A microelectromechanical system artificial basilar membrane based on a piezoelectric cantilever array and its characterization using an animal model

Biomimetic Wearable Sensors: Emerging Combination of Intelligence and Electronics

Owing to the advancement of interdisciplinary concepts, for example, wearable electronics, bioelectronics, and intelligent sensing, during the microelectronics industrial revolution, nowadays, extensively mature wearable sensing devices have become new favorites in the noninvasive human healthcare industry. The combination of wearable sensing devices with bionics is driving frontier developments in various fields, such as personalized medical monitoring and flexible electronics, due to the superior biocompatibilities and diverse sensing mechanisms. It is noticed that the integration of desired functions into wearable device materials can be realized by grafting biomimetic intelligence. Therefore, herein, the mechanism by which biomimetic materials satisfy and further enhance system functionality is reviewed. Next, wearable artificial sensory systems that integrate biomimetic sensing into portable sensing devices are introduced, which have received significant attention from the industry owing to their novel sensing approaches and portabilities. To address the limitations encountered by important signal and data units in biomimetic wearable sensing systems, two paths forward are identified and current challenges and opportunities are presented in this field. In summary, this review provides a further comprehensive understanding of the development of biomimetic wearable sensing devices from both breadth and depth perspectives, offering valuable guidance for future research and application expansion of these devices.

Current status and future application of electrically controlled micro/nanorobots in biomedicine

Using micro/nanorobots (MNRs) for targeted therapy within the human body is an emerging research direction in biomedical science. These nanoscale to microscale miniature robots possess specificity and precision that are lacking in most traditional treatment modalities. Currently, research on electrically controlled micro/nanorobots is still in its early stages, with researchers primarily focusing on the fabrication and manipulation of these robots to meet complex clinical demands. This review aims to compare the fabrication, powering, and locomotion of various electrically controlled micro/nanorobots, and explore their advantages, disadvantages, and potential applications.

Directional Resonant MEMS Acoustic Sensor and Associated Acoustic Vector Sensor

This paper reports on the design, modeling, analysis, and evaluation of a micro-electromechanical systems acoustic sensor and the novel design of an acoustic vector sensor array (AVS) which utilized this acoustic sensor. This research builds upon previous work conducted to develop a small, lightweight, portable system for the detection and location of quiet or distant acoustic sources of interest. This study also reports on the underwater operation of this sensor and AVS. Studies were conducted in the lab and in the field utilizing multiple acoustic sources (e.g., generated tones, gun shots, drones). The sensor operates at resonance, providing for high acoustic sensitivity and a high signal-to-noise ratio (SNR). The sensor demonstrated a maximum SNR of 88 dB with an associated sensitivity of -84.6 dB re 1 V/μPa (59 V/Pa). The sensor design can be adjusted to set a specified resonant frequency to align with a known acoustic signature of interest. The AVS demonstrated an unambiguous, 360-degree, in-plane, azimuthal coverage and was able to provide an acoustic direction of arrival to an average error of within 3.5° during field experiments. The results of this research demonstrate the potential usefulness of this sensor and AVS design for specific applications.

Review of the applications of principles of insect hearing to microscale acoustic engineering challenges

When looking for novel, simple, and energy-efficient solutions to engineering problems, nature has proved to be an incredibly valuable source of inspiration. The development of acoustic sensors has been a prolific field for bioinspired solutions. With a diverse array of evolutionary approaches to the problem of hearing at small scales (some widely different to the traditional concept of 'ear'), insects in particular have served as a starting point for several designs. From locusts to moths, through crickets and mosquitoes among many others, the mechanisms found in nature to deal with small-scale acoustic detection and the engineering solutions they have inspired are reviewed. The present article is comprised of three main sections corresponding to the principal problems faced by insects, namely frequency discrimination, which is addressed by tonotopy, whether performed by a specific organ or directly on the tympana; directionality, with solutions including diverse adaptations to tympanal structure; and detection of weak signals, through what is known as active hearing. The three aforementioned problems concern tiny animals as much as human-manufactured microphones and have therefore been widely investigated. Even though bioinspired systems may not always provide perfect performance, they are sure to give us solutions with clever use of resources and minimal post-processing, being serious contenders for the best alternative depending on the requisites of the problem.

Emerging Trends in Soft Electronics: Integrating Machine Intelligence with Soft Acoustic/Vibration Sensors

In the last decade, soft acoustic/vibration sensors have gained tremendous research interest due to their unique ability to detect broadband acoustic/vibration stimuli, potentializing futuristic applications including voice biometrics, voice-controlled human-machine-interfaces, electronic skin, and skin-mountable healthcare devices. Importantly, to benefit most from these sensors, it is inevitable to use machine learning (ML) to process their output signals; with ML, a more accurate and efficient interpretation of original data is possible. This paper is dedicated to offering an overview of recent advances empowering the development of soft acoustic/vibration sensors and their signal processing using ML. First, the key performance parameters of the sensors are discussed. Second, popular transduction mechanisms for the sensors are addressed, followed by an in-depth overview of each type, covering materials used, structural designs, and sensing performances. Third, potential applications of the sensors are elaborated and fourth, a thorough discussion on ML is conducted, exploring different types of ML, specific ML algorithms suitable for processing acoustic/vibration signals, and current trends in ML-assisted applications. Finally, the challenges and potential opportunities in soft acoustic/vibration sensor and ML research are revealed to offer new insights into future prospects in these fields.

