Photoplethysmography-based derivation of physiological information using the BioPoint.

The BioPoint is a new wireless and wearable device, targeting both the ambulatory and on-site monitoring of biosignals. It is described as being capable of streaming and recording the i) electromyography, ii) electrocardiography, iii) electrodermal activity, iv) photoplethysmography, v) skin temperature and vi) actigraphy simultaneously, while making the raw signals recorded by the sensors readily available. However, an in-depth assessment of the biophysical signals recorded by this device, as well as its ability to derive vital signs and other health metrics, remains to be carried out. Consequently, this work proposes a preliminary study to evaluate the quality of the signals that can be acquired by this wearable with a focus on the derivation of heart rate and peripheral blood oxygenation via photoplethysmography. The device is quantitatively compared to the medical-grade pulse oximeter NoninConnect 3245, by Nonin inc. This study was performed with participants wearing the BioPoint at different positions on the body (finger, wrist, forearm, biceps and plantar arch), while the NoninConnect was worn on the fingertip and used as the ground truth. The results show that the BioPoint can accurately determine both heart rate and oxygen saturation from various locations on the body. However, as the BioPoint's photoplethysmograph is not calibrated it cannot be used for medical purposes (non-medical-grade).

Optimization & Characterization of Interdigitated Electrodes for Microbial Growth Monitoring.

This study optimally designed and implemented highly sensitive microscale interdigitated electrodes (IDEs) to monitor microorganisms' growth in diverse environments. Gold interdigitated electrodes (AuIDE) with 4 mm×4 mm effective sensing area and varying microscale interdigitate gaps were designed and fabricated. The electrodes were electrically characterized voltametrically. Electrochemical impedance spectroscopy (EIS) measurements were conducted to determine the optimal geometry by observing the impedance spectra of microelectrodes through varying pH and temperature. Furthermore, the sensors sensitivity was evaluated by measuring the impedance properties of a microscale volume of microorganism concentrations in growth media solution.

A versatile wearable sEMG recording system for long-term epileptic seizure monitoring.

Surface electromyography (sEMG) can be used to detect motor epileptic seizures non-invasively. For clinical use, a compact-size, user-friendly, safe and accurate sEMG measurement system can be worn by epileptic patients to detect and characterize a seizure. Such devices must be small, wireless, power-efficient minimally invasive and robust to avoid movement artefacts, friction, and slipping of the electrode, which can compromise data integrity and/or generate false positives or false negatives. This paper presents a highly versatile device that can be worn in different locations on the body to capture sEMG signals in a freely moving user without movement artefact. The system can be safely worn on the body for several hours to capture sEMG from wet Ag/AgCl electrodes, while sEMG data is wirelessly transmitted to a host computer within a range of 20 m. We demonstrate the versatility of our sensor by recording sEMG from five different body locations in a freely moving volunteer. Then, simulated seizure data was captured while the device was placed on the extensor carpi ulnaris. We show that sEMG bursts were successfully recorded to characterize the seizure afterward. The presented sensor prototype is small (5 cm x 3.5 cm x 1 cm), lightweight (46 g), and has an autonomy of 12 hrs from a small 110-mAh battery.

The EcoChip 2: An Autonomous Sensor Platform for Multimodal Bio-environmental Monitoring of the Northern Habitat.

This paper presents the EcoChip 2, an autonomous multimodal bio-environmental sensor platform for the monitoring of microorganisms in the northern habitat. The EcoChip 2 prototype includes an array of 96-wells for the continuous monitoring of microbiological growth through a multichannel electrochemical impedance analyzer circuit. In addition, the platform includes luminosity, humidity, temperature sensors and monitoring. The developed electronic board uses an ultra-low-power microcontroller unit, a custom power management unit, a low-power wireless ISM-2.45 GHz transceiver, and a flash memory to accumulate and store the sensor data over extended monitoring periods. When a wireless base station is placed within the transmission range of the EcoChip 2, an embedded low-power wireless transceiver transmits the 96-wells impedance data and the other sensor data stored in the flash memory to the user interface. We present the measured performance of the prototype, along with laboratory test results of bacterial growth measurements inside the 96 wells in parallel. We show that the EcoChip 2 can successfully measure the impedances associated with bacterial growth over several hours using an excitation frequency of 2 kHz with power consumption of 114.6 mW under operating mode.

A Wearable Wireless Armband Sensor for High-Density Surface Electromyography Recording.

