A battery-free multichannel digital neural/EMG telemetry system for flying insects

Tracking technologies: advances driving new insights into monarch migration

Understanding the rules of how monarch butterflies complete their annual North American migration will be clarified by studying them within a movement ecology framework. Insect movement ecology is growing at a rapid pace due to the development of novel monitoring systems that allow ever-smaller animals to be tracked at higher spatiotemporal resolution for longer periods of time. New innovations in tracking hardware and associated software, including miniaturization, energy autonomy, data management, and wireless communication, are reducing the size and increasing the capability of next-generation tracking technologies, bringing the goal of tracking monarchs over their entire migration closer within reach. These tools are beginning to be leveraged to provide insight into different aspects of monarch biology and ecology, and to contribute to a growing capacity to understand insect movement ecology more broadly and its impact on human life.

Behavioral algorithms and neural mechanisms underlying odor-modulated locomotion in insects

Odors released from mates and resources such as a host and food are often the first sensory signals that an animal can detect. Changes in locomotion in response to odors are an important mechanism by which animals access resources important to their survival. Odor-modulated changes in locomotion in insects constitute a whole suite of flexible behaviors that allow insects to close in on these resources from long distances and perform local searches to locate and subsequently assess them. Here, we review changes in odor-mediated locomotion across many insect species. We emphasize that changes in locomotion induced by odors are diverse. In particular, the olfactory stimulus is sporadic at long distances and becomes more continuous at short distances. This distance-dependent change in temporal profile produces a corresponding change in an insect's locomotory strategy. We also discuss the neural circuits underlying odor modulation of locomotion.

Evolution of Biotelemetry in Medical Devices: From Radio Pills to mm-Scale Implants

The advent of semiconductor technology in the mid-20th century created unprecedented opportunities to develop a new generation of small-scale wireless medical sensing devices that can support remote monitoring of patients' vital signs. The first radio pills were developed as early as the 1950's using only a few transistors. These swallowable capsules could sense and wirelessly transmit vital parameters from inside the human body. Since then we have witnessed the rapid progress of medical devices driven by the evolution of semiconductor technology, from single-transistor oscillators to complex mixed-signal multi-channel and multi-modal systems. This paper retraces the evolution of biotelemetry devices from their very early inception to the smart miniaturized systems of modern days, focusing on semiconductor-enabled sensing methods and circuits developed over the last six decades. The paper also includes the author's perspective on current and future trends in the development of CMOS-based biotelemeters, focusing on concepts of implant modularity, miniaturization and hybrid energy harvesting solutions.

Recent advances in recording and modulation technologies for next-generation neural interfaces

Along with the advancement in neural engineering techniques, unprecedented progress in the development of neural interfaces has been made over the past few decades. However, despite these achievements, there is still room for further improvements especially toward the possibility of monitoring and modulating neural activities with high resolution and specificity in our daily lives. In an effort of taking a step toward the next-generation neural interfaces, we want to highlight the recent progress in neural technologies. We will cover a wide scope of such developments ranging from novel platforms for highly specific recording and modulation to system integration for practical applications of novel interfaces.

Recent approaches to study the neural bases of complex insect behavior

Recent advances in biocompatible materials, miniaturized instrumentation, advanced computational algorithms, and genetic tools have enabled the development of novel methods and approaches to quantify the behavior of individuals or groups of animals. In conjunction with technologies that allow simultaneous monitoring of neural responses, quantitative studies of complex behaviors can reveal tighter links between the external sensory cues in the vicinity of the organism and neural responses they elicit, and how internal neural representations finally get mapped onto the behavior generated. In this review, we examine a few approaches that are beginning to be widely exploited for understanding neural-behavioral response transformations.