Models of Cochlea Used in Cochlear Implant Research: A Review

As the first clinically translated machine-neural interface, cochlear implants (CI) have demonstrated much success in providing hearing to those with severe to profound hearing loss. Despite their clinical effectiveness, key drawbacks such as hearing damage, partly from insertion forces that arise during implantation, and current spread, which limits focussing ability, prevent wider CI eligibility. In this review, we provide an overview of the anatomical and physical properties of the cochlea as a resource to aid the development of accurate models to improve future CI treatments. We highlight the advancements in the development of various physical, animal, tissue engineering, and computational models of the cochlea and the need for such models, challenges in their use, and a perspective on their future directions.

MEMS piezoelectric resonant microphone array for lung sound classification

This paper reports a highly sensitive piezoelectric microelectromechanical systems (MEMS) resonant microphone array (RMA) for detection and classification of wheezing in lung sounds. The RMA is composed of eight width-stepped cantilever resonant microphones with Mel-distributed resonance frequencies from 230 to 630 Hz, the main frequency range of wheezing. At the resonance frequencies, the unamplified sensitivities of the microphones in the RMA are between 86 and 265 mV Pa-1, while the signal-to-noise ratios (SNRs) for 1 Pa sound pressure are between 86.6 and 98.0 dBA. Over 200-650 Hz, the unamplified sensitivities are between 35 and 265 mV Pa-1, while the SNRs are between 79 and 98 dBA. Wheezing feature in lung sounds recorded by the RMA is more distinguishable than that recorded by a reference microphone with traditional flat sensitivity, and thus, the automatic classification accuracy of wheezing is higher with the lung sounds recorded by the RMA than with those by the reference microphone, when tested with deep learning algorithms on computer or with simple machine learning algorithms on low-power wireless chip set for wearable applications.

A bioinspired configurable cochlea based on memristors

Cochleas are the basis for biology to process and recognize speech information, emulating which with electronic devices helps us construct high-efficient intelligent voice systems. Memristor provides novel physics for performing neuromorphic engineering beyond complementary metal-oxide-semiconductor technology. This work presents an artificial cochlea based on the shallen-key filter model configured with memristors, in which one filter emulates one channel. We first fabricate a memristor with the TiN/HfOx/TaOx/TiN structure to implement such a cochlea and demonstrate the non-volatile multilevel states through electrical operations. Then, we build the shallen-key filter circuit and experimentally demonstrate the frequency-selection function of cochlea’s five channels, whose central frequency is determined by the memristor’s resistance. To further demonstrate the feasibility of the cochlea for system applications, we use it to extract the speech signal features and then combine it with a convolutional neural network to recognize the Free Spoken Digit Dataset. The recognition accuracy reaches 92% with 64 channels, compatible with the traditional 64 Fourier transform transformation points of mel-frequency cepstral coefficients method with 95% recognition accuracy. This work provides a novel strategy for building cochleas, which has a great potential to conduct configurable, high-parallel, and high-efficient auditory systems for neuromorphic robots.

Oscillation Characteristics of an Artificial Cochlear Sensory Epithelium Optimized for a Micrometer-Scale Curved Structure

Based on the modern microelectromechanical systems technology, we present a revolutionary miniaturized artificial cochlear sensory epithelium for future implantation tests on guinea pigs. The device was curved to fit the spiral structure of the cochlea and miniaturized to a maximum dimension of <1 mm to be implanted in the cochlea. First, the effect of the curved configuration on the oscillation characteristics of a trapezoidal membrane was evaluated using the relatively larger devices, which had a trapezoidal and a comparable curved shape designed for high-precision in vitro measurements. Both experimental and numerical analyses were used to determine the resonance frequencies and positions, and multiple oscillation modes were clearly observed. Because the maximum oscillation amplitude positions, i.e., the resonance positions, differed depending on the resonance frequencies in both trapezoidal and curved membrane devices, the sound frequency was determined based on the resonance position, thus reproducing the frequency selectivity of the basilar membrane in the organ of Corti. Furthermore, the resonance frequencies and positions of these two devices with different configurations were determined to be quantitatively consistent and similar in terms of mechanical dynamics. This result shows that despite a curved angle of 50−60°, the effect of the curved shape on oscillation characteristics was negligible. Second, the nanometer-scale oscillation of the miniaturized device was successfully measured, and the local resonance frequency in air was varied from 157 to 277 kHz using an experimental system that could measure the amplitude distribution in a two-dimensional (2D) plane with a high accuracy and reproducibility at a high speed. The miniaturized device developed in this study was shown to have frequency selectivity, and when the device was implanted in the cochlea, it was expected to discriminate frequencies in the same manner as the basilar membrane in the biological system. This study established methods for fabricating and evaluating the miniaturized device, and the proposed miniaturized device in a curved shape demonstrated the feasibility of next-generation cochlear implants.

