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

Spiral Ganglion Neurite Outgrowth and Pathfinding on Electrospun Microfibrous Piezoelectric Nanocomposite Polymer Scaffolds

Sensorineural hearing loss (SNHL) can be caused by hair cell loss and spiral ganglion neurone (SGN) degeneration. Cochlear implants (CIs), the only means of restoring residual hearing to profoundly deaf people, stimulate possible preserved SGNs electrically. Thus, SGN degeneration dictates the efficacy of CIs. SGN degeneration reduces sensitivity and frequency selectivity. In addition, stimulation thresholds increase due to SGN degeneration consequently increasing power demands. The replacement of auditory neurones with proper functional spatial alignment is an important step in the attempt to restore auditory function. This study adopts a tissue-engineering approach. We examined the viability of polyvinylidene fluoride (PVDF) and polyvinylidene trifluoroethylene (P(VDF-TrFE)). P(VDF-TrFE) was chosen to add directional growth cues through electrospinning aligned microfibrous scaffolds. The effects of the scaffolds on the length and orientation of re-growing SGN neurites and glia were tested in vitro using primary murine cultures. Two methods of SGN preparation were compared; explants and dissociated cultures. Primary SGNs showed preferential affinity to P(VDF-TrFE) microfibres and the microfibrous scaffolds were found to promote aligned SGN neurite regrowth compared to glass coverslips. Subsequently, we doped the electrospun P(VDF-TrFE) microfibres with carbon nanotubes (CNT) to optimise the scaffold mechanically and electrically. The CNT addition was found to be biocompatible and promoted aligned SGN neurite regrowth. The CNT doping enhanced the mechanical properties of the microfibres and improved scaffold handling. Moreover, the scaffolds could be biofunctionalized with neurone modulating drugs. Preliminary testing of gamma-secretase inhibitor (LY411575) showed promising regenerative effects on SGNs in vitro. In conclusion, electrospun aligned microfibrous P(VDF-TrFE)-CNT nanocomposite scaffolds can modulate glial and SGN neurite and axon organization in vitro. Combined with a specific protocol of electrical induction in the first weeks of implantation, the piezoelectric fibrous scaffold could significantly improve cochlear implantation results, frequency selectivity and minimize power demands

An overview on structural health monitoring: From the current state-of-the-art to new bio-inspired sensing paradigms

In the last decades, the field of structural health monitoring (SHM) has grown exponentially. Yet, several technical constraints persist, which are preventing full realization of its potential. To upgrade current state-of-the-art technologies, researchers have started to look at nature’s creations giving rise to a new field called ‘biomimetics’, which operates across the border between living and non-living systems. The highly optimised and time-tested performance of biological assemblies keeps on inspiring the development of bio-inspired artificial counterparts that can potentially outperform conventional systems. After a critical appraisal on the current status of SHM, this paper presents a review of selected works related to neural, cochlea and immune-inspired algorithms implemented in the field of SHM, including a brief survey of the advancements of bio-inspired sensor technology for the purpose of SHM. In parallel to this engineering progress, a more in-depth understanding of the most suitable biological patterns to be transferred into multimodal SHM systems is fundamental to foster new scientific breakthroughs. Hence, grounded in the dissection of three selected human biological systems, a framework for new bio-inspired sensing paradigms aimed at guiding the identification of tailored attributes to transplant from nature to SHM is outlined.info:eu-repo/semantics/acceptedVersio