Epileptic Seizure Detection on an Ultra-Low-Power Embedded RISC-V Processor Using a Convolutional Neural Network

The treatment of refractory epilepsy via closed-loop implantable devices that act on seizures either by drug release or electrostimulation is a highly attractive option. For such implantable medical devices, efficient and low energy consumption, small size, and efficient processing architectures are essential. To meet these requirements, epileptic seizure detection by analysis and classification of brain signals with a convolutional neural network (CNN) is an attractive approach. This work presents a CNN for epileptic seizure detection capable of running on an ultra-low-power microprocessor. The CNN is implemented and optimized in MATLAB. In addition, the CNN is also implemented on a GAP8 microprocessor with RISC-V architecture. The training, optimization, and evaluation of the proposed CNN are based on the CHB-MIT dataset. The CNN reaches a median sensitivity of 90% and a very high specificity over 99% corresponding to a median false positive rate of 6.8 s per hour. After implementation of the CNN on the microcontroller, a sensitivity of 85% is reached. The classification of 1 s of EEG data takes t=35 ms and consumes an average power of P≈140 μW. The proposed detector outperforms related approaches in terms of power consumption by a factor of 6. The universal applicability of the proposed CNN based detector is verified with recording of epileptic rats. This results enable the design of future medical devices for epilepsy treatment.

Wireless and battery-free platforms for collection of biosignals

Recent progress in biosensors have quantitively expanded current capabilities in exploratory research tools, diagnostics and therapeutics. This rapid pace in sensor development has been accentuated by vast improvements in data analysis methods in the form of machine learning and artificial intelligence that, together, promise fantastic opportunities in chronic sensing of biosignals to enable preventative screening, automated diagnosis, and tools for personalized treatment strategies. At the same time, the importance of widely accessible personal monitoring has become evident by recent events such as the COVID-19 pandemic. Progress in fully integrated and chronic sensing solutions is therefore increasingly important. Chronic operation, however, is not truly possible with tethered approaches or bulky, battery-powered systems that require frequent user interaction. A solution for this integration challenge is offered by wireless and battery-free platforms that enable continuous collection of biosignals. This review summarizes current approaches to realize such device architectures and discusses their building blocks. Specifically, power supplies, wireless communication methods and compatible sensing modalities in the context of most prevalent implementations in target organ systems. Additionally, we highlight examples of current embodiments that quantitively expand sensing capabilities because of their use of wireless and battery-free architectures.

Enhancing insect flight research with a lab-on-cables

A cable-driven robot that tracks flying insects at close range offers a useful method to study insects in free flight.

Potential application of Aloe Vera-derived plant-based cell in powering wireless device for remote sensor activation

It is well proven that electrical energy can be harvested from the living plants which can be used as a potential renewable energy source for powering wireless devices in remote areas where replacing or recharging the battery is a difficult task. Therefore, harvesting electrical energy from living plants in remote areas such as in farms or forest areas can be an ideal source of energy as these areas are rich with living plants. The present paper proposes a design of a power management circuit that can harness, store and manage the electrical energy which is harvested from the leaves of Aloe Barbadensis Miller (Aloe Vera) plants to trigger a transmitter load to power a remote sensor. The power management circuit consists of two sections namely; an energy storage system that acts as an energy storage reservoir to store the energy harvested from the plants as well as a voltage regulation system which is used to boost and manage the energy in accordance to a load operation. The experimental results show that the electrical energy harvested from the Aloe Vera under a specific setup condition can produce an output of 3.49 V and 1.1 mA. The harvested energy is being channeled to the power management circuit which can boost the voltage to 10.9 V under no load condition. The harvested energy from the plants boosted by the power management circuit can turn ON the transmitter automatically to activate a temperature and humidity sensor to measure the environmental stimuli periodically with a ton of 1.22 seconds and toff of 0.46 seconds. This proves that this new source of energy combined with a power management circuit can be employed for powering the wireless sensor network for application in the Internet of Things (IoT).

A 25 Mbps, 12.4 pJ/b DQPSK Backscatter Data Uplink for the NeuroDisc Brain-Computer Interface

Wireless brain-computer interfaces (BCIs) are used to study neural activity in freely moving non-human primates (NHPs). However, the high energy consumption of conventional active radios is proving to be an obstacle as research drives for wireless BCIs that can provide continuous high-rate data uplinks for longer durations (i.e. multiple days). We present a differential quadrature phase shift keying (DQPSK) backscatter uplink for the NeuroDisc BCI as an alternative to active radios. The uplink achieves a 25 Mbps throughput while operating in the 915 MHz industrial, scientific, and medical (ISM) band. The DQPSK backscatter modulator was measured to have an error-vector magnitude (EVM) of 9.7% and a measured power consumption of 309  μW during continuous, full-rate transmissions, yielding an analog communication efficiency of 12.4 pJ/bit. The NeuroDisc is capable of recording 16 channels of neural data with 16-bit resolution at up to 20 kSps per channel with a measured input-referred noise of 2.35  μV. In previous work, we demonstrated the DQPSK backscatter uplink, but bandwidth constraints in the signal chain limited the uplink rate to 6.25 Mbps and the neural sampling rate to 5 kSps. This work provides new innovations to increase the bandwidth of the system, including an ultra-high frequency (UHF) antenna design with a -10 dB return loss bandwidth of 12.5 MHz and a full-duplex receiver with an average self-jammer cancellation of 89 dB. We present end-to-end characterization of the NeuroDisc and validate the backscatter uplink using pre-recorded neural data as well as in vivo recordings from a pigtail macaque.

