A neural probe with up to 966 electrodes and up to 384 configurable channels in 0.13 μm SOI CMOS

In vivo recording of neural action-potential and local-field-potential signals requires the use of high-resolution penetrating probes. Several international initiatives to better understand the brain are driving technology efforts towards maximizing the number of recording sites while minimizing the neural probe dimensions. We designed and fabricated (0.13-μm SOI Al CMOS) a 384-channel configurable neural probe for large-scale in vivo recording of neural signals. Up to 966 selectable active electrodes were integrated along an implantable shank (70 μm wide, 10 mm long, 20 μm thick), achieving a crosstalk of −64.4 dB. The probe base (5 × 9 mm2) implements dual-band recording and a 1

Low-Noise Micro-Power Amplifiers for Biosignal Acquisition

There are many different types of biopotential signals, such as action potentials (APs), local field potentials (LFPs), electromyography (EMG), electrocardiogram (ECG), electroencephalogram (EEG), etc. Nerve action potentials play an important role for the analysis of human cognition, such as perception, memory, language, emotions, and motor control. EMGs provide vital information about the patients which allow clinicians to diagnose and treat many neuromuscular diseases, which could result in muscle paralysis, motor problems, etc. EEGs is critical in diagnosing epilepsy, sleep disorders, as well as brain tumors. Biopotential signals are very weak, which requires the biopotential amplifier to exhibit low input-referred noise. For example, EEGs have amplitudes from 1 μV [microvolt] to 100 μV [microvolt] with much of the energy in the sub-Hz [hertz] to 100 Hz [hertz] band. APs have amplitudes up to 500 μV [microvolt] with much of the energy in the 100 Hz [hertz] to 7 kHz [hertz] band. In wearable/implantable systems, the low-power operation of the biopotential amplifier is critical to avoid thermal damage to surrounding tissues, preserve long battery life, and enable wirelessly-delivered or harvested energy supply. For an ideal thermal-noise-limited amplifier, the amplifier power is inversely proportional to the input-referred noise of the amplifier. Therefore, there is a noise-power trade-off which must be well-balanced by the designers. In this work I propose novel amplifier topologies, which are able to significantly improve the noise-power efficiency by increasing the effective transconductance at a given current. In order to reject the DC offsets generated at the tissue-electrode interface, energy-efficient techniques are employed to create a low-frequency high-pass cutoff. The noise contribution of the high-pass cutoff circuitry is minimized by using power-efficient configurations, and optimizing the biasing and dimension of the devices. Sufficient common-mode rejection ratio (CMRR) and power supply rejection ratio (PSRR) are achieved to suppress common-mode interferences and power supply noises. Our design are fabricated in standard CMOS processes. The amplifiers’ performance are measured on the bench, and also demonstrated with biopotential recordings

Ultra-low power mixed-signal frontend for wearable EEGs

Electronics circuits are ubiquitous in daily life, aided by advancements in the chip design industry, leading to miniaturised solutions for typical day to day problems. One of the critical healthcare areas helped by this advancement in technology is electroencephalography (EEG). EEG is a non-invasive method of tracking a person's brain waves, and a crucial tool in several healthcare contexts, including epilepsy and sleep disorders. Current ambulatory EEG systems still suffer from limitations that affect their usability. Furthermore, many patients admitted to emergency departments (ED) for a neurological disorder like altered mental status or seizures, would remain undiagnosed hours to days after admission, which leads to an elevated rate of death compared to other conditions. Conducting a thorough EEG monitoring in early-stage could prevent further damage to the brain and avoid high mortality. But lack of portability and ease of access results in a long wait time for the prescribed patients. All real signals are analogue in nature, including brainwaves sensed by EEG systems. For converting the EEG signal into digital for further processing, a truly wearable EEG has to have an analogue mixed-signal front-end (AFE). This research aims to define the specifications for building a custom AFE for the EEG recording and use that to review the suitability of the architectures available in the literature. Another critical task is to provide new architectures that can meet the developed specifications for EEG monitoring and can be used in epilepsy diagnosis, sleep monitoring, drowsiness detection and depression study. The thesis starts with a preview on EEG technology and available methods of brainwaves recording. It further expands to design requirements for the AFE, with a discussion about critical issues that need resolving. Three new continuous-time capacitive feedback chopped amplifier designs are proposed. A novel calibration loop for setting the accurate value for a pseudo-resistor, which is a crucial block in the proposed topology, is also discussed. This pseudoresistor calibration loop achieved the resistor variation of under 8.25%. The thesis also presents a new design of a curvature corrected bandgap, as well as a novel DDA based fourth-order Sallen-Key filter. A modified sensor frontend architecture is then proposed, along with a detailed analysis of its implementation. Measurement results of the AFE are finally presented. The AFE consumed a total power of 3.2A (including ADC, amplifier, filter, and current generation circuitry) with the overall integrated input-referred noise of 0.87V-rms in the frequency band of 0.5-50Hz. Measurement results confirmed that only the proposed AFE achieved all defined specifications for the wearable EEG system with the smallest power consumption than state-of-art architectures that meet few but not all specifications. The AFE also achieved a CMRR of 131.62dB, which is higher than any studied architectures.Open Acces