A High-Fidelity Skin-Attachable Acoustic Sensor for Realizing Auditory Electronic Skin

Wearable auditory sensors are critical in user-friendly sound-recognition systems for smart human-machine interaction and the Internet of Things. However, previously reported wearable sensors have limited sound-sensing quality as a consequence of a poor frequency response and a narrow acoustic-pressure range. Here, a skin-attachable acoustic sensor is presented that has higher sensing accuracy in wider auditory field than human ears, with flat frequency response (15-10 000 Hz) and a good range of linearity (29-134 dB_SPL ) as well as high conformality to flexible surfaces and human skin. This high sound-sensing quality is achieved by exploiting the low residual stress and high processability of polymer materials in a diaphragm structure designed using acousto-mechano-electric modeling. Thus, this acoustic sensor shows high acoustic fidelity by sensing human-audible sounds, even loud sounds and low-frequency sounds that human ears cannot detect without distorting them. The polymer-based ultrasmall (<9 mm² ) and thin sensor maintains sound-detection quality on flexible substrates and in a wide temperature range (25 to 90 °C). The acoustic sensor shows a significant potential of auditory electronic skin, by recognizing voice successfully when the sensor attached on human skin is connected to a commercial mobile device running the latest artificial intelligence assistant.

Piezoelectric nanogenerators for personalized healthcare

The development of flexible piezoelectric nanogenerators has experienced rapid progress in the past decade and is serving as the technological foundation of future state-of-the-art personalized healthcare. Due to their highly efficient mechanical-to-electrical energy conversion, easy implementation, and self-powering nature, these devices permit a plethora of innovative healthcare applications in the space of active sensing, electrical stimulation therapy, as well as passive human biomechanical energy harvesting to third party power on-body devices. This article gives a comprehensive review of the piezoelectric nanogenerators for personalized healthcare. After a brief introduction to the fundamental physical science of the piezoelectric effect, material engineering strategies, device structural designs, and human-body centered energy harvesting, sensing, and therapeutics applications are also systematically discussed. In addition, the challenges and opportunities of utilizing piezoelectric nanogenerators for self-powered bioelectronics and personalized healthcare are outlined in detail.

In Vivo Basilar Membrane Time Delays in Humans

To date, objective measurements and psychophysical experiments have been used to measure frequency dependent basilar membrane (BM) delays in humans; however, in vivo measurements have not been made. This study aimed to measure BM delays by performing intracochlear electrocochleography in cochlear implant recipients. Sixteen subjects with various degrees of hearing abilities were selected. Postoperative Computer Tomography was performed to determine electrode locations. Electrical potentials in response to acoustic tone pips at 0.25, 0.5, 1, 2, and 4 kHz and clicks were recorded with electrodes at the frequency specific region. The electrode array was inserted up to the characteristic cochlear frequency region of 250 Hz for 6 subjects. Furthermore, the array was inserted in the region of 500 Hz for 15 subjects, and 1, 2, and 4 kHz were reached in all subjects. Intracochlear electrocochleography for each frequency-specific tone pip and clicks showed detectable responses in all subjects. The latencies differed among the cochlear location and the cochlear microphonic (CM) onset latency increased with decreasing frequency and were consistent with click derived band technique. Accordingly, BM delays in humans could be derived. The BM delays increased systematically along the cochlea from basal to apical end and were in accordance with Ruggero and Temchin, 2007.

Mathematical model of the auditory nerve response to stimulation by a micro-machined cochlea

We report a novel mathematical model of an artificial auditory system consisting of a micro-machined cochlea and the auditory nerve response it evokes. The modeled micro-machined cochlea is one previously realized experimentally by mimicking functions of the cochlea [Shintaku et al, Sens. Actuat. 158 (2010) 183-192; Inaoka et al, Proc. Natl. Acad. Sci. USA 108 (2011) 18390-18395]. First, from the viewpoint of mechanical engineering, the frequency characteristics of a model device were experimentally investigated to develop an artificial basilar membrane based on a spring-mass-damper system. In addition, a nonlinear feedback controller mimicking the function of the outer hair cells was incorporated in this experimental system. That is, the developed device reproduces the proportional relationship between the oscillation amplitude of the basilar membrane and the cube root of the sound pressure observed in the mammalian auditory system, which is what enables it to have a wide dynamic range, and the characteristics of the control performance were evaluated numerically and experimentally. Furthermore, the stimulation of the auditory nerve by the micro-machined cochlea was investigated using the present mathematical model, and the simulation results were compared with our previous experimental results from animal testing [Shintaku et al, J. Biomech. Sci. Eng. 8 (2013) 198-208]. The simulation results were found to be in reasonably good agreement with those from the previous animal test; namely, there exists a threshold at which the excitation of the nerve starts and a saturation value for the firing rate under a large input. The proposed numerical model was able to qualitatively reproduce the results of the animal test with the micro-machined cochlea and is thus expected to guide the evaluation of micro-machined cochleae for future animal experiments.

