Artifact-Aware Analogue/Mixed-Signal Front-Ends for Neural Recording Applications

This paper presents a brief review of techniques to overcome the problems associated with artifacts in analog frontends for neural recording applications. These techniques are employed for handling Common-Mode (CM) Differential-Mode (DM) artifacts and include techniques such as Average Template Subtraction, Channel Blanking or Blind Adaptive Stimulation Artifact Rejection (ASAR), among others. Additionally, a new technique for DM artifacts compression is proposed. It allows to compress these artifacts to the requirements of the analog frontend and, afterwards, it allows to reconstruct the whole artifact or largely suppress it.Ministerio de Economía y Empresa TEC2016-80923-

A 16-Channel Wireless Neural Recording System-on-Chip with CHT Feature Extraction Processor in 65nm CMOS

Wireless implantable neural recording chips enable multichannel data acquisition with high spatiotemporal resolution in situ. Recently, the use of machine learning approaches on neural data for diagnosis and prosthesis control have renewed the interest in this field, and increased even more the demand for multichannel data. However, simultaneous data acquisition from many channels is a grand challenge due to data rate and power limitations on wireless transmission for implants. As a result, recent studies have focused on on-chip classifiers, despite the fact that only primitive classifiers can be placed on resource-constrained chips. Moreover, robustness of the chosen algorithm cannot be guaranteed pre-implantation due to the scarcity of patient-specific data; waveforms can change over time due to electrode micro migration or tissue reaction, highlighting the need for robust adaptive features

An AC-Coupled Wideband Neural Recording Front-End With Sub-1 mm² × fJ/conv-step Efficiency and 0.97 NEF

This letter presents an energy-and-area-efficient ac-coupled front-end for the multichannel recording of wideband neural signals. The proposed unit conditions local field and action potentials using an inverter-based capacitively coupled low-noise amplifier, followed by a per-channel 10-b asynchronous SAR ADC. The adaptation of unit-length capacitors minimizes the ADC area and relaxes the amplifier gain so that small coupling capacitors can be integrated. The prototype in 65-nm CMOS achieves 4× smaller area and 3× higher energy–area efficiency compared to the state of the art with 164 μm×40μm footprint and 0.78 mm²× fJ/conv-step energy-area figure of merit. The measured 0.65- μW power consumption and 3.1 - μVrms input-referred noise within 1 Hz–10 kHz bandwidth correspond to a noise efficiency factor of 0.97

An AC-Coupled Wideband Neural Recording Front-End With Sub-1 mm² × fJ/conv-step Efficiency and 0.97 NEF

This letter presents an energy-and-area-efficient ac-coupled front-end for the multichannel recording of wideband neural signals. The proposed unit conditions local field and action potentials using an inverter-based capacitively coupled low-noise amplifier, followed by a per-channel 10-b asynchronous SAR ADC. The adaptation of unit-length capacitors minimizes the ADC area and relaxes the amplifier gain so that small coupling capacitors can be integrated. The prototype in 65-nm CMOS achieves 4× smaller area and 3× higher energy–area efficiency compared to the state of the art with 164 μm×40μm footprint and 0.78 mm²× fJ/conv-step energy-area figure of merit. The measured 0.65- μW power consumption and 3.1 - μVrms input-referred noise within 1 Hz–10 kHz bandwidth correspond to a noise efficiency factor of 0.97

A HIGHLY-SCALABLE DC-COUPLED DIRECT-ADC NEURAL RECORDING CHANNEL ARCHITECTURE WITH INPUT-ADAPTIVE RESOLUTION

This thesis presents the design, development, and characterization of a novel neural recording channel architecture with (a) quantization resolution that is adaptive to the input signal's level of activity, (b) fully-dynamic power consumption that is linearly proportional to the recording resolution, and (c) immunity to DC offset and drifts at the input. Our results demonstrate the proposed design's capability in conducting neural recording with near lossless input-adaptive data compression, leading to a significant reduction in the energy required for both recording and data transmission, hence allowing for a potential high scaling of the number of recording channels integrated on a single implanted microchip without the need to increase the power budget. The proposed channel with the implemented compression technique is implemented in a standard 130nm CMOS technology with overall power consumption of 7.6uW and active area of 92×92µm for the implemented digital-backend

Wireless Communication System for Submucosal Implants

Refluxní choroba jícnu (GERD) a gastroparéza jsou dvě nemoci gastrointestinálního traktu (GIT), které můžou být charakterizovány nedostatečnou funkcí příslušné svaloviny. U refluxní choroby jícnu nedochází k uzávěru dolnojícnového svěrače, což umožňuje vstup kyselého obsahu žaludku do jícnu. Gastroparéza je charakteristická částečnou paralýzou žaludku, což vede k tomu, že potrava v něm zůstává po dobu delší, než je běžné. Léčba těchto onemocnění je zpravidla medikamentózní nebo chirurgická, která s sebou nese zvýšená rizika. Endoskopie zažívá v posledních letech zvýšený zájem, protože se jedná o téměř neinvazivní techniku pro zákroky v GIT. Cilem této diplomové práce je vývoj bezdrátového rozhraní pro aktivní implantabilní zdravotnický prostředek (AIMD), který by mohl být použit pro léčbu GERD a gastroparézy. Zařízení je implantováno technikou, která se nazývá "endoscopic submucosal pocketing". Práce je specificky zaměřena na vývoj bezdrátového komunikačního rozhraní provozovaného v pásmu MEDS. Konvoluční kodování a šifrování je vyvinuto a implementováno. Prototyp AIMD s biokompatibilním obalem a zařízením pro příjem dat a nabíjením bylo vyvinuto a navržený obousměrný bezdrátový komunikační řetězec byl implementován v jazyce C s použitím mikrokontrolerů PIC a Si4455 radiového transceiveru. Nakonec bylo zařízení otestováno jeho implantací do submukozy v prasečím žaludku pomocí endoskopu, čímž byla otestována možnost jeho využití v navazujícím výzkumu.Gastroesophageal reflux disease (GERD) and gastroparesis are two diseases of gastrointestinal tract (GIT) which can be characterized by the disorder of muscle tissue. In GERD, the lower esophageal sphincter does not close properly, allowing the acidic contents of stomach to enter esophagus. Gastroparesis is characterized by partial paralysis of stomach, resulting in food remaining there for an abnormally long time. Treatment for these diseases includes medication and invasive surgery which is dangerous. In recent years, endoscopy is getting attention because it is virtually non-invasive technique for surgeries inside GIT. The goal of this thesis is the development of wireless link for an active implantable medical device (AIMD) which could be used in treatment of GERD and gastroparesis. The device is implanted using a technique called endoscopic submucosal pocketing. Focus is given to the design of the wireless communication link which is operated in MEDS band. Convolutional coding and encryption is developed and implemented in the system. A prototype of AIMD with biocompatible housing and a receiver/charger device was developed and the proposed bidirectional wireless communication link was implemented using C language, PIC microcontrollers and Si4455 radio transceivers. Finally, the device was implanted into submucosa of a pig stomach with an endoscope to test the feasibility of using the device during ongoing research