A Two Channel Analog Front end Design AFE Design with Continuous Time Σ-Δ Modulator for ECG Signal

In this context, the AFE with 2-channels is described, which has high impedance for low power application of bio-medical electrical activity. The challenge in obtaining accurate recordings of biomedical signals such as EEG/ECG to study the human body in research work. This paper is to propose Multi-Vt in AFE circuit design cascaded with CT modulator. The new architecture is anticipated with two dissimilar input signals filtered from 2-channel to one modulator. In this methodology, the amplifier is low powered multi-VT Analog Front-End which consumes less power by applying dual threshold voltage. Type -I category 2 channel signals of the first mode: 50 and 150 Hz amplified from AFE are given to 2nd CT sigma-delta ADC. Depict the SNR and SNDR as 63dB and 60dB respectively, consuming the power of 11mW. The design was simulated in a 0.18 um standard UMC CMOS process at 1.8V supply. The AFE measured frequency response from 50 Hz to 360 Hz, depict the SNR and SNDR as 63dB and 60dB respectively, consuming the power of 11mW. The design was simulated in 0.18 m standard UMC CMOS process at 1.8V supply. The AFE measured frequency response from 50 Hz to 360 Hz, programmable gains from 52.6 dB to 72 dB, input referred noise of 3.5 μV in the amplifier bandwidth, NEF of 3

Resource-Constrained Acquisition Circuits for Next Generation Neural Interfaces

The development of neural interfaces allowing the acquisition of signals from the cortex of the brain has seen an increasing amount of interest both in academic research as well as in the commercial space due to their ability to aid people with various medical conditions, such as spinal cord injuries, as well as their potential to allow more seamless interactions between people and machines. While it has already been demonstrated that neural implants can allow tetraplegic patients to control robotic arms, thus to an extent returning some motoric function, the current state of the art often involves the use of heavy table-top instruments connected by wires passing through the patient’s skull, thus making the applications impractical and chronically infeasible. Those limitations are leading to the development of the next generation of neural interfaces that will overcome those issues by being minimal in size and completely wireless, thus paving a way to the possibility of their chronic application. Their development however faces several challenges in numerous aspects of engineering due to constraints presented by their minimal size, amount of power available as well as the materials that can be utilised. The aim of this work is to explore some of those challenges and investigate novel circuit techniques that would allow the implementation of acquisition analogue front-ends under the presented constraints. This is facilitated by first giving an overview of the problematic of recording electrodes and their electrical characterisation in terms of their impedance profile and added noise that can be used to guide the design of analogue front-ends. Continuous time (CT) acquisition is then investigated as a promising signal digitisation technique alternative to more conventional methods in terms of its suitability. This is complemented by a description of practical implementations of a CT analogue-to-digital converter (ADC) including a novel technique of clockless stochastic chopping aimed at the suppression of flicker noise that commonly affects the acquisition of low-frequency signals. A compact design is presented, implementing a 450 nW, 5.5 bit ENOB CT ADC, occupying an area of 0.0288 mm2 in a 0.18 μm CMOS technology, making this the smallest presented design in literature to the best of our knowledge. As completely wireless neural implants rely on power delivered through wireless links, their supply voltage is often subject to large high frequency variations as well voltage uncertainty making it necessary to design reference circuits and voltage regulators providing stable reference voltage and supply in the constrained space afforded to them. This results in numerous challenges that are explored and a design of a practical implementation of a reference circuit and voltage regulator is presented. Two designs in a 0.35 μm CMOS technology are presented, showing respectively a measured PSRR of ≈60 dB and ≈53 dB at DC and a worst-case PSRR of ≈42 dB and ≈33 dB with a less than 1% standard deviation in the output reference voltage of 1.2 V while consuming a power of ≈7 μW. Finally, ΣΔ modulators are investigated for their suitability in neural signal acquisition chains, their properties explained and a practical implementation of a ΣΔ DC-coupled neural acquisition circuit presented. This implements a 10-kHz, 40 dB SNDR ΣΔ analogue front-end implemented in a 0.18 μm CMOS technology occupying a compact area of 0.044 μm2 per channel while consuming 31.1 μW per channel.Open Acces