Development of Ultrasensitive Biomimetic Auditory Hair Cells Based on Piezoresistive Hydrogel Nanocomposites

With an ageing population, hearing disorders are predicted to rise considerably in the following decades. Thus, developing a new class of artificial auditory system has been highlighted as one of the most exciting research topics for biomedical applications. Herein, a design of a biocompatible piezoresistive-based artificial hair cell sensor is presented consisting of a highly flexible and conductive polyvinyl alcohol (PVA) nanocomposite with vertical graphene nanosheets (VGNs). The bilayer hydrogel sensor demonstrates excellent performance to mimic biological hair cells, responding to acoustic stimuli in the audible range between 60 Hz to 20 kHz. The sensor output demonstrates stable mid-frequency regions (∼4-9 kHz), with the greatest sensitivity as high frequencies (∼13-20 kHz). This is somewhat akin to the mammalian auditory system, which has remarkable sensitivity and sharp tuning at high frequencies due to the "active process". This work validates the PVA/VGN sensor as a potential candidate to play a similar functional role to that of the cochlear hair cells, which also operate over a wide frequency domain in a viscous environment. Further characterizations of the sensor show that increasing the sound amplitude results in higher responses from the sensor while taking it to the depth drops the sensor outputs due to attenuation of sound in water. Meanwhile, the acoustic pressure distribution of sound waves is predicted through finite element analysis, whereby the numerical results are in perfect agreement with experimental data. This proof-of-concept work creates a platform for the future design of susceptible, flexible biomimetic sensors to closely mimic the biological cochlea.

Development and Characterization of a Biomimetic Totally Implantable Artificial Basilar Membrane System

Cochlear implants (CIs) have become the standard treatment for severe-to-profound sensorineural hearing loss. Conventional CIs have some challenges, such as the use of extracorporeal devices, and high power consumption for frequency analysis. To overcome these, artificial basilar membranes (ABMs) made of piezoelectric materials have been studied. This study aimed to verify the conceptual idea of a totally implantable ABM system. A prototype of the totally implantable system composed of the ABM developed in previous research, an electronic module (EM) for the amplification of electrical output from the ABM, and electrode was developed. We investigated the feasibility of the ABM system and obtained meaningful auditory brainstem responses of deafened guinea pigs by implanting the electrode of the ABM system. Also, an optimal method of coupling the ABM system to the human ossicle for transducing sound waves into electrical signals using the middle ear vibration was studied and the electrical signal output according to the sound stimuli was measured successfully. Although the overall power output from the ABM system is still less than the conventional CIs and further improvements to the ABM system are needed, we found a possibility of the developed ABM system as a totally implantable CIs in the future.

Mechanical Energy Sensing and Harvesting in Micromachined Polymer-Based Piezoelectric Transducers for Fully Implanted Hearing Systems: A Review

The paper presents a comprehensive review of mechanical energy harvesters and microphone sensors for totally implanted hearing systems. The studies on hearing mechanisms, hearing losses and hearing solutions are first introduced to bring to light the necessity of creating and integrating the in vivo energy harvester and implantable microphone into a single chip. The in vivo energy harvester can continuously harness energy from the biomechanical motion of the internal organs. The implantable microphone executes mechanoelectrical transduction, and an array of such structures can filter sound frequency directly without an analogue-to-digital converter. The revision of the available transduction mechanisms, device configuration structures and piezoelectric material characteristics reveals the advantage of adopting the polymer-based piezoelectric transducers. A dual function of sensing the sound signal and simultaneously harvesting vibration energy to power up its system can be attained from a single transducer. Advanced process technology incorporates polymers into piezoelectric materials, initiating the invention of a self-powered and flexible transducer that is compatible with the human body, magnetic resonance imaging system (MRI) and the standard complementary metal-oxide-semiconductor (CMOS) processes. The polymer-based piezoelectric is a promising material that satisfies many of the requirements for obtaining high performance implantable microphones and in vivo piezoelectric energy harvesters.

Biomimetic and flexible piezoelectric mobile acoustic sensors with multiresonant ultrathin structures for machine learning biometrics

Flexible resonant acoustic sensors have attracted substantial attention as an essential component for intuitive human-machine interaction (HMI) in the future voice user interface (VUI). Several researches have been reported by mimicking the basilar membrane but still have dimensional drawback due to limitation of controlling a multifrequency band and broadening resonant spectrum for full-cover phonetic frequencies. Here, highly sensitive piezoelectric mobile acoustic sensor (PMAS) is demonstrated by exploiting an ultrathin membrane for biomimetic frequency band control. Simulation results prove that resonant bandwidth of a piezoelectric film can be broadened by adopting a lead-zirconate-titanate (PZT) membrane on the ultrathin polymer to cover the entire voice spectrum. Machine learning-based biometric authentication is demonstrated by the integrated acoustic sensor module with an algorithm processor and customized Android app. Last, exceptional error rate reduction in speaker identification is achieved by a PMAS module with a small amount of training data, compared to a conventional microelectromechanical system microphone.

