Sergi Consul-Pacareu

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

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 (fc = 60Hz), then band-passed by a 2nd-order Chebyshev-I low-pass filter cascaded with a 2nd-order low-pass (fc = 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.

Body-worn fully-passive wireless analog sensors for physiological signal capture through load modulation using resistive transducers

Fully-passive wireless body-sensors pose viable solutions for unobtrusive monitoring of physiological signals at natural settings. While fully-passive capacitive analog passive wireless sensors has been reported, we present an alternative solution with resistive based transducers. The passive sensor is composed of a loop antenna, a tuning capacitor, and a resistive transducer suitable for the type of physiological signals to be measured. The scanner transmits carrier RF signal at 13.75MHz whose amplitude is modulated based on the resistive loading by the transducer. The load modulation is captured with the signal analyzer. The system was characterized for various resistive loads of 1.2Ω to 82KΩ and open at 5, 10, 20, and 40 mm co-axial distances between the transmitter and the receiver antennas. We demonstrate the practicality of the system by measuring several physiological signals like heart rate, temperature, and pulse oximetry. The wireless power used for remote sensing is very low (-20dBm, except pulse oximetry requires 0dBm). The results show the potential of developing a new set of body-worn fully-passive sensors for physiological signal monitoring.

Body-worn fully-passive wireless analog sensors for biopotential measurement through load modulation

Fully-passive wireless and disposable bodysensors are promising for unobtrusive monitoring of physiological signals at natural settings. We present a new type of wireless analog passive sensor (WAPS) based on resistive damping, which can be used for biopotential sensing. The resistive WAPS operates by modulating the amplitudes of the incident RF signal, and composes of a loop antenna, a tuning capacitor, and a MOSFET (an additional biasing resistance is used in one variation). The scanner transmits carrier RF signal at 13:34MHz and the load modulated signal is captured with the signal analyzer. The envelope of the modulated signal correlates with the biopotential being sensed. Both enhancement and depletion MOSFETs are demonstrated, where the earlier demonstrated superior performance. The sensitivity can be as low as 10 mV, suitable for ECG and EMG physiological signal capture. The transmission power were 0 dBm while the co-axial separation between antennas were 21.5 mm. The results show that the proposed WAPS can be used to develop disposable biopotential sensor suitable for body-worn physiological signal monitoring system.

Feasibility of patterned vertical CNT for dry electrode sensing of physiological parameters

Dry electrodes for impedimetric sensing of physiological parameters (such as ECG, EEG, and GSR) promise the ability for long duration monitoring. This paper describes the feasibility of a novel dry electrode interfacing using Patterned Vertical Carbon Nanotube (pvCNT) for physiological parameter sensing. The electrodes were fabricated on circular discs (φ = 10 mm) stainless steel substrate. Multiwalled electrically conductive carbon nanotubes were grown in pattered pillar formation of 100 μm squared with 50, 100, 200 and 500μm spacing. The heights of the pillars were between 1 to 1.5 mm. A comparative test with commercial ECG electrodes shows that pvCNT has lower electrical impedance, stable impedance over very long time, and comparable signal capture in vitro. Long duration study shows minimal degradation of impedance over 2 days period. The results demonstrate the feasibility of using pvCNT dry electrodes for physiological parameter sensing.

Power optimization of NeuroMonitor EEG device: Hardware/software co-designed interrupt driven clocking approach

Wireless and wearable EEG device for home based long-term non intrusive diagnosis for therapy applications like ASD, ADHD, Epilepsy and other neurological disorders is crucial. This work presents the NeuroMonitor (rev. 2.0) platform designed to record EEG signals from two (bipolar or referential montage) channels. The device is lightweight 41.8g (with 900mAh battery and 3 electrodes) and miniature, 5.58cm× 2.03cm × 0.91cm. A power analysis and power optimization techniques have been studied using interrupt driven clocking approach for the Analog Front End, the ADC and the Digital Back End. About 5 fold power reduction; from the 94mW (av.) in rev. 1.0 to a 17mW in rev. 2.0, while maintaining the sampling rate has been achieved.

