Design, implementation, and preliminary in-vivo assessment of a high-CMRR low-NEF wireless EEG miniaturized platform.

This work presents the design, manufacture, test, and preliminary in-vivo assessment of the proof-of-concept of a miniaturized wireless platform for acquiring electroencephalography signals, where the input stage is a high-CMRR current-efficiency custom-made integrated neural preamplifier.Clinical relevance- Small, low-power consumption, wireless, wearable devices for chronically monitoring EEG recordings may contribute to the diagnosis of transient neurological events, the characterization and potential forecasting of epileptic seizures, and provide signals for controlling prosthetic and aid devices.

Bruxist Activity Monitor System (BAMS): An instrumental approach tool in the assessment of Bruxism.

The magnitude of harmful effects on dental structures, periodontium, masticatory muscles, and the temporomandibular joint, derived from temporomandibular disorders, specifically from sleep Bruxism, generates evidence that needs to be objectively collected. This paper introduces a portable device aiming at extracting and analyzing parameters (like timestamp, duration, or latency) from recordings obtained from the monitoring of occlusal activity, throughout a complete sleep cycle. An electronic device embedded in a mid-density medical grade silicon occlusal splint detects the moment in which the subject exerts sustained force, and records the time and length of the event, keeping the device on hold until a new event arises. The electronic device, based on a microcontroller, identifies occlusive events from an array of two piezo-resistive sensors and has a storage capacity of up to 36 hours of continuous activity. The collected data is wirelessly transmitted to an external module that is connected via USB to a PC. In the PC, the data is decoded, processed, analyzed, displayed, and stored in ordered files for case subjects, updating every recorded test for a complete history review. The proposed Bruxist Activity Monitor System (BAMS) was tested in one subject for more than 40 hours (5 sessions in 7 days). Preliminary results show the oral appliance endure without any significant damage over its surface nor undermining its functionality.

Enhanced ICMR amplifier for high CMRR biopotential recordings.

This paper presents an integrated biopotential preamplifier architecture targeting applications that simultaneously require high common-mode rejection ratio (CMRR), low noise, high input common-mode range (ICMR), and current-efficiency (low Noise Efficiency Factor or NEF). A biopotential preamplifier, which performs well in line with the state-of-the-art of the field while providing enhanced ICMR and CMRR performance, was fabricated in a 0.5 µm CMOS process. Results from measurements show that the gain is 47 dB, the bandwidth ranges from 1 Hz to 7.7 kHz, the equivalent input noise is 1.8 µVrms, the CMRR is 100.5 dB, the ICMR is 1.7 V and the NEF is 3.2.

Current-Efficient Preamplifier Architecture for CMRR Sensitive Neural Recording Applications.

There are neural recording applications in which the amplitude of common-mode interfering signals is several orders of magnitude higher than the amplitude of the signals of interest. This challenging situation for neural amplifiers occurs, among other applications, in neural recordings of weakly electric fish or nerve activity recordings made with cuff electrodes. This paper reports an integrated neural amplifier architecture targeting in-vivo recording of local field potentials and unitary signals from the brain stem of a weakly electric fish Gymnotus omarorum. The proposed architecture offers low noise, high common-mode rejection ratio (CMRR), current-efficiency, and a high-pass frequency fixed without MOS pseudoresistors. The main contributions of this work are the overall architecture coupled with an efficient and simple single-stage circuit for the amplifier main transconductor, and the ability of the amplifier to acquire biopotential signals from high-amplitude common-mode interference in an unshielded environment. A fully-integrated neural preamplifier, which performs well in line with the state-of-the-art of the field while providing enhanced CMRR performance, was fabricated in a 0.5  m CMOS process. Results from measurements show that the gain is 49.5 dB, the bandwidth ranges from 13 Hz to 9.8 kHz, the equivalent input noise is 1.88  V, the CMRR is 87 dB and the Noise Efficiency Factor is 2.1. In addition, in-vivo recordings of weakly electric fish neural activity performed by the proposed amplifier are introduced and favorably compared with those of a commercial laboratory instrumentation system.

Wireless EEG System Achieving High Throughput and Reduced Energy Consumption Through Lossless and Near-Lossless Compression.

This work presents a wireless multichannel electroencephalogram (EEG) recording system featuring lossless and near-lossless compression of the digitized EEG signal. Two novel, low-complexity, efficient compression algorithms were developed and tested in a low-power platform. The algorithms were tested on six public EEG databases comparing favorably with the best compression rates reported up to date in the literature. In its lossless mode, the platform is capable of encoding and transmitting 59-channel EEG signals, sampled at 500 Hz and 16 bits per sample, at a current consumption of 337 A per channel; this comes with a guarantee that the decompressed signal is identical to the sampled one. The near-lossless mode allows for significant energy savings and/or higher throughputs in exchange for a small guaranteed maximum per-sample distortion in the recovered signal. Finally, we address the tradeoff between computation cost and transmission savings by evaluating three alternatives: sending raw data, or encoding with one of two compression algorithms that differ in complexity and compression performance. We observe that the higher the throughput (number of channels and sampling rate) the larger the benefits obtained from compression.

Wearable EEG via lossless compression.

This work presents a wearable multi-channel EEG recording system featuring a lossless compression algorithm. The algorithm, based in a previously reported algorithm by the authors, exploits the existing temporal correlation between samples at different sampling times, and the spatial correlation between different electrodes across the scalp. The low-power platform is able to compress, by a factor between 2.3 and 3.6, up to 300sps from 64 channels with a power consumption of 176µW/ch. The performance of the algorithm compares favorably with the best compression rates reported up to date in the literature.

An analog circuit implementation of a Huber-Braun cold receptor neuron model.

We present the design and implementation of an electronic device that, using off the shelf discrete analog components, implements the mathematical model of a cold receptor neuron called Huber-Braun. This model describes the electrical behavior of certain kinds of receptors when interacting with their environment, and it consists of a set of differential equations that has only been solved by numeric simulations. By these means a chaotic behavior has been found. An analog computer can be relevant for further analysis and validation of the model. The results obtained by means of numeric simulations and through our analog circuit simulator are consistent. In particular, temperature and external current bifurcation diagrams were successfully built. Finally, the electronic device allows the observation of all relevant variables and most of the expected behavior (tonic firing, chaotic, burst discharge, subthreshold oscillation and steady state).