A highly sensitive, self-powered triboelectric auditory sensor for social robotics and hearing aids

The auditory system is the most efficient and straightforward communication strategy for connecting human beings and robots. Here, we designed a self-powered triboelectric auditory sensor (TAS) for constructing an electronic auditory system and an architecture for an external hearing aid in intelligent robotic applications. Based on newly developed triboelectric nanogenerator (TENG) technology, the TAS showed ultrahigh sensitivity (110 millivolts/decibel). A TAS with the broadband response from 100 to 5000 hertz was achieved by designing the annular or sectorial inner boundary architecture with systematic optimization. When incorporated with intelligent robotic devices, TAS demonstrated high-quality music recording and accurate voice recognition for realizing intelligent human-robot interaction. Furthermore, the tunable resonant frequency of TAS was achieved by adjusting the geometric design of inner boundary architecture, which could be used to amplify a specific sound wave naturally. On the basis of this unique property, we propose a hearing aid with the TENG technique, which can simplify the signal processing circuit and reduce the power consuming. This work expresses notable advantages of using TENG technology to build a new generation of auditory systems for meeting the challenges in social robotics.

Flexible Piezoelectric Acoustic Sensors and Machine Learning for Speech Processing

Flexible piezoelectric acoustic sensors have been developed to generate multiple sound signals with high sensitivity, shifting the paradigm of future voice technologies. Speech recognition based on advanced acoustic sensors and optimized machine learning software will play an innovative interface for artificial intelligence (AI) services. Collaboration and novel approaches between both smart sensors and speech algorithms should be attempted to realize a hyperconnected society, which can offer personalized services such as biometric authentication, AI secretaries, and home appliances. Here, representative developments in speech recognition are reviewed in terms of flexible piezoelectric materials, self-powered sensors, machine learning algorithms, and speaker recognition.

Bioinspired Multiresonant Acoustic Devices Based on Electrospun Piezoelectric Polymeric Nanofibers

Cochlear hair cells are critical for the conversion of acoustic into electrical signals and their dysfunction is a primary cause of acquired hearing impairments, which worsen with aging. Piezoelectric materials can reproduce the acoustic-electrical transduction properties of the cochlea and represent promising candidates for future cochlear prostheses. The majority of piezoelectric hearing devices so far developed are based on thin films, which have not managed to simultaneously provide the desired flexibility, high sensitivity, wide frequency selectivity, and biocompatibility. To overcome these issues, we hypothesized that fibrous membranes made up of polymeric piezoelectric biocompatible nanofibers could be employed to mimic the function of the basilar membrane, by selectively vibrating in response to different frequencies of sound and transmitting the resulting electrical impulses to the vestibulocochlear nerve. In this study, poly(vinylidene fluoride-trifluoroethylene) piezoelectric nanofiber-based acoustic circular sensors were designed and fabricated using the electrospinning technique. The performance of the sensors was investigated with particular focus on the identification of the resonance frequencies and acoustic-electrical conversion in fibrous membrane with different size and fiber orientation. The voltage output (1-17 mV) varied in the range of low resonance frequency (100-400 Hz) depending on the diameter of the macroscale sensors and alignment of the fibers. The devices developed can be regarded as a proof-of-concept demonstrating the possibility of using piezoelectric fibers to convert acoustic waves into electrical signals, through possible synergistic effects of piezoelectricity and triboelectricity. The study has paved the way for the development of self-powered nanofibrous implantable auditory sensors.

A Preliminary Prototype High-Speed Feedback Control of an Artificial Cochlear Sensory Epithelium Mimicking Function of Outer Hair Cells

A novel feedback control technique for the local oscillation amplitude in an artificial cochlear sensory epithelium that mimics the functions of the outer hair cells in the cochlea is successfully developed and can be implemented with a control time on the order of hundreds of milliseconds. The prototype artificial cochlear sensory epithelium was improved from that developed in our previous study to enable the instantaneous determination of the local resonance position based on the electrical output from a bimorph piezoelectric membrane. The device contains local patterned electrodes deposited with micro electro mechanical system (MEMS) technology that is used to detect the electrical output and oscillate the device by applying local electrical stimuli. The main feature of the present feedback control system is the principle that the resonance position is recognized by simultaneously measuring the local electrical outputs of all of the electrodes and comparing their magnitudes, which drastically reduces the feedback control time. In this way, it takes 0.8 s to control the local oscillation of the device, representing the speed of control with the order of one hundred times relative to that in the previous study using the mechanical automatic stage to scan the oscillation amplitude at each electrode. Furthermore, the intrinsic difficulties in the experiment such as the electrical measurement against the electromagnetic noise, adhesion of materials, and fatigue failure mechanism of the oscillation system are also shown and discussed in detail based on the many scientific aspects. The basic knowledge of the MEMS fabrication and the experimental measurement would provide useful suggestions for future research. The proposed preliminary prototype high-speed feedback control can aid in the future development of fully implantable cochlear implants with a wider dynamic range.