Ultra low power wearable sleep diagnostic systems

Sleep disorders are studied using sleep study systems called Polysomnography that records several biophysical parameters during sleep. However, these are bulky and are typically located in a medical facility where patient monitoring is costly and quite inefficient. Home-based portable systems solve these problems to an extent but they record only a minimal number of channels due to limited battery life. To surmount this, wearable sleep system are desired which need to be unobtrusive and have long battery life. In this thesis, a novel sleep system architecture is presented that enables the design of an ultra low power sleep diagnostic system. This architecture is capable of extending the recording time to 120 hours in a wearable system which is an order of magnitude improvement over commercial wearable systems that record for about 12 hours. This architecture has in effect reduced the average power consumption of 5-6 mW per channel to less than 500 uW per channel. This has been achieved by eliminating sampled data architecture, reducing the wireless transmission rate and by moving the sleep scoring to the sensors. Further, ultra low power instrumentation amplifiers have been designed to operate in weak inversion region to support this architecture. A 40 dB chopper-stabilised low power instrumentation amplifiers to process EEG were designed and tested to operate from 1.0 V consuming just 3.1 uW for peak mode operation with DC servo loop. A 50 dB non-EEG amplifier continuous-time bandpass amplifier with a consumption of 400 nW was also fabricated and tested. Both the amplifiers achieved a high CMRR and impedance that are critical for wearable systems. Combining these amplifiers with the novel architecture enables the design of an ultra low power sleep recording system. This reduces the size of the battery required and hence enables a truly wearable system.Open Acces

An Oversampled Analog To Digital Converter For Acquiring Neural Signals

A third order delta-sigma modulator and associated low-pass digital filter is designed for an analog to digital converter: ADC) for sensing bioelectric phenomena. The third order noise shaping reduces the quantization noise in the baseband and the digital lowpass filter greatly attenuates the out of band quantization noise, increasing the effective number of bits. As part of a neural signal acquisition system designed by The BrainScope Company to capture Electro-Encephalogram: EEG) and Automated Brainstem Response: ABR) signals, this paper describes the design of a third order Delta-Sigma modulator which meets or exceeds the low noise specifications mandated by previous BrainScope products. The third order cascaded delta-sigma modulator attains a resolution of 12.3 bits in a signal bandwidth of 3kHz and 14.9 bits in a signal bandwidth of 100Hz, operating from a +/- 1.76V reference with a 250kHz clock

Hardware design of a portable medical device to measure the quadriceps muscle group after a total knee arthroplasty by EMG, LBIA and clinical score methods

