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.

A new molecular imprinted PEDOT glassy carbon electrode for carbamazepine detection.

An electrochemical sensor for the detection of carbamazepine was fabricated by the electropolymerization of PEDOT on glassy carbon electrodes. Molecular imprinted polymer sites were synthesized by cyclic voltammetry on the electrodes' surfaces providing high selectivity and sensitivity towards carbamazepine molecules. Scanning electron microscopy validated the formation of the polymer. Extraction of carbamazepine from the polymer was performed by immersion in acetonitrile and validated by ultraviolet-visible spectroscopy along with cyclic voltammetry experiments comparing pre- and post-template extraction data. Further cyclic voltammetry and square-wave voltammetry tests aided in characterizing the electrodes' response to carbamazepine concentration in PBS solution with [Fe(CN)6]3-/4- as a redox pair/mediator. The limits of detection and quantification were found to be 0.98 x 10-3 M and 2.97 x 10-3 M respectively. The biosensor was highly sensitive to carbamazepine molecules in comparison to non-imprinted electrodes, simple to construct and easy to operate.

Unsupervised Clustering of HRV Features Reveals Preictal Changes in Human Epilepsy.

Over a third of patients suffering from epilepsy continue to live with recurrent disabling seizures and would greatly benefit from personalized seizure forecasting. While electroencephalography (EEG) remains most popular for studying subject-specific epileptic precursors, dysfunctions of the autonomous nervous system, notably cardiac activity measured in heart rate variability (HRV), have also been associated with epileptic seizures. This work proposes an unsupervised clustering technique which aims to automatically identify preictal HRV changes in 9 patients who underwent simultaneous electrocardiography (ECG) and intracranial EEG presurgical monitoring at the University of Montreal Hospital Center. A 2-class k-means clustering combined with a quantitative preictal HRV change detection technique were adopted in a subject- and seizure-specific manner. Results indicate inter and intra-patient variability in preictal HRV changes (between 3.5 and 6.5 min before seizure onset) and a statistically significant negative correlation between the time of change in HRV state and the duration of seizures (p<0.05). The presented findings show promise for new avenues of research regarding multimodal seizure prediction and unsupervised preictal time assessment.Clinical Relevance- This study proposed an unsupervised technique for quantitatively identifying preictal HRV changes which can be eventually used to implement an ECG-based seizure forecasting algorithm.

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.

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.

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%.

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.

A transcutaneous power transfer interface based on a multicoil inductive link.

This paper presents a transcutaneous power transfer link based on a multicoil structure. Multicoil inductive links using 4-coil or 3-coil topologies have shown significant improvement over conventional 2-coil structures for transferring power transcutaneously across larger distances and with higher efficiency. However, such performance comes at the cost of additional inductors and capacitor in the system, which is not convenient in implantable applications. This paper presents a transcutaneous power transfer interface that takes advantage on a 3-coils inductive topology to achieve wide separation distances and high power transfer efficiency without increasing the size of the implanted device compared to a conventional 2-coil structure. In the proposed link, a middle coil is placed outside the body to act as a repeater between an external transmitting coil and an implanted receiving coil. The proposed structure allows optimizing the link parameters after implantation by changing the characteristics of the repeater coil. Simulation with a multilayer model of the biological tissues and measured results are presented for the proposed link.

Exponential current pulse generation for efficient very high-impedance multisite stimulation.

We describe in this paper an intracortical current-pulse generator for high-impedance microstimulation. This dual-chip system features a stimuli generator and a high-voltage electrode driver. The stimuli generator produces flexible rising exponential pulses in addition to standard rectangular stimuli. This novel stimulation waveform is expected to provide superior energy efficiency for action potential triggering while releasing less toxic reduced ions in the cortical tissues. The proposed fully integrated electrode driver is used as the output stage where high-voltage supplies are generated on-chip to significantly increase the voltage compliance for stimulation through high-impedance electrode-tissue interfaces. The stimuli generator has been implemented in 0.18-µm CMOS technology while a 0.8-µm CMOS/DMOS process has been used to integrate the high-voltage output stage. Experimental results show that the rectangular pulses cover a range of 1.6 to 167.2 µA with a DNL and an INL of 0.098 and 0.163 least-significant bit, respectively. The maximal dynamic range of the generated exponential reaches 34.36 dB at full scale within an error of ± 0.5 dB while all of its parameters (amplitude, duration, and time constant) are independently programmable over wide ranges. This chip consumes a maximum of 88.3 µ W in the exponential mode. High-voltage supplies of 8.95 and -8.46 V are generated by the output stage, boosting the voltage swing up to 13.6 V for a load as high as 100 kΩ.