Development of adaptive transducer based on biological sensory mechanism

textAn adaptive sensor concept and prototype has been developed based on a sensing element which is analogous to and inspired by the arrangement of outer hair cells and inner hair cells between the basilar membrane and tectorial membrane which form the organ of corti in mammalian cochlea. The bio-inspired design was supported by development of a bond graph model of the electromotility (active response) of outer hair cells. Outer hair cells perform like actuators and simulation results using this model are compared with physiological data found in the literature to verify its characteristic response. Insight gained from the model is used to develop a sensor structure analogous to the organ of corti and designed to measure acceleration. A piezoelectric bimorph was selected as the transducer basis, and a bond graph model of the bimorph in an accelerometer configuration was formulated to aid control design and simulation. There is no published data regarding the type of information transmitted among the inner hair cells, outer hair cells, and brain. Consequently, a controller intended to adjust the adaptation process similar to what might exist in the cochlear system has been developed for the sensor and based on a model referenced adaptive control algorithm. Simulations verify that the algorithm can successfully control and enhance performance of the sensor. Practicability of the design is evaluated by a series of experiments on a prototype. This study focused on using a controller structure that was programmed, implemented, and tested using programmable logic based on FPGA technology. The experiments evaluated how well the adaptive sensor could meet a specified performance requirement. Implementation issues that arise, such as the need for differentiators in the adaptive controller or internal propagation of vibration within the sensor structure, hinder the tuning ability. Nevertheless, the trends indicate that the algorithm can meet the desired performance if certain limitations can be overcome. Finally, recommendations have been made for expansion of the research in such fields as an alternative structure for tuning, sensor networking, and reference sensor configuration.Mechanical Engineerin

Fast frequency discrimination and phoneme recognition using a biomimetic membrane coupled to a neural network

In the human ear, the basilar membrane plays a central role in sound recognition. When excited by sound, this membrane responds with a frequency-dependent displacement pattern that is detected and identified by the auditory hair cells combined with the human neural system. Inspired by this structure, we designed and fabricated an artificial membrane that produces a spatial displacement pattern in response to an audible signal, which we used to train a convolutional neural network (CNN). When trained with single frequency tones, this system can unambiguously distinguish tones closely spaced in frequency. When instead trained to recognize spoken vowels, this system outperforms existing methods for phoneme recognition, including the discrete Fourier transform (DFT), zoom FFT and chirp z-transform, especially when tested in short time windows. This sound recognition scheme therefore promises significant benefits in fast and accurate sound identification compared to existing methods.Comment: 7 pages, 4 figure

A Bio-inspired Framework for Highly Efficient Structural Health Monitoring and Vibration Analysis

Civil engineering structures are continuously exposed to the risk of damage whether due to ageing effects, excessive live loads or extreme events, such as earthquakes, blasts and cyclones. If not readily identified, damage will inevitably compromise the structural integrity, leading the system to stop operating and undergo in-depth interventions. The economic and social impacts associated with such an adverse condition can be significant, therefore effective methods able to early identify structural vulnerabilities are needed for these systems to keep meeting the required life-safety standards and avoid the impairment of their normal function. In this context, vibration-based analysis approaches play a leading role as they allow to detect structural faults which lie beneath the surface of the structure by identifying and quantifying anomalous changes in the system’s inherent vibration characteristics. However, although the considerable degree of maturity attained within the fields of experimental vibration analysis (EVA) and structural health monitoring (SHM), several technical issues still need to be addressed in order to ensure the successful implementation of these powerful tools for damage identification purposes. The scope of this paper is to present a bio-inspired framework for optimal structural health monitoring and vibration analysis. After a critical overview on current methods and tools, three main sources of bio-inspiration are described along with the relative algorithms derived for SHM applications. It is shown how uncovering the general principles behind the functioning of selected biological systems can foster the development of efficient solutions to the technical conflicts of actual SHM architectures and lead to new sensing paradigms for optimal network topology and sensors location. A compatibility-matrix is proposed to help compare biological and SHM systems and discriminate desired from unwanted features. Such a framework will ultimately assist in seeking for the most suitable nature-inspired solutions for more accurate condition screening and robust vibration analysis.FEDER funds through the Competitiveness Factors Operational Programme - COMPETE and by national funds through FCT – Foundation for Science and Technology within the scope of the project POCI-01-0145-FEDER-007633info:eu-repo/semantics/publishedVersio