Integrated circuit design for implantable neural interfaces

Progress in microfabrication technology has opened the way for new possibilities in neuroscience and medicine. Chronic, biocompatible brain implants with recording and stimulation capabilities provided by embedded electronics have been successfully demonstrated. However, more ambitious applications call for improvements in every aspect of existing implementations. This thesis proposes two prototypes that advance the field in significant ways. The first prototype is a neural recording front-end with spectral selectivity capabilities that implements a design strategy that leads to the lowest reported power consumption as compared to the state of the art. The second one is a bidirectional front-end for closed-loop neuromodulation that accounts for self-interference and impedance mismatch thus enabling simultaneous recording and stimulation. The design process and experimental verification of both prototypes is presented herein

Optimizations and applications in head-mounted video-based eye tracking

Video-based eye tracking techniques have become increasingly attractive in many research fields, such as visual perception and human-computer interface design. The technique primarily relies on the positional difference between the center of the eye\u27s pupil and the first-surface reflection at the cornea, the corneal reflection (CR). This difference vector is mapped to determine an observer\u27s point of regard (POR). In current head-mounted video-based eye trackers, the systems are limited in several aspects, such as inadequate measurement range and misdetection of eye features (pupil and CR). This research first proposes a new `structured illumination\u27 configuration, using multiple IREDs to illuminate the eye, to ensure that eye positions can still be tracked even during extreme eye movements (up to ±45° horizontally and ±25° vertically). Then eye features are detected by a two-stage processing approach. First, potential CRs and the pupil are isolated based on statistical information in an eye image. Second, genuine CRs are distinguished by a novel CR location prediction technique based on the well-correlated relationship between the offset of the pupil and that of the CR. The optical relationship of the pupil and CR offsets derived in this thesis can be applied to two typical illumination configurations - collimated and near-source ones- in the video-based eye tracking system. The relationships from the optical derivation and that from an experimental measurement match well. Two application studies, smooth pursuit dynamics in controlled static (laboratory) and unconstrained vibrating (car) environments were conducted. In the first study, the extended stimuli (color photographs subtending 2° and 17°, respectively) were found to enhance smooth pursuit movements induced by realistic images, and the eye velocity for tracking a small dot (subtending \u3c0.1°) was saturated at about 64 deg/sec while the saturation velocity occurred at higher velocities for the extended images. The difference in gain due to target size was significant between dot and the two extended stimuli, while no statistical difference existed between the two extended stimuli. In the second study, twovisual stimuli same as in the first study were used. The visual performance was impaired dramatically due to the whole body motion in the car, even in the tracking of a slowly moving target (2 deg/sec); the eye was found not able to perform a pursuit task as smooth as in the static environment though the unconstrained head motion in the unstable condition was supposed to enhance the visual performance

Low-power Wearable Healthcare Sensors

Advances in technology have produced a range of on-body sensors and smartwatches that can be used to monitor a wearer’s health with the objective to keep the user healthy. However, the real potential of such devices not only lies in monitoring but also in interactive communication with expert-system-based cloud services to offer personalized and real-time healthcare advice that will enable the user to manage their health and, over time, to reduce expensive hospital admissions. To meet this goal, the research challenges for the next generation of wearable healthcare devices include the need to offer a wide range of sensing, computing, communication, and human–computer interaction methods, all within a tiny device with limited resources and electrical power. This Special Issue presents a collection of six papers on a wide range of research developments that highlight the specific challenges in creating the next generation of low-power wearable healthcare sensors

