems. Each single-channel EEG SSN with a input-referred noise of 0.82 μVrms and CMRR of 70 dB (at 60 Hz), samples brain signals at 512 sps. SSNs in the network can be configured at the time of deployment and can process information locally to significantly reduce data payload of the network. A Control Command Node (CCN) initializes, synchronizes, periodically scans for the available SSNs in the network, aggregates their data and sends it wirelessly to a paired device at a baud rate of 115.2 kbps. At the given settings of the I2C bus speed of 100 kbps, CCN can configure up to 39 EEG SSNs in a lego-like platform. The temporal and frequency-domain performance of the designed "DRL-less" EEG SSNs is evaluated against a research-grade Neuroscan and consumer-grade Emotiv EPOC EEG. The results show that the proposed network system with wearable EEG can be deployed in situ for continuous brain signal recording in real-life scenarios. The proposed system can also seamlessly incorporate other physiological SSNs for ECG, HRV, temperature etc. along with EEG within the same topology.

Entities:  

Keywords:  Body sensor network; Driven-right-leg circuit; Fully reconfigurable architecture; I2C bus; Wearable EEG

Mesh:

Year:  2018        PMID: 30167826     DOI: 10.1007/s10916-018-1036-0

Source DB:  PubMed          Journal:  J Med Syst        ISSN: 0148-5598            Impact factor:   4.460


  13 in total

1.  A WBAN-based real-time electroencephalogram monitoring system: design and implementation.

Authors:  Haifeng Chen; Wanqing Wu; Jungtae Lee
Journal:  J Med Syst       Date:  2010-06       Impact factor: 4.460

2.  A multiparameter wearable physiologic monitoring system for space and terrestrial applications.

Authors:  Carsten W Mundt; Kevin N Montgomery; Usen E Udoh; Valerie N Barker; Guillaume C Thonier; Arnaud M Tellier; Robert D Ricks; Robert B Darling; Yvonne D Cagle; Nathalie A Cabrol; Stephen J Ruoss; Judith L Swain; John W Hines; Gregory T A Kovacs
Journal:  IEEE Trans Inf Technol Biomed       Date:  2005-09

3.  A TinyOS-enabled MICA2-based wireless neural interface.

Authors:  Shahin Farshchi; Paul H Nuyujukian; Aleksey Pesterev; Istvan Mody; Jack W Judy
Journal:  IEEE Trans Biomed Eng       Date:  2006-07       Impact factor: 4.538

4.  Wireless multichannel biopotential recording using an integrated FM telemetry circuit.

Authors:  P Mohseni; K Najafi
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2004

5.  Bi-Fi: an embedded sensor/system architecture for REMOTE biological monitoring.

Authors:  Shahin Farshchi; Aleksey Pesterev; Paul H Nuyujukian; Istvan Mody; Jack W Judy
Journal:  IEEE Trans Inf Technol Biomed       Date:  2007-11

Review 6.  Potential and challenges of body area networks for cardiac monitoring.

Authors:  Bert Gyselinckx; Julien Penders; Ruud Vullers
Journal:  J Electrocardiol       Date:  2007 Nov-Dec       Impact factor: 1.438

7.  A wearable physiological sensor suite for unobtrusive monitoring of physiological and cognitive state.

Authors:  Robert Matthews; Neil J McDonald; Paul Hervieux; Peter J Turner; Martin A Steindorf
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2007

8.  EEG alpha activity reflects attentional demands, and beta activity reflects emotional and cognitive processes.

Authors:  W J Ray; H W Cole
Journal:  Science       Date:  1985-05-10       Impact factor: 47.728

9.  Wearable feedback systems for rehabilitation.

Authors:  Michael Sung; Carl Marci; Alex Pentland
Journal:  J Neuroeng Rehabil       Date:  2005-06-29       Impact factor: 4.262

10.  High-frequency brain activity and muscle artifacts in MEG/EEG: a review and recommendations.

Authors:  Suresh D Muthukumaraswamy
Journal:  Front Hum Neurosci       Date:  2013-04-15       Impact factor: 3.169

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.