Neural Modulation of the Primary Auditory Cortex by Intracortical Microstimulation with a Bio-Inspired Electronic System

Nowadays, the majority of the progress in the development of implantable neuroprostheses has been achieved by improving the knowledge of brain functions so as to restore sensorial impairments. Intracortical microstimulation (ICMS) is a widely used technique to investigate site-specific cortical responses to electrical stimuli. Herein, we investigated the neural modulation induced in the primary auditory cortex (A1) by an acousto-electric transduction of ultrasonic signals using a bio-inspired intracortical microstimulator. The developed electronic system emulates the transduction of ultrasound signals in the cochlea, providing bio-inspired electrical stimuli. Firstly, we identified the receptive fields in the primary auditory cortex devoted to encoding ultrasonic waves at different frequencies, mapping each area with neurophysiological patterns. Subsequently, the activity elicited by bio-inspired ICMS in the previously identified areas, bypassing the sense organ, was investigated. The observed evoked response by microstimulation resulted as highly specific to the stimuli, and the spatiotemporal dynamics of neural oscillatory activity in the alpha, beta, and gamma waves were related to the stimuli preferred by the neurons at the stimulated site. The alpha waves modulated cortical excitability only during the activation of the specific tonotopic neuronal populations, inhibiting neural responses in unrelated areas. Greater neuronal activity in the posterior area of A1 was observed in the beta band, whereas a gamma rhythm was induced in the anterior A1. The results evidence that the proposed bio-inspired acousto-electric ICMS triggers high-frequency oscillations, encoding information about the stimulation sites and involving a large-scale integration in the brain.

Nonlinear dynamic stability of piezoelectric thermoelastic electromechanical resonators

This research work deals with analyzing instability and nonlinear behaviors of piezoelectric thermal nano-bridges. An adjustable thermo-elastic model with the ability to control stability conditions is developed to examine the system behavior at different temperatures. To increase the performance range and improve system characteristics, a piezovoltage is applied and a spring is connected to the sliding end of the deformable beam as design parameters. The partial differential equations (PDEs) are derived using the extended Hamilton’s principle and Galerkin decomposition is implemented to discretize the nonlinear equations, which are solved via a computational method called the step-by-step linearization method (SSLM). To improve the accuracy of the solution, the number of mode shapes and the size of voltage increments are analyzed and sufficient values are employed in the solution. The validity of the formulation and solution method is verified with experimental, analytical, and numerical data for several cases. Finally, the vibration and eigenvalue problem of the actuated nano-manipulator subjected to electrostatic and Casimir attractions are investigated. It is concluded that the fringing-fields correction changes the system frequency, static equilibrium, and pull-in characteristics significantly. The results are expected to be instrumental in the analysis, design, and operation of numerous adjustable advanced nano-systems.

A thermosensitive electromechanical model for detecting biological particles

Miniature electromechanical systems form a class of bioMEMS that can provide appropriate sensitivity. In this research, a thermo-electro-mechanical model is presented to detect biological particles in the microscale. Identification in the model is based on analyzing pull-in instability parameters and frequency shifts. Here, governing equations are derived via the extended Hamilton’s principle. The coupled effects of system parameters such as surface layer energy, electric field correction, and material properties are incorporated in this thermosensitive model. Afterward, the accuracy of the present model and obtained results are validated with experimental, analytical, and numerical data for several cases. Performing a parametric study reveals that mechanical properties of biosensors can significantly affect the detection sensitivity of actuated ultra-small detectors and should be taken into account. Furthermore, it is shown that the number or dimension of deposited particles on the sensing zone can be estimated by investigating the changes in the threshold voltage, electrode deflection, and frequency shifts. The present analysis is likely to provide pertinent guidelines to design thermal switches and miniature detectors with the desired performance. The developed biosensor is more appropriate to detect and characterize viruses in samples with different temperatures.

Bioinspired Electronics for Artificial Sensory Systems

Humans have a myriad of sensory receptors in different sense organs that form the five traditionally recognized senses of sight, hearing, smell, taste, and touch. These receptors detect diverse stimuli originating from the world and turn them into brain-interpretable electrical impulses for sensory cognitive processing, enabling us to communicate and socialize. Developments in biologically inspired electronics have led to the demonstration of a wide range of electronic sensors in all five traditional categories, with the potential to impact a broad spectrum of applications. Here, recent advances in bioinspired electronics that can function as potential artificial sensory systems, including prosthesis and humanoid robots are reviewed. The mechanisms and demonstrations in mimicking biological sensory systems are individually discussed and the remaining future challenges that must be solved for their versatile use are analyzed. Recent progress in bioinspired electronic sensors shows that the five traditional senses are successfully mimicked using novel electronic components and the performance regarding sensitivity, selectivity, and accuracy have improved to levels that outperform human sensory organs. Finally, neural interfacing techniques for connecting artificial sensors to the brain are discussed.

