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).

Childhood adversities and risk of posttraumatic stress disorder and major depression following a motor vehicle collision in adulthood.

AIMS: Childhood adversities (CAs) predict heightened risks of posttraumatic stress disorder (PTSD) and major depressive episode (MDE) among people exposed to adult traumatic events. Identifying which CAs put individuals at greatest risk for these adverse posttraumatic neuropsychiatric sequelae (APNS) is important for targeting prevention interventions. METHODS: Data came from n = 999 patients ages 18-75 presenting to 29 U.S. emergency departments after a motor vehicle collision (MVC) and followed for 3 months, the amount of time traditionally used to define chronic PTSD, in the Advancing Understanding of Recovery After Trauma (AURORA) study. Six CA types were self-reported at baseline: physical abuse, sexual abuse, emotional abuse, physical neglect, emotional neglect and bullying. Both dichotomous measures of ever experiencing each CA type and numeric measures of exposure frequency were included in the analysis. Risk ratios (RRs) of these CA measures as well as complex interactions among these measures were examined as predictors of APNS 3 months post-MVC. APNS was defined as meeting self-reported criteria for either PTSD based on the PTSD Checklist for DSM-5 and/or MDE based on the PROMIS Depression Short-Form 8b. We controlled for pre-MVC lifetime histories of PTSD and MDE. We also examined mediating effects through peritraumatic symptoms assessed in the emergency department and PTSD and MDE assessed in 2-week and 8-week follow-up surveys. Analyses were carried out with robust Poisson regression models. RESULTS: Most participants (90.9%) reported at least rarely having experienced some CA. Ever experiencing each CA other than emotional neglect was univariably associated with 3-month APNS (RRs = 1.31-1.60). Each CA frequency was also univariably associated with 3-month APNS (RRs = 1.65-2.45). In multivariable models, joint associations of CAs with 3-month APNS were additive, with frequency of emotional abuse (RR = 2.03; 95% CI = 1.43-2.87) and bullying (RR = 1.44; 95% CI = 0.99-2.10) being the strongest predictors. Control variable analyses found that these associations were largely explained by pre-MVC histories of PTSD and MDE. CONCLUSIONS: Although individuals who experience frequent emotional abuse and bullying in childhood have a heightened risk of experiencing APNS after an adult MVC, these associations are largely mediated by prior histories of PTSD and MDE.

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.

Forearm High-Density Electromyography Data Visualization and Classification with Machine Learning for Hand Prosthesis Control.

Electromyography offers a way to interface an amputee's resilient muscles to control a bionic prosthesis. While myoelectric prostheses are promising, user acceptance of these devices remain low due to a lack of intuitiveness and ease-of-use. Using a low-cost wearable flexible electrodes array, the proposed system leverages high-density surface electromyography (HD-EMG) and deep learning techniques to classify forearm muscle contractions. These techniques allow for increased intuitiveness and ease-of-use of a myoelectric control scheme with a single easy-to-install electrodes apparatus. This paper proposes a flexible electrodes array construction using standard printed circuit board manufacturing processes for low-cost and quick design-to-production cycles. HD-EMG dataset visualization with t-distributed Stochastic Neighbor Embedding (t-SNE) is introduced, and offline classification results of the wearable gesture recognition system for hand prosthesis control are validated on a group of 8 able-bodied subjects. Using a majority vote on 5 successive inferences, a median recognition accuracy of 98.61 % was obtained across the group for an 8 gestures set. For a 6 gestures set containing commonly used prosthesis positions, the median accuracy reached 99.57 % with the majority vote.

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.

Management of the thyroid gland during laryngectomy.

OBJECTIVES: This study aimed to: describe the incidence of thyroid gland involvement in advanced laryngeal cancer, analyse patterns of spread to the thyroid and elucidate predictors of thyroid involvement. METHODS: A retrospective review was performed on patients who underwent laryngectomy from 1991 to 2015 as a primary or salvage treatment for squamous cell carcinoma of the larynx, hypopharynx or base of tongue. The incidence of thyroidectomy during total laryngectomy, type of thyroidectomy, incidence of gland involvement, route of spread, and positive predictors of spread were analysed and reported. RESULTS: A total of 188 patients fit the inclusion criteria. Of these, 125 (66 per cent) underwent thyroidectomy. The thyroid was involved in 10 of the 125 patients (8 per cent), 9 by direct extension and 1 by metastasis. Cartilage invasion was a predictor of thyroid gland involvement, with a positive predictive value of 26 per cent. CONCLUSION: There is a low incidence of thyroid gland involvement in laryngeal carcinoma. Most cases of gland involvement occurred by direct extension. Thyroidectomy during laryngectomy should be considered for advanced stage tumours with cartilage invasion.