Wireless ambulatory ECG signal capture for HRV and cognitive load study using the NeuroMonitor platform

The heart rhythms, controlled by the autonomic nervous system, can fluctuate with varying cognitive loads that can be captured with electrocardiogram (ECG) and heart rate variability (HRV) metrics. In this paper, we report customization of a wireless, ambulatory NeuroMonitor device originally developed for collecting electroencephalogram (EEG) signals as a platform for ECG and HRV data collection. The overall gain is altered to 93.86, while the band pass filter was set to 0.5 Hz to 126 Hz. The four independent inputs were connected to left arm, right arm, left leg and right leg. ECG signal and HRV data was collected during relax state and elevated cognitive load conditions. The signals were digitized at 256 sps and wirelessly transmitted to a remote computer for analysis. These cardiac signals were filtered and plotted using MATLAB. We demonstrate successful data collection that enables multiple applications of NeuroMonitor platform as an ambulatory physiological parameter monitoring hardware for long duration study of patients in natural settings.

Telemetry controlled simultaneous microstimulation and recording device for studying cortical plasticity

This paper describes a telemetric interactive intracortical microstimulation (ICMS) and simultaneous recording device developed to deliver chronic microstimulation to the ipsilateral cortex and monitor evoked responses from the contralateral cortex. The embedded device was developed utilizing a Programmable System on a Chip (PSoC) microcontroller that can be remotely configured through Bluetooth. This device, with dimensions of 42 mm × 71 mm, can deliver monophasic, biphasic or pseudophasic stimulation pulses (peak current: ≤ 100 μA, duration: ≤ 10 ms, delay: ≤ 40 ms, repetition rate: 0.5 to 1 Hz) to a physiologically identified site in primary somatosensory cortex (SI) and record single and multiunit responses within 367 to 6470 Hz from a homotopic site in contralateral SI. This device was bench tested and validated in vivo in rat.

Design and Analysis of a Novel Wireless Resistive Analog Passive (WRAP) Sensor Technique

Unobtrusive monitoring of physiological signals in natural settings is important for precision diagnostics. Fully-passive wireless body-worn sensors are viable and promising for unobtrusive monitoring. In this study, the authors present a new class of fully-passive sensor, namely wireless resistive analog passive (WRAP) sensor. It uses resistive transducers at the sensors for converting physical stimulus to load modulation of carrier wireless signal at 13.56 MHz at low power (-20 to 0 dBm). The sensor is simply composed of a loop antenna, a tuning capacitor, and a resistive transducer suitable for the type of physiological signals to be measured. The authors report the characterisation of WRAP sensors for various resistive loads of 1.2 ω to 82 kω at various co-axial distances (5-40 mm) between the TX and RX antennas. They have prototyped and characterised multiple WRAP sensors with several practical measurements of physiological signals such as heart rate, temperature, and pulse oximetry. They also demonstrate bio-potential measurement (down to 400 μ V pp ) using metal-oxide-semiconductor field-effect transistor as the transducer. These results show the feasibility of developing a new type of body-worn fully-passive WRAP sensors for unobtrusive physiological signal monitoring at real-life settings for precision diagnostics of many disorders and tracking person-centric therapy efficacy.

Neuronal recorder implementation with envelope detector for fidelity and linearity

Neuronal recorders of high-performance and low-power are needed for many embedded biomedical devices and the next-generation cyber-physical systems to capture the low-voltage, low-frequency brain signals. In this paper, an envelope detector implementation is reported that outperforms the conventional 2nd order band-pass filter (BPF). Simulation of the envelope detector outperformed the BPF by 2 dB for fidelity and 2.25 dB for linearity, but performed 0.4% worse for THD+N. Implementation of the envelope detector provided satisfactory performance with 2.8 dB fidelity and 3.7 dB linearity attenuation. As envelope detector requires lesser area and power, it promises to be a viable alternative for miniature implementation of neuronal recorders.

Low-power Fuzzy Logic VLSI implementation with asynchronous topology for neuronal sensors

Embedded systems for ubiquitous sensing towards the next-generation cyber-physical systems require low-power design approaches. A non-traditional low-power asynchronous circuit design for Fuzzy Logic rule-block is presented in this paper. The developed low-power architecture of the Fuzzy rule blocks consumes 197.2 μW for 3 rules using CMOS 0.13 micron technology. Implementation with an asynchronous topology reduced the power consumption to 64.5 μW. Such low-power controllers would be attractive for embedded neuronal sensors powered by energy scavenging.