An Embedded, Eight Channel, Noise Canceling, Wireless, Wearable sEMG Data Acquisition System With Adaptive Muscle Contraction Detection

Wearable technology has gained increasing popularity in the applications of healthcare, sports science, and biomedical engineering in recent years. Because of its convenient nature, the wearable technology is particularly useful in the acquisition of the physiological signals. Specifically, the (surface electromyography) sEMG systems, which measure the muscle activation potentials, greatly benefit from this technology in both clinical and industrial applications. However, the current wearable sEMG systems have several drawbacks including inefficient noise cancellation, insufficient measurement quality, and difficult integration to customized applications. Additionally, none of these sEMG data acquisition systems can detect sEMG signals (i.e., contractions), which provides a valuable environment for further studies such as human machine interaction, gesture recognition, and fatigue tracking. To this end, we introduce an embedded, eight channel, noise canceling, wireless, wearable sEMG data acquisition system with adaptive muscle contraction detection. Our design consists of two stages, which are the sEMG sensors and the multichannel data acquisition unit. For the first stage, we propose a low cost, dry, and active sEMG sensor that captures the muscle activation potentials, a data acquisition unit that evaluates these captured multichannel sEMG signals and transmits them to a user interface. In the data acquisition unit, the sEMG signals are processed through embedded, adaptive methods in order to reject the power line noise and detect the muscle contractions. Through extensive experiments, we demonstrate that our sEMG sensor outperforms a widely used commercially available product and our data acquisition system achieves 4.583 dB SNR gain with accuracy in the detection of the contractions.

Combinatorial Codes and Labeled Lines: How Insects Use Olfactory Cues to Find and Judge Food, Mates, and Oviposition Sites in Complex Environments

Insects, including those which provide vital ecosystems services as well as those which are devastating pests or disease vectors, locate their resources mainly based on olfaction. Understanding insect olfaction not only from a neurobiological but also from an ecological perspective is therefore crucial to balance insect control and conservation. However, among all sensory stimuli olfaction is particularly hard to grasp. Our chemical environment is made up of thousands of different compounds, which might again be detected by our nose in multiple ways. Due to this complexity, researchers have only recently begun to explore the chemosensory ecology of model organisms such as Drosophila, linking the tools of chemical ecology to those of neurogenetics. This cross-disciplinary approach has enabled several studies that range from single odors and their ecological relevance, via olfactory receptor genes and neuronal processing, up to the insects' behavior. We learned that the insect olfactory system employs strategies of combinatorial coding to process general odors as well as labeled lines for specific compounds that call for an immediate response. These studies opened new doors to the olfactory world in which insects feed, oviposit, and mate.

Wireless electrophysiology of the brain of freely swimming goldfish

BACKGROUND

Fish are a diverse group of vertebrates with very different brain structures. The study of the neurobiology of fish can thus lead to many important insights on information processing in the brain in a variety of environments.

NEW METHOD

We developed a novel wireless technique to record extracellular neural signal activity in freely behaving fish. The system is based on a data logger and enables continues recording of up to 2.5h.

RESULTS

For proof of concept we recorded from the optic tectum of goldfish. We found correlations between the activity of the optic tectum and the light intensity in the room, as expected.

COMPARISON WITH EXISTING METHODS

Due to the technical difficulties involved in making electrophysiological recordings of behaving aquatic animals, there is no method for recording electrical neural activity from the brain of freely swimming fish.

CONCLUSIONS

This powerful tool should facilitate studies of information processing in behaving fish and other behaving aquatic animals.

Motor control: how dragonflies catch their prey

Detailed measurements of head and body motion have revealed previously unknown complexity in the predatory behavior of dragonflies. The new evidence suggests that the brains of these agile predators compute internal models of their own actions and those of their prey.