Compressive Sensing and Multichannel Spike Detection for Neuro-Recording Systems

RÉSUMÉ Les interfaces cerveau-machines (ICM) sont de plus en plus importantes dans la recherche biomédicale et ses applications, tels que les tests et analyses médicaux en laboratoire, la cérébrologie et le traitement des dysfonctions neuromusculaires. Les ICM en général et les dispositifs d'enregistrement neuronaux, en particulier, dépendent fortement des méthodes de traitement de signaux utilisées pour fournir aux utilisateurs des renseignements sur l’état de diverses fonctions du cerveau. Les dispositifs d'enregistrement neuronaux courants intègrent de nombreux canaux parallèles produisant ainsi une énorme quantité de données. Celles-ci sont difficiles à transmettre, peuvent manquer une information précieuse des signaux enregistrés et limitent la capacité de traitement sur puce. Une amélioration de fonctions de traitement du signal est nécessaire pour s’assurer que les dispositifs d'enregistrements neuronaux peuvent faire face à l'augmentation rapide des exigences de taille de données et de précision requise de traitement. Cette thèse regroupe deux approches principales de traitement du signal - la compression et la réduction de données - pour les dispositifs d'enregistrement neuronaux. Tout d'abord, l’échantillonnage comprimé (AC) pour la compression du signal neuronal a été utilisé. Ceci implique l’usage d’une matrice de mesure déterministe basée sur un partitionnement selon le minimum de la distance Euclidienne ou celle de la distance de Manhattan (MDC). Nous avons comprimé les signaux neuronaux clairsemmés (Sparse) et non-clairsemmés et les avons reconstruit avec une marge d'erreur minimale en utilisant la matrice MDC construite plutôt. La réduction de données provenant de signaux neuronaux requiert la détection et le classement de potentiels d’actions (PA, ou spikes) lesquelles étaient réalisées en se servant de la méthode d’appariement de formes (templates) avec l'inférence bayésienne (Bayesian inference based template matching - BBTM). Par comparaison avec les méthodes fondées sur l'amplitude, sur le niveau d’énergie ou sur l’appariement de formes, la BBTM a une haute précision de détection, en particulier pour les signaux à faible rapport signal-bruit et peut séparer les potentiels d’actions reçus à partir des différents neurones et qui chevauchent. Ainsi, la BBTM peut automatiquement produire les appariements de formes nécessaires avec une complexité de calculs relativement faible.----------ABSTRACT Brain-Machine Interfaces (BMIs) are increasingly important in biomedical research and health care applications, such as medical laboratory tests and analyses, cerebrology, and complementary treatment of neuromuscular disorders. BMIs, and neural recording devices in particular, rely heavily on signal processing methods to provide users with nformation. Current neural recording devices integrate many parallel channels, which produce a huge amount of data that is difficult to transmit, cannot guarantee the quality of the recorded signals and may limit on-chip signal processing capabilities. An improved signal processing system is needed to ensure that neural recording devices can cope with rapidly increasing data size and accuracy requirements. This thesis focused on two signal processing approaches – signal compression and reduction – for neural recording devices. First, compressed sensing (CS) was employed for neural signal compression, using a minimum Euclidean or Manhattan distance cluster-based (MDC) deterministic sensing matrix. Sparse and non-sparse neural signals were substantially compressed and later reconstructed with minimal error using the built MDC matrix. Neural signal reduction required spike detection and sorting, which was conducted using a Bayesian inference-based template matching (BBTM) method. Compared with amplitude-based, energy-based, and some other template matching methods, BBTM has high detection accuracy, especially for low signal-to-noise ratio signals, and can separate overlapping spikes acquired from different neurons. In addition, BBTM can automatically generate the needed templates with relatively low system complexity. Finally, a digital online adaptive neural signal processing system, including spike detector and CS-based compressor, was designed. Both single and multi-channel solutions were implemented and evaluated. Compared with the signal processing systems in current use, the proposed signal processing system can efficiently compress a large number of sampled data and recover original signals with a small reconstruction error; also it has low power consumption and a small silicon area. The completed prototype shows considerable promise for application in a wide range of neural recording interfaces

NASA Tech Briefs, August 1990

Topics covered: New Product Ideas; NASA TU Services; Electronic Components and Circuits; Electronic Systems; Physical Sciences; Materials; Computer Programs; Mechanics; Machinery; Fabrication Technology; Mathematics and Information Sciences; Life Sciences