Integrated high-voltage inductive power and data-recovery front end dedicated to implantable devices.

In near-field electromagnetic links, the inductive voltage is usually much larger than the compliance of low-voltage integrated-circuit (IC) technologies used for the implementation of implantable devices. Thus most integrated power-recovery approaches limit the induced signal to low voltages with inefficient shunt regulation or voltage clipping. In this paper, we propose using high-voltage (HV) complementary metal-oxide semiconductor technology to fully integrate the inductive power and data-recovery front end while adopting a step-down approach where the inductive voltage is left free up to 20 or 50 V. The advantage is that excessive inductive power will translate to an additional charge that can be stored in a capacitor, instead of shunting to ground excessive current with voltage limiters. We report the design of two consecutive HV custom ICs-IC1 and IC2-fabricated in DALSA semiconductor C08G and C08E technologies, respectively, with a total silicon area (including pads) of 4 and 9 mm(2), respectively. Both ICs include HV rectification and regulation; however, IC2 includes two enhanced rectifier designs, a voltage-doubler, and a bridge rectifier, as well as data recovery. Postlayout simulations show that both IC2 rectifiers achieve more than 90% power efficiency at a 1-mA load and provide enough room for 12-V regulation at a 3-mA load and a maximum-available inductive power of 50 mW only. Successful measurement results show that HV regulators provide a stable 3.3- to 12-V supply from an unregulated input up to 50 or 20 V for IC1 and IC2, respectively, with performance that matches simulation results.

A Low-Power Asynchronous Step-Down DC-DC Converter for Implantable Devices.

In this paper, we present a fully integrated asynchronous step-down switched capacitor dc-dc conversion structure suitable for supporting ultra-low-power circuits commonly found in biomedical implants. The proposed converter uses a fully digital asynchronous state machine as the heart of the control circuitry to generate the drive signals. To minimize the switching losses, the asynchronous controller scales the switching frequency of the drive signals according to the loading conditions. It also turns on additional parallel switches when needed and has a backup synchronous drive mode. This circuit regulates load voltages from 300 mV to 1.1 V derived from a 1.2-V input voltage. A total of 350 pF on-chip capacitance was implemented to support a maximum of 230-µ W load power, while providing efficiency up to 80%. The circuit validating the proposed concepts was fabricated in 0.13- µm complementary metal-oxide semiconductor technology. Experimental test results confirm the expected functionality and performance of the proposed circuit.

A novel low-power-implantable epileptic seizure-onset detector.

A novel implantable low-power integrated circuit is proposed for real-time epileptic seizure detection. The presented chip is part of an epilepsy prosthesis device that triggers focal treatment to disrupt seizure progression. The proposed chip integrates a front-end preamplifier, voltage-level detectors, digital demodulators, and a high-frequency detector. The preamplifier uses a new chopper stabilizer topology that reduces instrumentation low-frequency and ripple noises by modulating the signal in the analog domain and demodulating it in the digital domain. Moreover, each voltage-level detector consists of an ultra-low-power comparator with an adjustable threshold voltage. The digitally integrated high-frequency detector is tunable to recognize the high-frequency activities for the unique detection of seizure patterns specific to each patient. The digitally controlled circuits perform accurate seizure detection. A mathematical model of the proposed seizure detection algorithm was validated in Matlab and circuits were implemented in a 2 mm(2) chip using the CMOS 0.18- µm process. The proposed detector was tested by using intracerebral electroencephalography (icEEG) recordings from seven patients with drug-resistant epilepsy. The seizure signals were assessed by the proposed detector and the average seizure detection delay was 13.5 s, well before the onset of clinical manifestations. The measured total power consumption of the detector is 51 µW.

A low-power high-sensitivity CMOS mixed-signal seizure-onset detector.

In this paper, we present a new seizure detection algorithm and the associated CMOS circuitry implementation. The proposed low-power seizure detector is a good candidate for an implantable epilepsy prosthesis. The device is designed for patient-specific seizure detection with a one variable parameter. The parameter value is extracted from a single seizure that is subsequently excluded from the validation phase. A two-path system is also proposed to minimize the detection delay. The algorithm is first validated using MATLAB® tools and then implemented and validated using circuits designed in a standard 0.18-µm CMOS process with a total power dissipation of 7.08 µW. A total of 13 seizures from two drug-resistant epileptic patients are assessed using the proposed algorithm and resulted in 100% sensitivity and a mean detection delay of 9.7 s after electrical onset.

CMOS/microfluidic Lab-on-chip for cells-based diagnostic tools.