A HIGHLY-SCALABLE DC-COUPLED DIRECT-ADC NEURAL RECORDING CHANNEL ARCHITECTURE WITH INPUT-ADAPTIVE RESOLUTION

This thesis presents the design, development, and characterization of a novel neural recording channel architecture with (a) quantization resolution that is adaptive to the input signal's level of activity, (b) fully-dynamic power consumption that is linearly proportional to the recording resolution, and (c) immunity to DC offset and drifts at the input. Our results demonstrate the proposed design's capability in conducting neural recording with near lossless input-adaptive data compression, leading to a significant reduction in the energy required for both recording and data transmission, hence allowing for a potential high scaling of the number of recording channels integrated on a single implanted microchip without the need to increase the power budget. The proposed channel with the implemented compression technique is implemented in a standard 130nm CMOS technology with overall power consumption of 7.6uW and active area of 9292m for the implemented digital-backend

Bionode5.0: A miniature, wireless, closed-loop biological implant for neuromodulation

The needs for electrotherapy, using electrical devices, are significantly increasing, due to limitations that pharmaceutical therapies may have, such as unignorable side effects and meager side effects on a multitude of cardiovascular and neurological diseases. To research on electrotherapy using an implantable electronic module, a miniature, wireless, and closed-loop implantable device, called Bionode , has been developed at Center for Implantable Device, directed by Dr. Pedro Irazoqui. Bionode4.1, the most recent version of the Bionode, is a device that consists of three different printed circuit boards(PCB), including a wireless communication system, an inductive power receiving system, and a two-channel recording system with a stimulator that has an ability to output a biphasic constant current stimulation. However, a few issues were brought to the surface during the fabrication process and in-vivo animal tests: 1) Unwanted data loss due to the failure of communication between the device and the Base Station, 2) stimulator\u27s imbalanced output with glitches and noise, 3) structural complexity that made debugging and constructing the device difficult, 4) device configuration, which could not be customized for the specific applications. These limitations found in Bionode 4.1 led to the development of the new version of Bionode, Bionode 5.0 . In order to increase the fidelity of the data transmission, a meandered inverted F trace antenna, which can cover the 2.4 GHz industrial, scientific, and medical (ISM) radio band, was designed and implemented in the wireless communication system of the Bionode 5.0. In order to resolve the stimulation issue, the old stimulator built in Bionode 4.1 was replaced with an upgraded stimulation circuitry that consists of the additional feedback system and the switches for suppressing the imbalanced pulses and controlling the unwanted glitches on the output. Re-optimizing the overall floor plan of the device and utilizing a new type of board-to-board connector solved the issues related to the structure and customizability. As a result, Bionode 5.0 with the smaller volume and the larger utilizable surface area resolved the issues that Binode4.1 had and would potentially allow the users to widely utilize the new version in various applications for the medical research

Wireless Implantable ICs for Energy-Efficient Long-Term Ambulatory EEG Monitoring

This thesis presents the design, development, and experimental characterization of wireless subcutaneous implantable integrated circuits and systems for long-term ambulatory EEG monitoring. Application-, system- and circuit-level requirements for such a device are discussed and a critical review of the state-of-the-art academic and currently available commercial solutions are provided. Two prototypes are presented: The first prototype presented in Chapter 2 is an 8-channel wireless implantable device with a 2.5×1.5 mm2 custom-designed integrated circuit implemented using CMOS 180nm technology at its core. The microchip is fabricated and the measurement results showing its efficacy in EEG signal recording in terms of input-referred noise, voltage gain, signal-to-noise ratio, and power consumption are presented. The chip is implemented together with a BLE 5.0 module on the same platform. Our vision and discussions on biocompatible encapsulation of this system, as well as its integration with a microelectrode array as also provided. The second prototype, also implemented in CMOS 180nm technology and presented in Chapter 3, employs a novel EEG recording channel architecture that enables long-term implantation of EEG monitoring devices through significant improvement of their energy efficiency. The channel leverages the inherent sparsity of the EEG signals and conducts recording in an activity-dependent adaptive manner. Thanks to the proposed fully dynamic spectral-compressing architecture, the recording channels power consumption is drastically reduced. More importantly, the proposed architecture reduces the required wireless transmission throughput by more than an order of magnitude. Our test results on 10 different patients’ pre-recorded human EEG data shows an average of 12.6× improvement in the device’s energy efficiency