Ultrasound data communication system for bioelectronic medicines

PhD ThesisThe coming years may see the advent of distributed implantable devices to support bioelectronic medicinal treatments. Such treatments could be complementary and, in some cases, may even prove superior to pharmaceutical treatments for certain chronic disease conditions. Therefore, a significant research effort is being undertaken in the bioelectronics domain. Target conditions include diabetes, inflammatory bowel disease, lupus, and arthritis. Modern active medical implantable devices require communications to transmit information to the outside world or other implantable sub-systems. This can include physiological data, diagnostics, and parameters to optimise the therapeutic protocol. However, the communication scheme can be very challenging especially for deeper devices. Challenges include absorption and scattering by tissue, and the need to ensure there are no undesirable heating effects. Wired connectivity is undesirable and tissue absorption of traditional radio frequency and optical methods mean that ultrasound communications have significant potential in this niche. In this thesis, a reliable and efficient ultrasonic communication telemetry is presented. An omnidirectional transducer has been employed to implement intra body communication inside a model of the human body. A prototype has been implemented to evaluate the system performance in saline and up to 30 distance between the transmitter and receiver. Short pulses sequences with guard intervals have been employed to minimise the multipath effect that leads to an increase in the bit and thus packet error rates with distance. Error detection and correction code have been employed to improve communication at a low signal to noise ratio. The data rate is limited to 0.6 due to the necessary guard intervals. Energy per bit and current consumption for the transmitter and receiver main parts are presented and discussed in terms of battery life. Transmission can be achieved at an energy cost of 642 per bit data packet using on/off power cycling in the electronics

Advances in Bioengineering

The technological approach and the high level of innovation make bioengineering extremely dynamic and this forces researchers to continuous updating. It involves the publication of the results of the latest scientific research. This book covers a wide range of aspects and issues related to advances in bioengineering research with a particular focus on innovative technologies and applications. The book consists of 13 scientific contributions divided in four sections: Materials Science; Biosensors. Electronics and Telemetry; Light Therapy; Computing and Analysis Techniques

Learning-Based Hardware Design for Data Acquisition Systems

This multidisciplinary research work aims to investigate the optimized information extraction from signals or data volumes and to develop tailored hardware implementations that trade-off the complexity of data acquisition with that of data processing, conceptually allowing radically new device designs. The mathematical results in classical Compressive Sampling (CS) support the paradigm of Analog-to-Information Conversion (AIC) as a replacement for conventional ADC technologies. The AICs simultaneously perform data acquisition and compression, seeking to directly sample signals for achieving specific tasks as opposed to acquiring a full signal only at the Nyquist rate to throw most of it away via compression. Our contention is that in order for CS to live up its name, both theory and practice must leverage concepts from learning. This work demonstrates our contention in hardware prototypes, with key trade-offs, for two different fields of application as edge and big-data computing. In the framework of edge-data computing, such as wearable and implantable ecosystems, the power budget is defined by the battery capacity, which generally limits the device performance and usability. This is more evident in very challenging field, such as medical monitoring, where high performance requirements are necessary for the device to process the information with high accuracy. Furthermore, in applications like implantable medical monitoring, the system performances have to merge the small area as well as the low-power requirements, in order to facilitate the implant bio-compatibility, avoiding the rejection from the human body. Based on our new mathematical foundations, we built different prototypes to get a neural signal acquisition chip that not only rigorously trades off its area, energy consumption, and the quality of its signal output, but also significantly outperforms the state-of-the-art in all aspects. In the framework of big-data and high-performance computation, such as in high-end servers application, the RF circuits meant to transmit data from chip-to-chip or chip-to-memory are defined by low power requirements, since the heat generated by the integrated circuits is partially distributed by the chip package. Hence, the overall system power budget is defined by its affordable cooling capacity. For this reason, application specific architectures and innovative techniques are used for low-power implementation. In this work, we have developed a single-ended multi-lane receiver for high speed I/O link in servers application. The receiver operates at 7 Gbps by learning inter-symbol interference and electromagnetic coupling noise in chip-to-chip communication systems. A learning-based approach allows a versatile receiver circuit which not only copes with large channel attenuation but also implements novel crosstalk reduction techniques, to allow single-ended multiple lines transmission, without sacrificing its overall bandwidth for a given area within the interconnect's data-path