We describe in this paper cells sensing and manipulation methods, as well as platforms based on Lab-on-chip devices. Among other contributions, new circuit and microfluidic techniques, and packaging methods are proposed for efficient cells manipulation and detection. The proposed devices include high-sensitivity sensing circuits (200 mV/fF), low-pressure liquid injection interfaces (< 0.65 psi), low-voltage manipulation signals, direct-write microfluidic fabrication technique on top of CMOS based capacitive sensors. In addition, several types of electrode arrays (square and L-shaped) are used for the manipulation of various types of cells and particles.

A mixed-signal multichip neural recording interface with bandwidth reduction.

We present a multichip structure assembled with a medical-grade stainless-steel microelectrode array intended for neural recordings from multiple channels. The design features a mixed-signal integrated circuit (IC) that handles conditioning, digitization, and time-division multiplexing of neural signals, and a digital IC that provides control, bandwidth reduction, and data communications for telemetry toward a remote host. Bandwidth reduction is achieved through action potential detection and complete capture of waveforms by means of onchip data buffering. The adopted architecture uses high parallelism and low-power building blocks for safety and long-term implantability. Both ICs are fabricated in a CMOS 0.18-mum process and are subsequently mounted on the base of the microelectrode array. The chips are stacked according to a vertical integration approach for better compactness. The presented device integrates 16 channels, and is scalable to hundreds of recording channels. Its performance was validated on a testbench with synthetic neural signals. The proposed interface presents a power consumption of 138 muW per channel, a size of 2.30 mm(2), and achieves a bandwidth reduction factor of up to 48 with typical recordings.

Micro-Organism-on-Chip: Emerging Direct-Write CMOS-Based Platform for Biological Applications.

We describe the emerging applications of direct-write CMOS-based lab-on-chip which consists of capacitive sensors integrated with microfluidic structures. The microfluidic components are implemented through direct-write microfabrication process (DWFP) on a variety of substrates including integrated circuits. We put forward the recent advances of DWFP for different applications while our focus is placed on biological testing through a novel on-chip capacitive measurement method. We thereafter reveal the viability of this approach for biosensing purposes by demonstrating and discussing the experimental results on micro-organisms. These results are in full agreement with the bio-interface model and other features presented throughout the paper.

Electrode-tissues interface: modeling and experimental validation.

The electrode-tissues interface (ETI) is one of the key issues in implantable devices such as stimulators and sensors. Once the stimulator is implanted, safety and reliability become more and more critical. In this case, modeling and monitoring of the ETI are required. We propose an empirical model for the ETI and a dedicated integrated circuit to measure its corresponding complex impedance. These measurements in the frequency range of 1 Hz to 100 kHz were achieved in acute dog experiments. The model demonstrates a closer fitting with experimental measurements. In addition, a custom monitoring device based on a stimuli current generator has been completed to evaluate the phase shift and voltage across the electrodes and to transmit wirelessly the values to an external controller. This integrated circuit has been fabricated in a CMOS 0.18 microm process, which consumes 4 mW only during measurements and occupies an area of 1 mm(2).

A highly flexible system for microstimulation of the visual cortex: design and implementation.

This paper presents the design of a system intended to be used as a prosthesis allowing profoundly visually impaired patients to recover partial vision by means of microstimulation in the primary visual cortex area. The main component of the system is a bio-electronic device to be implanted inside the skull of the user, composed of a plurality of stimulation modules, whose actions are controlled via an interface module. Power and data are transmitted to the implant wirelessly through a bidirectional inductive link, allowing diagnosis of the stimulating device and its environment after implantation, as well as power delivery optimization. A high level of flexibility is supported in terms of stimulation parameters, but a configurable communication protocol allows the device to be used with maximum efficiency. The core of an external controller implemented in a system on a programmable chip is also presented, performing data conversion and timing management such that phosphene intensity can be modulated by any parameter defining stimulation, either at the pulse level or in the time domain. Measured performances achieved with a prototype using two types of custom ASICs implemented in a 0.18-mum CMOS process and commercial components fulfill the requirements for a complete visual prosthesis for humans. When on/off activation is used with predefined parameters, stimuli measured on an electronic test bench could attain a rate in excess of 500 k pulses/s.

A Hybrid Microfluidic/CMOS Capacitive Sensor Dedicated to Lab-on-Chip Applications.

A hybrid microfluidic/IC capacitive sensor is presented in this paper for highly integrated lab-on-chips (LoCs). We put forward the design and implementation of a charge based capacitive sensor array in 0.18-mum CMOS process. This sensor chip is incorporated with a microfluidic channel using direct-write microfluidic fabrication process (DWFP). The design, construction and experimental results as well are demonstrated using four different chemical solutions with known dielectric constants. The proposed highly sensitive CMOS capacitive sensor (ap530 mV/fF) along with low complexity DWFP emerges as clear favorite for LoC applications.