Compact Lens Technologies: Curved Image Sensor and Volumetric Imaging Efficiency

Compact image systems bring up people\u27s attention in the field of target recognition, surveillance, situation awareness or even photography. Conventional metrics assess image system based on image quality without considering systems\u27 volume. More comprehensive metrics, such as General Image-Quality Equation and the Targeting Task Performance metric, incorporates all image system components from object, lenses to detector and even imaging processing algorithm. All these key factors prohibit these metrics from being applied to image system in a convenient manner. Here, we propose a simple metric, volumetric imaging efficiency, considering both image quality and volume. Only concentrate on optical lenses enables the metric being implemented onto conventional bulk optics and flat optics efficiently. Curved image sensor with monocentric lenses shows an exceptional performance based on our metric but potentially challenging in fabrication due to conventional flat substrate process. Normally, this can be done with inorganic photodetector array and perform bending as the last step or organic photodetector being directly deposited on a curved plastic substrate. Inorganic method utilizes state-of-the-art CMOS technology but the interconnects suffer great strain and stress after bending and ultimately runs the risk of device failure while organic device ensures minimum strain, but the fabrication is not compatible with CMOS technology, thus a pattern transfer method is involved for contacts deposition. Here, we introduce both techniques and addressing their challenges. For inorganic device, several interconnect deposition methods are developed and both 1D and 2D bending test are performed to test their stretchability. For organic device, without CMOS circuity, we developed a new type of photodetector, frustrated organic photodetector (F-OPD), which enables single pixel selection by biasing device in different directions. A total of 45 devices are fabricated and perform as an input of 30X30 detectors array. A variety of noise sources are discussed and applied to each pixel. The image is then restored by color leveling and 2-points or 3-points non-uniformity correction (NUC). The results are compared with original figure as a proof of concept showing the capability of the device being extended to an array

Optoelectronics – Devices and Applications

Optoelectronics - Devices and Applications is the second part of an edited anthology on the multifaced areas of optoelectronics by a selected group of authors including promising novices to experts in the field. Photonics and optoelectronics are making an impact multiple times as the semiconductor revolution made on the quality of our life. In telecommunication, entertainment devices, computational techniques, clean energy harvesting, medical instrumentation, materials and device characterization and scores of other areas of R&D the science of optics and electronics get coupled by fine technology advances to make incredibly large strides. The technology of light has advanced to a stage where disciplines sans boundaries are finding it indispensable. New design concepts are fast emerging and being tested and applications developed in an unimaginable pace and speed. The wide spectrum of topics related to optoelectronics and photonics presented here is sure to make this collection of essays extremely useful to students and other stake holders in the field such as researchers and device designers

Group 14 and 15 elements as building blocks for low dimensional functional nanostructures

Carbon nanotubes (CNTs) are an interesting allotrope of carbon which can have a wide range of applications as they have extraordinary mechanical, electrical and thermal properties. All this makes CNTs an interesting nanomaterial for different applications ranging from mechanical sensors to electrical microelectrodes and even biological applications due to their biological compatibility. Beside the excellent material properties, the use of special structuring of these materials is of great importance. The random orientation of CNTs cannot be controlled which usually leads to irreproducible material which is not suitable for real world applications. Therefore, the controlled growth of vertically aligned carbon nanotubes (VACNTs) is considered in this work. VACNTs have been grown on Si/SiO2 substrates using a water-assisted chemical vapor deposition technique. By this technique highly crystalline, pure, low-layer multiwalled CNTs with a vertical orientation to the substrate are obtained. The parameters for the growth are optimized and even structuring of the VACNTs is possible obtaining VACNTs with different heights in one synthesis step. This structuring is the used to construct a nano-microstructured artificial-hair-cell-type sensor as an example for a mechanical sensor which can measure three-dimensional forces by the changing contact resistance between neighboring CNT bundles of different heights. Because to the excellent electrical properties together with the highly-increased surface area due to the vertical alignment of VACNTs, they are compared to randomly oriented CNTs for microelectrode applications. In this, the advantage of vertical alignment becomes clear in the dramatic decrease in impedance and enormous increase in capacity. These microelectrodes are then tested for biological applications for which the compatibility and growth pattern of cortical neurons on VACNTs is studied. While CNTs represent one-dimensional systems, also two-dimensional materials related to carbon such as graphene oxide and reduced graphene oxide are studied and used for gas-adsorption as well as liquids absorbents in combination with bacterial cellulose in the form of aerogels. Finally, phosphorene as an example of a two-dimensional material closely related to graphene is synthesized. Phosphorene, although structurally similar to graphene, it has a band gap in contrast to graphene which makes it an interesting material field-effect transistor devices as shown in this work

NASA Tech Briefs, Fall 1978

Topics covered: NASA TU Services: Technology Utilization services that can assist you in learning about and applying NASA technology; New Product Ideas: A summary of selected innovations of value to manufacturers for the development of new products; Electronic Components and Circuits; Electronic Systems; Physical Sciences; Materials; Life Sciences; Mechanics; Machinery; Fabrication Technology; Mathematics and Information Sciences