A 110-nW in-channel sigma-delta converter for large-scale neural recording implants.

Advancement in wireless and microsystems technology have ushered in new devices that can directly interface with the central nervous system for stimulating and/or monitoring neural circuitry. In this paper, we present an ultra low-power sigma-delta analog-to-digital converter (ADC) intended for utilization into large-scale multi-channel neural recording implants. This proposed design, which provides a resolution of 9 bits using a one-bit oversampled ADC, presents several desirable features that allow for an in-channel ADC scheme, where one sigma-delta converter is provided for each channel, enabling development of scalable systems that can interface with different types of high-density neural microprobes. The proposed circuit, which have been fabricated in a TSMC 180-nm CMOS process, employs a first order noise shaping topology with a passive integrator and a low-supply voltage of 0.6 V to achieve ultra low-power consumption and small size. The proposed ADC clearly outperforms other designs with a power consumption as low as 110 nW for a precision of 9 bits (11-fJ per conversion), a silicon area of only 82 µm × 84 µm and one of the best reported figure of merit among recently published data converters utilized in similar applications.

A short-impulse UWB BPSK transmitter for large-scale neural recording implants.

In this paper, a short-impulse ultra-wide band (UWB) transmitter is introduced to enable large-scale neural recordings within miniature brain implants including thousands of channels. The proposed impulse radio UWB transmitter uses a BPSK modulation scheme, the carrier signal of which uses only two delayed impulses to encode the transmitted signal. The proposed UWB transmitter has been implemented into a CMOS 180 nm technology. It occupies 300 µm × 230 µm, and consumes only 6.7 pJ/bit from a 1.8-V supply. Experimental results show that the transmitter has a bandwidth of 2.6 GHz to 5.6 GHz and achieves a maximum data rate of 800 Mbps, which outperforms existing low-power UWB transmitters for similar applications.

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.

Intuitive wireless control of a robotic arm for people living with an upper body disability.

Assistive Technologies (ATs) also called extrinsic enablers are useful tools for people living with various disabilities. The key points when designing such useful devices not only concern their intended goal, but also the most suitable human-machine interface (HMI) that should be provided to users. This paper describes the design of a highly intuitive wireless controller for people living with upper body disabilities with a residual or complete control of their neck and their shoulders. Tested with JACO, a six-degree-of-freedom (6-DOF) assistive robotic arm with 3 flexible fingers on its end-effector, the system described in this article is made of low-cost commercial off-the-shelf components and allows a full emulation of JACO's standard controller, a 3 axis joystick with 7 user buttons. To do so, three nine-degree-of-freedom (9-DOF) inertial measurement units (IMUs) are connected to a microcontroller and help measuring the user's head and shoulders position, using a complementary filter approach. The results are then transmitted to a base-station via a 2.4-GHz low-power wireless transceiver and interpreted by the control algorithm running on a PC host. A dedicated software interface allows the user to quickly calibrate the controller, and translates the information into suitable commands for JACO. The proposed controller is thoroughly described, from the electronic design to implemented algorithms and user interfaces. Its performance and future improvements are discussed as well.

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.

Towards a wireless optical stimulation system for long term in-vivo experiments.

This paper presents our recent progresses towards the development of a wirelessly powered head mountable optical stimulator for enabling long-term optogenetic experiments with small freely moving transgenic models. The proposed system includes a wireless power transmission chamber with uniform power distribution in 3D and a wireless head mountable optical stimulator prototype with power recovery. The wireless power link, which includes the inductive chamber and power recovery circuits, is robust against subject movements in all directions, and against angular misalignment. Such link provides uniform power distribution without the need for a closed-loop control system, and can localize the transmitted power towards the receiver, without using additional detection and control circuitry compared to other systems. Additionally, the chamber is equipped with a camera for capturing the animal motion and behavior after applying optical stimulation patterns. A low-power microcontroller unit is embedded with the stimulator prototype to generate arbitrary light stimulation patterns. Measurement results show that the inductive chamber can continuously deliver 70 mW to the stimulator prototype with a power efficiency of 59%.

