title: Design and validation of a wearable "DRL-less" EEG using a novel fully-reconfigurable architecture.
abstract: The conventional EEG system consists of a driven-right-leg (DRL) circuit, which prohibits modularization of the system. We propose a Lego-like connectable fully reconfigurable architecture of wearable EEG that can be easily customized and deployed at naturalistic settings for collecting neurological data. We have designed a novel Analog Front End (AFE) that eliminates the need for DRL while maintaining a comparable signal quality of EEG. We have prototyped this AFE for a single channel EEG, referred to as Smart Sensing Node (SSN), that senses brain signals and sends it to a Command Control Node (CCN) via an I2C bus. The AFE of each SSN (referential-montage) consists of an off-the-shelf instrumentation amplifier (gain=26), an active notch filter fc = 60Hz), 2nd-order active Butterworth low-pass filter followed by a passive low pass filter (fc = 47.5 Hz, gain = 1.61) and a passive high pass filter fc = 0.16 Hz, gain = 0.83). The filtered signals are digitized using a low-power microcontroller (MSP430F5528) with a 12-bit ADC at 512 sps, and transmitted to the CCN every 1 s at a bus rate of 100 kbps. The CCN can further transmit this data wirelessly using Bluetooth to the paired computer at a baud rate of 115.2 kbps. We have compared temporal and frequency-domain EEG signals of our system with a research-grade EEG. Results show that the proposed reconfigurable EEG captures comparable signals, and is thus promising for practical routine neurological monitoring in non-clinical settings where a flexible number of EEG channels are needed.
authors.forename: Ruhi
authors.initials: R
authors.lastname: Mahajan
authors.forename: Bashir I
authors.initials: BI
authors.lastname: Morshed
authors.forename: Gavin M
authors.initials: GM
authors.lastname: Bidelman
mesh_terms: D001921:Brain / Q000502:physiology; D004569:Electroencephalography / Q000295:instrumentation* / Q000379:methods*; D004867:Equipment Design; D006801:Humans; D015203:Reproducibility of Results; D012815:Signal Processing, Computer-Assisted / Q000295:instrumentation; D014584:User-Computer Interface; D058067:Wavelet Analysis