Ms. Ruhi Mahajan Profile

Ruhi Mahajan

at Univ of Memphis

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Proceedings Article | 31 May 2013 Paper

Ambulatory EEG NeuroMonitor platform for engagement studies of children with development delays

Ruhi Mahajan, Sergi Consul-Pacareu, Mohammed Abusaud, Md Sahadat, Bashir Morshed

Proceedings Volume 8719, 87190L (2013) https://doi.org/10.1117/12.2016205

KEYWORDS: Electroencephalography, Linear filtering, Electrodes, Amplifiers, Brain, Electronic filtering, Data acquisition, Analog electronics, Prototyping, Prefrontal cortex

Read Abstract +

Engagement monitoring is crucial in many clinical and therapy applications such as early learning preschool classes for children with developmental delays including autism spectrum disorder (ASD), attention-deficit hyperactivity disorder (ADHD), or cerebral palsy; as it is challenging for the instructors to evaluate the individual responses of these children to determine the effectiveness of the teaching strategies due to the diverse and unique need of each child who might have difficulty in verbal or behavioral communication. This paper presents an ambulatory scalp electroencephalogram (EEG) NeuroMonitor platform to study brain engagement activities in natural settings. The developed platform is miniature (size: 2.2” x 0.8” x 0.36”, weight: 41.8 gm with 800 mAh Li-ion battery and 3 snap leads) and low-power (active mode: 32 mA low power mode: under 5mA) with 2 channels (Fp1, Fp2) to record prefrontal cortex activities of the subject in natural settings while concealed within a headband. The signals from the electrodes are amplified with a low-power instrumentation amplifier; notch filtered (f_c = 60Hz), then band-passed by a 2nd-order Chebyshev-I low-pass filter cascaded with a 2nd-order low-pass (f_c = 125Hz). A PSoC ADC (16-bit, 256 sps) samples this filtered signal, and can either transmit it through a Class-2 Bluetooth transceiver to a remote station for real-time analysis or store it in a microSD card for offline processing. This platform is currently being evaluated to capture data in the classroom settings for engagement monitoring of children, aimed to study the effectiveness of various teaching strategies that will allow the development of personalized classroom curriculum for children with developmental delays.

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