Flexible sixteen monopole antenna array for microwave breast cancer detection.

Radar based microwave imaging (MI) has been widely studied for breast cancer detection in recent times. Sensing dielectric property differences of tissues over a wide frequency band has been made possible by ultra-wideband (UWB) techniques. In this paper, a flexible, compact monopole antenna on a 100 µm Kapton polyimide is designed, using a high frequency structure simulator (HFSS), to be in contact with biological breast tissues over the 2-5GHz frequency range. The antenna parameters are optimized to obtain a good impedance match over the required frequency range. The designed antenna size is 18mm × 18mm. Further, a flexible conformal 4×4 ultra-wideband antenna array, in a format similar to that of a bra, was developed for a radar-based breast cancer detection system.

BER performance of implant-to-air high-speed UWB data communications for neural recording systems.

Implant-to-air ultra-wideband communication systems are interesting for neural recording systems due to their low power consumption and high data-rates. In this paper we investigate the performance of an implant-to-air wireless link using a realistic model of the biological channel for neural recording systems. We propose an optimized fifth-derivative Gaussian pulse as a transmitted waveform for different modulations: binary phase shift keying (BPSK), on-off keying (OOK) and differential phase shift keying (DPSK). Monitoring of neural responses with high resolution in the brain requires a high data rate link as the number of electrodes is increased. Each electrode needs a data rate around 800 kb/s to support its neural channel. As we target more than 512 electrodes, we require a data link higher than 400 Mbps.

A low-power current-reuse dual-band analog front-end for multi-channel neural signal recording.

Thoroughly studying the brain activity of freely moving subjects requires miniature data acquisition systems to measure and wirelessly transmit neural signals in real time. In this application, it is mandatory to simultaneously record the bioelectrical activity of a large number of neurons to gain a better knowledge of brain functions. However, due to limitations in transferring the entire raw data to a remote base station, employing dedicated data reduction techniques to extract the relevant part of neural signals is critical to decrease the amount of data to transfer. In this work, we present a new dual-band neural amplifier to separate the neuronal spike signals (SPK) and the local field potential (LFP) simultaneously in the analog domain, immediately after the pre-amplification stage. By separating these two bands right after the pre-amplification stage, it is possible to process LFP and SPK separately. As a result, the required dynamic range of the entire channel, which is determined by the signal-to-noise ratio of the SPK signal of larger bandwidth, can be relaxed. In this design, a new current-reuse low-power low-noise amplifier and a new dual-band filter that separates SPK and LFP while saving capacitors and pseudo resistors. A four-channel dual-band (SPK, LFP) analog front-end capable of simultaneously separating SPK and LFP is implemented in a TSMC 0.18 µm technology. Simulation results present a total power consumption per channel of 3.1 µw for an input referred noise of 3.28 µV and a NEF for 2.07. The cutoff frequency of the LFP band is fc=280 Hz, and fL=725 Hz and fL=11.2 KHz for SPK, with 36 dB gain for LFP band 46 dB gain for SPK band.

Multicoil resonance-based parallel array for smart wireless power delivery.

This paper presents a novel resonance-based multicoil structure as a smart power surface to wirelessly power up apparatus like mobile, animal headstage, implanted devices, etc. The proposed powering system is based on a 4-coil resonance-based inductive link, the resonance coil of which is formed by an array of several paralleled coils as a smart power transmitter. The power transmitter employs simple circuit connections and includes only one power driver circuit per multicoil resonance-based array, which enables higher power transfer efficiency and power delivery to the load. The power transmitted by the driver circuit is proportional to the load seen by the individual coil in the array. Thus, the transmitted power scales with respect to the load of the electric/electronic system to power up, and does not divide equally over every parallel coils that form the array. Instead, only the loaded coils of the parallel array transmit significant part of total transmitted power to the receiver. Such adaptive behavior enables superior power, size and cost efficiency then other solutions since it does not need to use complex detection circuitry to find the location of the load. The performance of the proposed structure is verified by measurement results. Natural load detection and covering 4 times bigger area than conventional topologies with a power transfer efficiency of 55% are the novelties of presented paper.