El propòsit d'aquest projecte és el disseny del hardware d'un dispositiu mèdic portàtil per a mesurar senyals d'electromiografia (EMG) i bioimpedància localitzada (LBIA), que s'utilitzarà per avaluar la progressió de dues pròtesis de genoll (Medial-Pivot i Ultra- Congruent) en pacients operats d'una artroplàstia total de genoll per a l'hospital Germans Trias i Pujol de Badalona. Per això, s'ha realitzat un estudi complet sobre els senyals d'EMG i LBIA, per tal de definir les característiques necessàries de l'equip mèdic i poder optimitzar el disseny electrònic. Per l'adquisició de senyals EMG, s'ha dissenyat i simulat un sistema compost per diferents fases, que treballen independentment per adquirir, amplificar, filtrar i adaptar el senyal EMG pel seu futur processament digital. D'altra banda, per obtenir valors de la bioimpedància localitzada dels diferents músculs que conformen el quàdriceps, s'ha dissenyat un sistema compost per dos grans blocs; el primer bloc és l'etapa d'injecció, on es genera i s'injecta un senyal feble de corrent altern a la zona a mesurar, mentre que el segon bloc, és l'etapa d'adquisició de senyals. Aquest últim s'encarrega d'adquirir la diferència de voltatge produïda per la injecció de corrent al múscul (anteriorment mencionat) per després calcular la bioimpedància a partir de la llei d'ohm. Tots els senyals són digitalitzats mitjançant el microcontrolador STM32F407VG, que s'encarregarà de processar i aconseguir les dades claus per determinar quina de les deus pròtesis desenvolupa una millor funció mecànica i una millor adaptació biològica. És important remarcar que tot el disseny, sigui per a EMG o LBIA s'ha dut a terme de manera discreta sense fer servir Front-Ends comercials o integrats complexos més que l'amplificador d'instrumentació o ADC. En addició, el present treball inclou una primera estimació dels costos de producció i fabricació per a una sola unitat, càlculs de consums i funcionament (sorolls, CMRR del sistema i amplada de banda) i una simulació completa d'EMG i LBIA per observar com funciona i es du a terme cada etapa del circuit. Finalment, en tractar-se d'un equip mèdic, també s'ha revisat la normativa aplicable i se n'ha analitzat l'impacte ambiental, s'ha proposat i definit diferents punts per a futurs treballs, com podria ser la validació i testatge de l'equip, càlculs més aproximats de consums i perfilar la bill of materials (BOM) per a grans demandes de components.The purpose of this project is the hardware design of a portable medical device to measure electromyography (EMG) and localized bioimpedance (LBIA) signals, which will be used to evaluate the adaptability and progression of two knee prostheses (medial-pivot and ultra-congruent) in patients undergoing total knee arthroplasty at the Germans Trias i Pujol Hospital in Badalona. For this, the present work undercovers the relevant properties of the EMG and LBIA signals in order to define the characteristics of the medical equipment and thus optimize its electronic design. For the EMG measurements, a system made up of different stages has been designed and simulated. These phases work independently to acquire, amplify, filter, and adapt the EMG signal for its further digital processing. On the other hand, to obtain the bioimpedance values of different quadriceps muscles, a system composed of two large blocks has been designed; the first is the injection block, where a weak alternating current signal is generated and injected into the area to be measured, while the second block is the signal acquisition stage. The purpose of the latter is to acquire the voltage difference produced by the injection of current (mentioned above) and then obtain the bioimpedance from Ohm's law. All the signals are digitized from the STM32F407VG microcontroller, which will be in charge of processing and obtaining the key data to determine which of the two prostheses performs a better mechanical function and biological adaptation. It is important to note that the entire design, whether for EMG or LBIA, has been developed discreetly without using commercial Front-Ends or complex ICs other than the instrumentation amplifier or ADC. In addition, the thesis includes a first estimation of the production and manufacturing costs for a single unit, calculations of consumption and work operation (noise, CMRR of the system and bandwidth) and a complete simulation of EMG and LBIA to observe how it works on each stage for both circuits. Finally, as it is a medical device, the applicable regulations have also been reviewed and its environmental impact has been analysed. Additionally, different points have been proposed and defined for future work, such as the construction of the PCB and its respective validation, improving both the consumption calculations and the list of materials (BOM) for large component demands.El propósito de este proyecto es el diseño del Hardware de un dispositivo médico portátil para mediciones de electromiografía (EMG) y bioimpedancia localizada (LBIA), que se utilizará para estudiar la evolución de la adaptabilidad y funcionamiento de dos prótesis de rodilla (medial-pívot y ultracongruente) en pacientes operados de artroplastia total de rodilla en el Hospital Germans Trias i Pujol de Badalona. Para ello, se ha realizado un estudio exhaustivo sobre las propiedades de las señales de EMG y LBIA con la finalidad de definir las características del equipo médico y de esta forma, optimizar el diseño electrónico del mismo. Para la lectura de mediciones EMG, se ha diseñado y simulado un sistema constituido por distintas etapas, que trabajan independientemente para adquirir, amplificar, filtrar, y adaptarla señal EMG para su posterior procesado digital. Por otro lado, para obtener los valores de bioimpedancia de distintos músculos del cuádriceps, se ha diseñado un sistema compuesto por dos grandes bloques; el primero es el bloque de inyección, donde se genera y se inyecta una señal débil de corriente alterna en la zona a medir, mientras que el segundo bloque es la etapa de adquisición de señales. Esta última tiene como finalidad adquirir la diferencia de voltaje producido por la inyección de corriente (anteriormente mencionada) para después obtener la bioimpedancia a partir de la ley de ohm. Todas las señales son digitalizadas a partir del microcontrolador STM32F407VG, que se encargará de procesar y obtener los datos claves para determinar cuál de las dos prótesis desempeña una mejor función mecánica y adaptación biológica. Es importante remarcar que todo el diseño, ya sea para EMG o LBIA, se ha desarrollado de manera discreta sin usar Front-Ends comerciales o integrados complejos más que el amplificador de instrumentación o ADC. En adición, la tesis incluye una primera estimación de los costes de producción y fabricación para una sola unidad, cálculos de consumos y funcionamiento (ruidos, CMRR del sistema y ancho de banda) y una simulación completa de EMG y LBIA para observar cómo funciona y se desarrolla cada etapa de los distintos circuitos. Finalmente, al tratarse de un equipo médico, también se ha revisado la normativa aplicable y se ha analizado el impacto ambiental del mismo. Por último, se han propuesto y definido distintos puntos para futuros trabajos, como es la construcción de la PCB y su respectiva validación, realizar cálculos más aproximados de consumos y perfilar la lista de materiales (BOM) para grandes demandas de componentes