Studying small brains to understand the building blocks of cognition

Cognition encompasses a range of higher-order mental processes, such as attention, working memory, and model-based decision-making. These processes are thought to involve the dynamic interaction of multiple central brain regions. A mechanistic understanding of such computations requires not only monitoring and manipulating specific neural populations during behavior, but also knowing the connectivity of the underlying circuitry. These goals are experimentally challenging in mammals, but are feasible in numerically simpler insect brains. In Drosophila melanogaster in particular, genetic tools enable precisely targeted physiology and optogenetics in actively behaving animals. In this article we discuss how these advantages are increasingly being leveraged to study abstract neural representations and sensorimotor computations that may be relevant for cognition in both insects and mammals.

Implantable neurotechnologies: a review of integrated circuit neural amplifiers

Neural signal recording is critical in modern day neuroscience research and emerging neural prosthesis programs. Neural recording requires the use of precise, low-noise amplifier systems to acquire and condition the weak neural signals that are transduced through electrode interfaces. Neural amplifiers and amplifier-based systems are available commercially or can be designed in-house and fabricated using integrated circuit (IC) technologies, resulting in very large-scale integration or application-specific integrated circuit solutions. IC-based neural amplifiers are now used to acquire untethered/portable neural recordings, as they meet the requirements of a miniaturized form factor, light weight and low power consumption. Furthermore, such miniaturized and low-power IC neural amplifiers are now being used in emerging implantable neural prosthesis technologies. This review focuses on neural amplifier-based devices and is presented in two interrelated parts. First, neural signal recording is reviewed, and practical challenges are highlighted. Current amplifier designs with increased functionality and performance and without penalties in chip size and power are featured. Second, applications of IC-based neural amplifiers in basic science experiments (e.g., cortical studies using animal models), neural prostheses (e.g., brain/nerve machine interfaces) and treatment of neuronal diseases (e.g., DBS for treatment of epilepsy) are highlighted. The review concludes with future outlooks of this technology and important challenges with regard to neural signal amplification.

How animals glide: from trajectory to morphology

Animals that glide produce aerodynamic forces that enable transit through the air in both arboreal and aquatic environments. The relative ease of gliding compared with flapping flight has led to a large diversity of taxa that have evolved some degree of flight capability. Glide paths are curved, reflecting the changing forces on the animal as it progresses through its aerial trajectory. These changing forces can be under control of the glider, which uses specific aspects of anatomy to modulate lift, drag, and rotational moments on the body. However, gliders share no single anatomical or behavioral feature, and some species are unspecialized for gliding, producing aerodynamic forces using posture and orientation alone. Animals use gliding in a broad range of ecological roles, suggesting that multiple performance metrics are relevant for consideration, but we are only beginning to understand how gliders produce and control their flight from takeoff to landing. In this review, we focus on the physical aspects of how glide trajectories are produced, and additionally discuss the range of morphologies and postures that are used to control aerial movements across the broad diversity of animal gliders.

High order neural correlates of social behavior in the honeybee brain

BACKGROUND

Honeybees are well established models of neural correlates of sensory function, learning and memory formation. Here we report a novel approach allowing to record high-order mushroom body-extrinsic interneurons in the brain of worker bees within a functional colony. New method The use of two 100 cm long twisted copper electrodes allowed recording of up to four units of mushroom body-extrinsic neurons simultaneously for up to 24h in animals moving freely between members of the colony. Every worker, including the recorded bee, hatched in the experimental environment. The group consisted of 200 animals in average.

RESULTS

Animals explored different regions of the comb and interacted with other colony members. The activities of the units were not selective for locations on the comb, body directions with respect to gravity and olfactory signals on the comb, or different social interactions. However, combinations of these parameters defined neural activity in a unit-specific way. In addition, units recorded from the same animal co-varied according to unknown factors. Comparison with existing method(s): All electrophysiological studies with honey bees were performed so far on constrained animals outside their natural behavioral contexts. Yet no neuronal correlates were measured in a social context. Free mobility of recoded insects over a range of a quarter square meter allows addressing questions concerning neural correlates of social communication, planning of tasks within the colony and attention-like processes.