This paper presents a portable and modular wireless multichannel sensor system for high-density surface electromyography (HD-sEMG) signals acquisition. Featuring low-power and high-quality off-the-shelf components such as the Intan Technologies RHD2132 digital electrophysiology interface chip, the current iteration of the proposed sensor system allows the recording of 32 surface electromyography (sEMG) channels, each at a sampling rate of 1 kHz, and a sample resolution of 16 bits. It features the RHD2132's typical input-referred noise of 2.4 µVrms, with <; 15% variation with amplifier bandwidth as specified by the manufacturer, and a total power consumption of 49.5 mW. Data is sent in real-time to a base station using a 2.4-GHz industrial, scientific and medical (ISM) wireless link. Along with the recording platform, the integrated sensor system includes a dry surface electrodes array prototype directly built on a printed circuit board. Intended for complex muscles activity patterns detection on the forearm, the flexible 32 surface electrodes array is designed to be placed flat or to fit a curved area like the forearm in a hand gestures recognition prosthetic system. In such applications, this device will offer improved prosthesis control scheme intuitiveness and ease-of-use. Among other core features of the system are its compact, light-weight and easy to install physical design. The complete system fits on a 2 by 6.5 cm2 printed circuit board mounted on a 7.6 by 11.8 cm2 electrodes array. HD-sEMG user forearm output data collected with the system is presented with a proposed frequency-time-space cross-domain preprocessing method for visualization of HD-EMG data and building training datasets.

A Wireless Optoelectronic Neuroscience Platform for Chronic Fluorescence Sensing in Freely Behaving Rodents.

We present a new head mountable wireless fiber biophotometry microsystem conceived to detect fluorescent signal fluctuations correlated with neuronal activity. The proposed system incorporates all aspects of a conventional tethered fiber-based biophotometry system encompassed into a wireless microsystem. The interface includes an LED as excitation light source, a custom designed CMOS biosensor, a multimode fiber, a microcontroller (MCU), and a wireless data transceiver enclosed within a 3D-printed, small and light weight, plastic housing. Precisely, the system incorporates a new optoelectronic biosensor merging two individual building blocks, namely a low-noise sensing front-end and $\mathrm {a}2 ^{nd}$ order continuous-time $\Sigma \Delta $ modulator (CTSDM), into a single module for enabling high-sensitivity and high energy-efficiency photo-sensing. The proposed CMOS biosensor is implemented in $\mathrm {a}0 .18- \mu m$ CMOS technology, consuming $41 \mu W$ from $\mathrm {a}1 .8- V$ supply voltage, while achieving a peak dynamic range of $86 dB$ over a $50- Hz$ input bandwidth at a 20-kS/s sampling rate. This new interface opens new avenues for conducting in-vivo experiments with live animals.

Low-power adaptive spike detector based on a sigma-delta control loop.

This paper presents a resources-optimized digital action potential (AP) detector featuring an adaptive threshold based on a new Sigma-delta control loop. The proposed AP detector is optimized for utilizing low hardware resources, which makes it suitable for implementation on most popular low-power microcontrollers units (MCU). The adaptive threshold is calculated using a digital control loop based on a Sigma-delta modulator that precisely estimates the standard deviation of the amplitude of the neuronal signal. The detector was implemented on a popular low-power MCU and fully characterized experimentally using previously recorded neural signals with different signal-to-noise ratios. A comparison of the obtained results with other thresholding approaches shows that the proposed method can compete with high performance and highly resources demanding spike detection approaches while achieving up to 100% of true positive detection rate at high SNR, and up to 63% for an SNR as low as 0 dB, while necessitating an execution time as low as 11 µs with the MCU operating at 8 MHz.

Multichannel spike detector with an adaptive threshold based on a Sigma-delta control loop.

In this paper, we present a digital spike detector using an adaptive threshold which is suitable for real time processing of 32 electrophysiological channels in parallel. Such a new scheme is based on a Sigma-delta control loop that precisely estimates the standard deviation of the amplitude of the noise of the input signal to optimize the detection rate. Additionally, it is not dependent on the amplitude of the input signal thanks to a robust algorithm. The spike detector is implemented inside a Spartan-6 FPGA using low resources, only FPGA basic logic blocks, and is using a low clock frequency under 6 MHz for minimal power consumption. We present a comparison showing that the proposed system can compete with a dedicated off-line spike detection software. The whole system achieves up to 100% of true positive detection rate for SNRs down to 5 dB while achieving 62.3% of true positive detection rate for an SNR as low as -2 dB at a 150 AP/s firing rate.