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UID:20260524T024604EDT-3567N1OVWL@132.216.98.100
DTSTAMP:20260524T064604Z
DESCRIPTION:Abstract\n\nSmart wearables can provide clinical standard healt
 h monitoring services in our day-to-day life. One such wearable applicatio
 n is smart headband/eye-mask based biopotential monitoring systems\, which
  employ electroencephalography (EEG) and electrooculography (EOG) techniqu
 es for sleep assessment. However\, most of the commercial biopotential wea
 rables are rigid\, bulky\, and uncomfortable to wear.\n\nIn this research\
 , we propose a wearable for EOG measurement which is implemented on flexib
 le Polyimide PCB with integrated printed gold contact electrodes and the b
 iopotential acquisition. The wearable can be easily integrated with headba
 nds/eye-masks. The system performance is validated using a MATLAB based al
 gorithm for the detection of different eye activities such as blinks\, win
 ks\, and eye movements. But this prototype requires electrode gel for bett
 er EOG detection and is sensitive to random motion artifacts. To overcome 
 these limitations\, the EOG wearable design is redesigned with parallel no
 n-contact (or capacitive) electrode pairs\, which have better sensitivity 
 and do not require gel for EOG detection. The parallel electrode pairs are
  configured differentially for sensing and reducing motion artifacts durin
 g EOG measurement. The proposed wearable is then validated for acquiring E
 OG signals in the presence/absence of motion. However\, forehead/eye-masks
  based wearables are still uncomfortable to wear and prone to displacement
 s due to movements.\n\nIn recent studies\, EEG signals are successfully ac
 quired intra-orally\, with the help of oral appliances like mandibular adv
 ancement devices (MADs). Here\, we propose a smart MAD which integrates fl
 exible EEG electrodes\, accelerometer\, and the measurement unit. The syst
 em can measure intra-oral EEG and motion signals (such as tongue movements
 \, teeth grinding\, and gulping) simultaneously. An EMD-ICA based algorith
 m is also developed in MATLAB to identify the motion corrupted EEG segment
 s using the accelerometer data and denoise them accordingly. The smart MAD
  and the proposed algorithm are also validated for detecting ‘eye open’ an
 d ‘eye close’ activities from the acquired intra-oral EEG spectrums\, in t
 he presence/absence of intra-oral motions. This smart MAD system for intra
 -oral EEG can be a potential alternative solution to headband/eye-masks ba
 sed wearables.\n
DTSTART:20230825T173000Z
DTEND:20230825T193000Z
LOCATION:Room 603\, McConnell Engineering Building\, CA\, QC\, Montreal\, H
 3A 0E9\, 3480 rue University
SUMMARY:PhD defence of Shibam Debbarma – Wearable Flexible Biopotential Mea
 surement Systems
URL:/ece/channels/event/phd-defence-shibam-debbarma-we
 arable-flexible-biopotential-measurement-systems-349922
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