Wearable electroencephalography for long-term monitoring and diagnostic purposes

Truly Wearable EEG (WEEG) can be considered as the future of ambulatory EEG units, which are the current standard for long-term EEG monitoring. Replacing these short lifetime, bulky units with long-lasting, miniature and wearable devices that can be easily worn by patients will result in more EEG data being collected for extended monitoring periods. This thesis presents three new fabricated systems, in the form of Application Specific Integrated Circuits (ASICs), to aid the diagnosis of epilepsy and sleep disorders by detecting specific clinically important EEG events on the sensor node, while discarding background activity. The power consumption of the WEEG monitoring device incorporating these systems can be reduced since the transmitter, which is the dominating element in terms of power consumption, will only become active based on the output of these systems. Candidate interictal activity is identified by the developed analog-based interictal spike selection system-on-chip (SoC), using an approximation of the Continuous Wavelet Transform (CWT), as a bandpass filter, and thresholding. The spike selection SoC is fabricated in a 0.35 μm CMOS process and consumes 950 nW. Experimental results reveal that the SoC is able to identify 87% of interictal spikes correctly while only transmitting 45% of the data. Sections of EEG data containing likely ictal activity are detected by an analog seizure selection SoC using the low complexity line length feature. This SoC is fabricated in a 0.18 μm CMOS technology and consumes 1.14 μW. Based on experimental results, the fabricated SoC is able to correctly detect 83% of seizure episodes while transmitting 52% of the overall EEG data. A single-channel analog-based sleep spindle detection SoC is developed to aid the diagnosis of sleep disorders by detecting sleep spindles, which are characteristic events of sleep. The system identifies spindle events by monitoring abrupt changes in the input EEG. An approximation of the median frequency calculation, incorporated as part of the system, allows for non-spindle activity incorrectly identified by the system as sleep spindles to be discarded. The sleep spindle detection SoC is fabricated in a 0.18 μm CMOS technology, consuming only 515 nW. The SoC achieves a sensitivity and specificity of 71.5% and 98% respectively.Open Acces