Direct Powering a Real Cardiac Pacemaker by Natural Energy of a Heartbeat

Implantable medical devices are widely used for monitoring and treatment of severe diseases. In particular, an implantable cardiac pacemaker is the most effective therapeutic device for treating bradyrhythmia, however its surgical replacement is inevitable every 5-12 years due to the limited life of the built-in battery. Although several approaches of energy harvesting have been explored in this decade for powering cardiac pacemakers, the modern, commercial, and full-function pacemaker has never been powered effectively yet. Here, we report an integrated strategy for directly powering a modern and full-function cardiac pacemaker, which can pace the porcine heart in vivo by harvesting the natural energy of a heartbeat, without using any external energy storage element. The generator includes an elastic skeleton and two piezoelectric composites, which could generate a high-output current of 15 μA in vivo over state-of-the-art performance. This study makes an impressive step toward fabricating a self-powered cardiac pacemaker and resolving the power issue of implantable medical devices by piezoelectric harvesting technology.

Voltage readout from a piezoelectric intracochlear acoustic transducer implanted in a living guinea pig

The ability to measure the voltage readout from a sensor implanted inside the living cochlea enables continuous monitoring of intracochlear acoustic pressure locally, which could improve cochlear implants. We developed a piezoelectric intracochlear acoustic transducer (PIAT) designed to sense the acoustic pressure while fully implanted inside a living guinea pig cochlea. The PIAT, fabricated using micro-electro-mechanical systems (MEMS) techniques, consisted of an array of four piezoelectric cantilevers with varying lengths to enhance sensitivity across a wide frequency bandwidth. Prior to implantation, benchtop tests were conducted to characterize the device performance in air and in water. When implanted in the cochlea of an anesthetized guinea pig, the in vivo voltage response from the PIAT was measured in response to 80–95 dB sound pressure level 1–14 kHz sinusoidal acoustic excitation at the entrance of the guinea pig’s ear canal. All sensed signals were above the noise floor and unaffected by crosstalk from the cochlear microphonic or external electrical interference. These results demonstrate that external acoustic stimulus can be sensed via the piezoelectric voltage response of the implanted MEMS transducer inside the living cochlea, providing key steps towards developing intracochlear acoustic sensors to replace external or subcutaneous microphones for auditory prosthetics.

A Novel Frequency Selectivity Approach Based on Travelling Wave Propagation in Mechanoluminescence Basilar Membrane for Artificial Cochlea

This study presents the initial assessment for a new approach to frequency selectivity aimed at mimicking the function of the basilar membrane within the human cochlea. The term cochlea tonotopy refers to the passive frequency selectivity and a transformation from the acoustic wave into a frequency signal assisted by the hair cells in the organ of Corti. While high-frequency sound waves vibrate near the base of the cochlea (near the oval windows), low-frequency waves vibrate near the apex (at the maximum distance from the base), which suggests the existence of continuous frequency selectivity. Over the past few decades, frequency selectivity using artificial membranes has been utilized in acoustic transducers by mimicking cochlea tonotopy using cantilever-beam arrays with defined physical parameters such as length and thickness. Unlike the conventional cantilever-beam array type, the travelling wave propagation based-mechanoluminescence (ML) membrane made of ZnS:Cu- polydimethylsiloxane (ZnS:Cu-PDMS) composite that we describe here provides new frequency selectivity more similar to that demonstrated by the human membrane. Here, we explored the potential of the ML membrane to deliver new frequency selectivity by using a non-contact image sensor to measure visualized frequencies. We report that the ML basilar membrane can provide effective visualization of the distribution of strain rate associated with the position of maximal amplitude of the travelling wave.

Artificial Cochlear Sensory Epithelium with Functions of Outer Hair Cells Mimicked Using Feedback Electrical Stimuli

We report a novel vibration control technique of an artificial auditory cochlear epithelium that mimics the function of outer hair cells in the organ of Corti. The proposed piezoelectric and trapezoidal membrane not only has the acoustic/electric conversion and frequency selectivity of the previous device developed mainly by one of the authors and colleagues, but also has a function to control local vibration according to sound stimuli. Vibration control is achieved by applying local electrical stimuli to patterned electrodes on an epithelium made using micro-electro-mechanical system technology. By choosing appropriate phase differences between sound and electrical stimuli, it is shown that it is possible to both amplify and dampen membrane vibration, realizing better control of the response of the artificial cochlea. To be more specific, amplification and damping are achieved when the phase difference between the membrane vibration by sound stimuli and electrical stimuli is zero and π, respectively. We also demonstrate that the developed control system responds automatically to a change in sound frequency. The proposed technique can be applied to mimic the nonlinear response of the outer hair cells in a cochlea, and to realize a high-quality human auditory system.