Acoustic Power Transfer Leveraging Piezoelectricity and Metamaterials

Acoustic power transfer, or ultrasonic power transfer (UPT) more specifically, has received growing attention as a viable approach for wireless power delivery to low-power electronic devices. It has found applications in powering biomedical implants, sensors in sealed metallic enclosures, and sensors deep in the ocean. The design of an efficient UPT system requires coupled multiphysics modeling to establish strategies toward maximizing the transferred power. This work, first, investigates different analytical and numerical models to analyze the performance of UPT systems to increase the transferred power. Various electromechanical models are developed to represent the transducer (transmitter or receiver) and overall system dynamics for a broad range of aspect ratios covering the diverse UPT applications. The main challenges that limit UPT system efficiency such as attenuation, power divergence, and reflection due to impedance mismatch issues are investigated using the developed models. These effects are investigated at the system level with an application to transfer power through metallic barriers using bonded piezoelectric disc transducers. A complete system for transferring power from the battery of a transmitter to the DC load of a receiver is designed and simulated, then experimentally tested. The experimental results of the system agree well with the modeling predictions, and the system can deliver 17.5 W to a DC load with a total DC-to-DC efficiency of 66 %. A second system with a portable and detachable dry-coupled transmitter is also experimentally tested. The dry-coupled system can deliver 3 W of DC power with 50 % efficiency from a 9V battery. Novel approaches using acoustic metamaterials/phononic crystals are introduced to enhance the efficiency of UPT through wave focusing. Specifically, two 3D phononic crystal structures based on air in a 3D-printed polymer matrix are introduced to manipulate acoustic waves both under water and in air. Two designs for gradient-index lenses are fabricated and experimentally characterized to focus acoustic waves on a piezoelectric receiver, thereby dramatically enhancing the power output. Finally, acoustic and electrical impedance matching are investigated for sending both power and data using ultrasonic waves. Several impedance matching techniques are proposed to maximize transducer bandwidth, power efficiency, as well as sensitivity for underwater data transfer. A novel approach is introduced for achieving simultaneous power and data transfer using frequency multiplexing with a single transducer. The introduced designs allow for configurable matching for maximizing power efficiency, maximizing data transfer, or simultaneously sending power to the transducer while receiving data with lower bandwidth.Ph.D

Optimal strategies for electrical stimulation with implantable neuromodulation devices

Electrical stimulation (ES) is a neuromodulation technique that uses electrical pulses to modulate the activity of excitable cells to provide a therapeutic effect. Many past and present ES applications use rectangular current waveforms that have been well studied and are easy to generate. However, an extensive body of scientific literature describes different stimulation waveforms and their potential benefits. A key measure of stimulation performance is the amplitude required to reach a certain percentual threshold of activation, as it directly influences important ES parameters such as energy consumption per pulse and charge density. The research summarized in this thesis was conducted to re-examine some of the most-commonly suggested ES waveform variations in a rodent in-vivo nerve-muscle preparation. A key feature of our experimental model is the ability to test stimulation with both principal electrode configurations, monopolar and bipolar, under computer control and in randomized order. Among the rectangular stimulation waveforms, we investigated the effect of interphase gaps (IPGs), asymmetric charge balanced pulses, and subthreshold conditioning pre-pulses. For all these rectangular waveforms, we surprisingly observed opposite effects in the monopolar compared to the bipolar stimulation electrode configuration. The rationale for this consistent observation was identified by analyzing electroneurograms (ENGs) of the stimulated nerve. In the monopolar configuration, biphasic pulses first evoked compound action potentials (eCAPs) as a response to the first field transition. In the bipolar electrode configuration, that is the mode in which many contemporary ES devices, including the envisioned miniaturized electroceuticals, operate, eCAPs were first elicited at the return electrode in response to the middle field transition of biphasic pulses. As all rectangular waveform variations achieve their effect by modulating the amplitude and timing of cathodic (excitatory) and anodic (inhibitory) field transitions, the inverted current profile at the bipolar return electrode explains these observed opposite effects. Further we investigated the claimed benefits of non-rectangular, Gaussian stimulation waveforms in our animal model. In our study only moderate energy savings of up to 17% were observed, a finding that is surprising in light of the predicted range of benefits of up to 60% energy savings with this novel waveform in question. Additionally, we identified a major disadvantage in terms of substantially increased maximum instantaneous power requirements with Gaussian compared to rectangular stimuli. We examined physiological changes in fast twitch muscle following motor nerve injury, and optimal stimulation strategies for activation of denervated muscle. While a high frequency doublet has previously been identified to enhance stimulation efficiency of healthy fast twitch muscle, an effect that has been termed “doublet effect”, we here show that this benefit is gradually lost in muscle during denervation. Lastly, the effect of long duration stimulation pulses, that are required to activate denervated muscle, on nerve is examined. We show that these long pulses can activate nerves up to three times when the three field transition within the biphasic pulses are separated by more than (i.e., when the phase width is above) the refractory period of that nerve. This observation challenges state-of-the-art computational models of extracellular nerve stimulation that do not seem to predict such multiple activations. Further, an undesired up to threefold co-activation of innervated structures nearby the denervated stimulation target warrants further research to study whether these co-activations can be lessened with alternative stimulation waveforms such as ramped sawtooth pulses