CONCLUSIONS

The method makes it possible to study neural correlates of social behavior in a near-natural setting within the honeybee colony.

A wireless neural recording system with a precision motorized microdrive for freely behaving animals

The brain is composed of many different types of neurons. Therefore, analysis of brain activity with single-cell resolution could provide fundamental insights into brain mechanisms. However, the electrical signal of an individual neuron is very small, and precise isolation of single neuronal activity from moving subjects is still challenging. To measure single-unit signals in actively behaving states, establishment of technologies that enable fine control of electrode positioning and strict spike sorting is essential. To further apply such a single-cell recording approach to small brain areas in naturally behaving animals in large spaces or during social interaction, we developed a compact wireless recording system with a motorized microdrive. Wireless control of electrode placement facilitates the exploration of single neuronal activity without affecting animal behaviors. Because the system is equipped with a newly developed data-encoding program, the recorded data are readily compressed almost to theoretical limits and securely transmitted to a host computer. Brain activity can thereby be stably monitored in real time and further analyzed using online or offline spike sorting. Our wireless recording approach using a precision motorized microdrive will become a powerful tool for studying brain mechanisms underlying natural or social behaviors.

Internal models direct dragonfly interception steering

Sensorimotor control in vertebrates relies on internal models. When extending an arm to reach for an object, the brain uses predictive models of both limb dynamics and target properties. Whether invertebrates use such models remains unclear. Here we examine to what extent prey interception by dragonflies (Plathemis lydia), a behaviour analogous to targeted reaching, requires internal models. By simultaneously tracking the position and orientation of a dragonfly's head and body during flight, we provide evidence that interception steering is driven by forward and inverse models of dragonfly body dynamics and by models of prey motion. Predictive rotations of the dragonfly's head continuously track the prey's angular position. The head-body angles established by prey tracking appear to guide systematic rotations of the dragonfly's body to align it with the prey's flight path. Model-driven control thus underlies the bulk of interception steering manoeuvres, while vision is used for reactions to unexpected prey movements. These findings illuminate the computational sophistication with which insects construct behaviour.

A wireless power transmission system for implantable devices in freely moving rodents

Reliable wireless power delivery for implantable devices in animals is highly desired for safe and effective experimental use. Batteries require frequent replacement; wired connections are inconvenient and unsafe, and short-distance inductive coupling requires the attachment of an exterior transmitter to the animal's body. In this article, we propose a solution by which animals with implantable devices can move freely without attachments. Power is transmitted using coils attached to the animal's cage and is received by a receiver coil implanted in the animal. For a three-dimensionally uniform delivery of power, we designed a columnar dual-transmitter coil configuration. A resonator-based inductive link was adopted for efficient long-range power delivery, and we used a novel biocompatible liquid crystal polymer substrate as the implantable receiver device. Using this wireless power delivery system, we obtain an average power transfer efficiency of 15.2% (minimum efficiency of 10% and a standard deviation of 2.6) within a cage of 15×20×15 cm3.

Feedback control as a framework for understanding tradeoffs in biology

Control theory arose from a need to control synthetic systems. From regulating steam engines to tuning radios to devices capable of autonomous movement, it provided a formal mathematical basis for understanding the role of feedback in the stability (or change) of dynamical systems. It provides a framework for understanding any system with regulation via feedback, including biological ones such as regulatory gene networks, cellular metabolic systems, sensorimotor dynamics of moving animals, and even ecological or evolutionary dynamics of organisms and populations. Here, we focus on four case studies of the sensorimotor dynamics of animals, each of which involves the application of principles from control theory to probe stability and feedback in an organism's response to perturbations. We use examples from aquatic (two behaviors performed by electric fish), terrestrial (following of walls by cockroaches), and aerial environments (flight control by moths) to highlight how one can use control theory to understand the way feedback mechanisms interact with the physical dynamics of animals to determine their stability and response to sensory inputs and perturbations. Each case study is cast as a control problem with sensory input, neural processing, and motor dynamics, the output of which feeds back to the sensory inputs. Collectively, the interaction of these systems in a closed loop determines the behavior of the entire system.