Design principles of hair-like structures as biological machines

Hair-like structures are prevalent throughout biology and frequently act to sense or alter interactions with an organism's environment. The overall shape of a hair is simple: a long, filamentous object that protrudes from the surface of an organism. This basic design, however, can confer a wide range of functions, owing largely to the flexibility and large surface area that it usually possesses. From this simple structural basis, small changes in geometry, such as diameter, curvature and inter-hair spacing, can have considerable effects on mechanical properties, allowing functions such as mechanosensing, attachment, movement and protection. Here, we explore how passive features of hair-like structures, both individually and within arrays, enable diverse functions across biology. Understanding the relationships between form and function can provide biologists with an appreciation for the constraints and possibilities on hair-like structures. Additionally, such structures have already been used in biomimetic engineering with applications in sensing, water capture and adhesion. By examining hairs as a functional mechanical unit, geometry and arrangement can be rationally designed to generate new engineering devices and ideas.

Biomimetic Artificial Basilar Membranes for Next-Generation Cochlear Implants

Patients with sensorineural hearing loss can recover their hearing using a cochlear implant (CI). However, there is a need to develop next-generation CIs to overcome the limitations of conventional CIs caused by extracorporeal devices. Recently, artificial basilar membranes (ABMs) are actively studied for next-generation CIs. The ABM is an acoustic transducer that mimics the mechanical frequency selectivity of the BM and acoustic-to-electrical energy conversion of hair cells. This paper presents recent progress in biomimetic ABMs. First, the characteristics of frequency selectivity of the ABMs by the trapezoidal membrane and beam array are addressed. Second, to reflect the latest research of energy conversion technologies, ABMs using various piezoelectric materials and triboelectric-based ABMs are discussed. Third, in vivo evaluations of the ABMs in animal models are discussed according to the target position for implantation. Finally, future perspectives of ABM studies for the development of practical hearing devices are discussed.

Spiral-Shaped Piezoelectric MEMS Cantilever Array for Fully Implantable Hearing Systems

Fully implantable, self-powered hearing aids with no external unit could significantly increase the life quality of patients suffering severe hearing loss. This highly demanding concept, however, requires a strongly miniaturized device which is fully implantable in the middle/inner ear and includes the following components: frequency selective microphone or accelerometer, energy harvesting device, speech processor, and cochlear multielectrode. Here we demonstrate a low volume, piezoelectric micro-electromechanical system (MEMS) cantilever array which is sensitive, even in the lower part of the voice frequency range (300–700 Hz). The test array consisting of 16 cantilevers has been fabricated by standard bulk micromachining using a Si-on-Insulator (SOI) wafer and aluminum nitride (AlN) as a complementary metal-oxide-semiconductor (CMOS) and biocompatible piezoelectric material. The low frequency and low device footprint are ensured by Archimedean spiral geometry and Si seismic mass. Experimentally detected resonance frequencies were validated by an analytical model. The generated open circuit voltage (3–10 mV) is sufficient for the direct analog conversion of the signals for cochlear multielectrode implants.

Analytical and numerical modeling of the hearing system: Advances towards the assessment of hearing damage

Hearing is an extremely complex phenomenon, involving a large number of interrelated variables that are difficult to measure in vivo. In order to investigate such process under simplified and well-controlled conditions, models of sound transmission have been developed through many decades of research. The value of modeling the hearing system is not only to explain the normal function of the hearing system and account for experimental and clinical observations, but to simulate a variety of pathological conditions that lead to hearing damage and hearing loss, as well as for development of auditory implants, effective ear protections and auditory hazard countermeasures. In this paper, we provide a review of the strategies used to model the auditory function of the external, middle, inner ear, and the micromechanics of the organ of Corti, along with some of the key results obtained from such modeling efforts. Recent analytical and numerical approaches have incorporated the nonlinear behavior of some parameters and structures into their models. Few models of the integrated hearing system exist; in particular, we describe the evolution of the Auditory Hazard Assessment Algorithm for Human (AHAAH) model, used for prediction of hearing damage due to high intensity sound pressure. Unlike the AHAAH model, 3D finite element models of the entire hearing system are not able yet to predict auditory risk and threshold shifts. It is expected that both AHAAH and FE models will evolve towards a more accurate assessment of threshold shifts and hearing loss under a variety of stimuli conditions and pathologies.

A Triboelectric-Based Artificial Basilar Membrane to Mimic Cochlear Tonotopy

A triboelectric-based artificial basilar membrane (TEABM) can mimic cochlear tonotopy by triboelectrification between Kapton film and aluminum foil. The two films are stacked and clamped to form a beam structure. The TEABM tonotopy is tested using an animal model to verify the feasibility of a self-powered acoustic sensor for a prototype cochlear implant.