Collective analog bioelectronic computation

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2009.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from student submitted PDF version of thesis.Includes bibliographical references (p. 677-710).In this thesis, I present two examples of fast-and-highly-parallel analog computation inspired by architectures in biology. The first example, an RF cochlea, maps the partial differential equations that describe fluid-membrane-hair-cell wave propagation in the biological cochlea to an equivalent inductor-capacitor-transistor integrated circuit. It allows ultra-broadband spectrum analysis of RF signals to be performed in a rapid low-power fashion, thus enabling applications for universal or software radio. The second example exploits detailed similarities between the equations that describe chemical-reaction dynamics and the equations that describe subthreshold current flow in transistors to create fast-and-highly-parallel integrated-circuit models of protein-protein and gene-protein networks inside a cell. Due to a natural mapping between the Poisson statistics of molecular flows in a chemical reaction and Poisson statistics of electronic current flow in a transistor, stochastic effects are automatically incorporated into the circuit architecture, allowing highly computationally intensive stochastic simulations of large-scale biochemical reaction networks to be performed rapidly. I show that the exponentially tapered transmission-line architecture of the mammalian cochlea performs constant-fractional-bandwidth spectrum analysis with O(N) expenditure of both analysis time and hardware, where N is the number of analyzed frequency bins. This is the best known performance of any spectrum-analysis architecture, including the constant-resolution Fast Fourier Transform (FFT), which scales as O(N logN), or a constant-fractional-bandwidth filterbank, which scales as O (N2).(cont.) The RF cochlea uses this bio-inspired architecture to perform real-time, on-chip spectrum analysis at radio frequencies. I demonstrate two cochlea chips, implemented in standard 0.13m CMOS technology, that decompose the RF spectrum from 600MHz to 8GHz into 50 log-spaced channels, consume < 300mW of power, and possess 70dB of dynamic range. The real-time spectrum analysis capabilities of my chips make them uniquely suitable for ultra-broadband universal or software radio receivers of the future. I show that the protein-protein and gene-protein chips that I have built are particularly suitable for simulation, parameter discovery and sensitivity analysis of interaction networks in cell biology, such as signaling, metabolic, and gene regulation pathways. Importantly, the chips carry out massively parallel computations, resulting in simulation times that are independent of model complexity, i.e., O(1). They also automatically model stochastic effects, which are of importance in many biological systems, but are numerically stiff and simulate slowly on digital computers. Currently, non-fundamental data-acquisition limitations show that my proof-of-concept chips simulate small-scale biochemical reaction networks at least 100 times faster than modern desktop machines. It should be possible to get 103 to 106 simulation speedups of genome-scale and organ-scale intracellular and extracellular biochemical reaction networks with improved versions of my chips. Such chips could be important both as analysis tools in systems biology and design tools in synthetic biology.by Soumyajit Mandal.Ph.D