Soft microfluidic assemblies of sensors, circuits, and radios for the skin

When mounted on the skin, modern sensors, circuits, radios, and power supply systems have the potential to provide clinical-quality health monitoring capabilities for continuous use, beyond the confines of traditional hospital or laboratory facilities. The most well-developed component technologies are, however, broadly available only in hard, planar formats. As a result, existing options in system design are unable to effectively accommodate integration with the soft, textured, curvilinear, and time-dynamic surfaces of the skin. Here, we describe experimental and theoretical approaches for using ideas in soft microfluidics, structured adhesive surfaces, and controlled mechanical buckling to achieve ultralow modulus, highly stretchable systems that incorporate assemblies of high-modulus, rigid, state-of-the-art functional elements. The outcome is a thin, conformable device technology that can softly laminate onto the surface of the skin to enable advanced, multifunctional operation for physiological monitoring in a wireless mode.

Design and implementation of a wireless in-ovo EEG/EMG recorder

The developmental origins of sleep and brain activity rhythms in higher vertebrate animals (birds and mammals) are currently unknown. In order to create an experimental system in which these could be better elucidated, we designed, built and tested a system for recording EEG and EMG signals in-ovo from chicken embryos incubated for 16-21 days. This system can remain attached to the individual subject through the process of hatching and continue to be worn post-natally. Electrode wires surgically implanted on the head of the embryo are connected to a battery-operated ultraportable transmitter which can either be attached to the eggshell or worn on the back. The transmitter processes up to 6 channels of data with a maximum sampling frequency of 500 Hz and a resolution of 12 bits. The radio link uses a carrier frequency of 4 MHz, and has a maximum transfer rate of 500 kbit/s; receiving antennas compatible with both in-egg recordings and post-natal recordings from freely-moving birds were produced. A receiver connected with one USB port of a PC transmits the data for digital storage. This system is based on discrete, off-the-shelf components, can provide a few days of continuous operation with a single lithium coin battery, and has a noise floor level of 0.35 μV. The transmitter dimensions are 16 × 13 × 1.5 mm and the weight without the battery is 0.7 g. The microprocessor allows flexible operation modes not usually made available in other small multichannel acquisition systems implemented by means of ad hoc mixed signal chips.

EnerCage: a smart experimental arena with scalable architecture for behavioral experiments

Wireless power, when coupled with miniaturized implantable electronics, has the potential to provide a solution to several challenges facing neuroscientists during basic and preclinical studies with freely behaving animals. The EnerCage system is one such solution as it allows for uninterrupted electrophysiology experiments over extended periods of time and vast experimental arenas, while eliminating the need for bulky battery payloads or tethering. It has a scalable array of overlapping planar spiral coils (PSCs) and three-axis magnetic sensors for focused wireless power transmission to devices on freely moving subjects. In this paper, we present the first fully functional EnerCage system, in which the number of PSC drivers and magnetic sensors was reduced to one-third of the number used in our previous design via multicoil coupling. The power transfer efficiency (PTE) has been improved to 5.6% at a 120 mm coupling distance and a 48.5 mm lateral misalignment (worst case) between the transmitter (Tx) array and receiver (Rx) coils. The new EnerCage system is equipped with an Ethernet backbone, further supporting its modular/scalable architecture, which, in turn, allows experimental arenas with arbitrary shapes and dimensions. A set of experiments on a freely behaving rat were conducted by continuously delivering 20 mW to the electronics in the animal headstage for more than one hour in a powered 3538 cm(2) experimental area.

A wireless and batteryless microsystem with implantable grid electrode/3-dimensional probe array for ECoG and extracellular neural recording in rats

This paper presents the design and implementation of an integrated wireless microsystem platform that provides the possibility to support versatile implantable neural sensing devices in free laboratory rats. Inductive coupled coils with low dropout regulator design allows true long-term recording without limitation of battery capacity. A 16-channel analog front end chip located on the headstage is designed for high channel account neural signal conditioning with low current consumption and noise. Two types of implantable electrodes including grid electrode and 3D probe array are also presented for brain surface recording and 3D biopotential acquisition in the implanted target volume of tissue. The overall system consumes less than 20 mA with small form factor, 3.9 × 3.9 cm2 mainboard and 1.8 × 3.4 cm2 headstage, is packaged into a backpack for rats. Practical in vivo recordings including auditory response, brain resection tissue and PZT-induced seizures recording demonstrate the correct function of the proposed microsystem. Presented achievements addressed the aforementioned properties by combining MEMS neural sensors, low-power circuit designs and commercial chips into system-level integration.