Optimization of Cricket-inspired, Biomimetic Artificial Hair Sensors for Flow Sensing

High density arrays of artificial hair sensors, biomimicking the extremely sensitive mechanoreceptive filiform hairs found on cerci of crickets have been fabricated successfully. We assess the sensitivity of these artificial sensors and present a scheme for further optimization addressing the deteriorating effects of stress in the structures. We show that, by removing a portion of chromium electrodes close to the torsional beams, the upward lift at the edges of the membrane due to the stress, will decrease hence increase the sensitivity.Comment: Submitted on behalf of EDA Publishing Association (http://irevues.inist.fr/EDA-Publishing

Biomimetic flow-sensor arrays based on the filiform hairs on the cerci of crickets

In this paper we report on the latest developments in biomimetic flow-sensors based on the flow sensitive mechano-sensors of crickets. Crickets have one form of acoustic sensing evolved in the form of mechanoreceptive sensory hairs. These filiform hairs are highly perceptive to low-frequency sound with energy sensitivities close to thermal threshold. Arrays of artificial hair sensors have been fabricated using a surface micromachining technology to form suspended silicon nitride membranes and double-layer SU-8 processing to form 1 mm long hairs. Previously, we have shown that these hairs are sensitive to low-frequency sound, using a laser vibrometer setup to detect the movements of the nitride membranes. We have now realized readout electronics to detect the movements capacitively, using electrodes integrated on the membranes

Optimization Of Bio-inspired Hair Sensor Arrays

Crickets use a pair of hairy appendages on their abdomen called cerci, each of which contains numerous mechano-receptive filiform hairs. These sensitive hairs can respond even to the slightest air movements, down to 0.03 mm/s, generated by the approaching predators and initiating an escape mechanism in the crickets. Bio-mimicking the cricket cerci, arrays of artificial hair sensors have been successfully fabricated using advanced MEMS techniques. Despite its appreciable performance, the actual cricket filiform hairs outperform artificial hair sensors by several orders in sensitivity. Nevertheless, more careful look at the anatomy and physiology of the cricket cerci provides new directions to be explored with MEMS technologies to realize higher sensitivities on a par with crickets’. This paper aims to provide an overview of comparisons between the actual and artificial hair sensors in terms of sensitivity, structural functionalities and robustness and draws out constructive insights to optimize sensor performance

Model-based optimization of tunable, biomimetic hair sensor arrays

Crickets have, quite often, been a subject of common interest to biologists and engineers. They have evolved with a pair of special flow-sensitive appendices called cerci with numerous mechano-receptive filiform hairs of different lengths, distributed on the surface. These filiform hairs are extremely sensitive to acoustic signals, down to thermal noise levels, enabling them to identify and escape from approaching predators. Each filiform hair has a mechano-sensitive neuron at its base which fires a neuro-signal whenever there is a flow-induced deflection on the hair. Inspired by crickets and making use of technical advancements in MEMS techniques, SU-8 based artificial hair sensor arrays were successfully implemented recently [2]. Ways to improve the sensitivity of these artificial hair sensor arrays have been demonstrated; increasing the hair length and arranging the sensors on an artificial cercus-like platform that can be assembled to facilitate 3D-flow sensing. In this work, we present a model for our biomimetic, artificial hair sensors, to analyze the sensitivity dependence on their structural and geometrical parameters. Based on this model, feasible design improvements to achieve an increased sensitivity are discussed and a figure of merit to evaluate sensor performance is defined. Also, we discuss the results of a novel approach to implement adaptive sensor arrays through DC-biasing based on the electrostatic spring-softening effect. Experimental results show a clear theoretical accordance and tunability of system’s resonance frequency, providing opportunities for frequency focusing and selective sensitivity

Adaptive, cricket-inspired artificial hair sensor arrays

In this work, we present a model for our biomimetic, artificial hair sensors, to analyze the sensitivity dependence on their structural and geometrical parameters. Based on this model, feasible design improvements to achieve an increased sensitivity are discussed and a figure of merit to evaluate sensor performance is defined. Also, we discuss the results of a novel approach to implement adaptive sensor arrays through DC-biasing based on the electrostatic spring-softening effect. Experimental results show a clear theoretical accordance and tunability of system’s resonance frequency, providing opportunities for frequency focusing and selective sensitivity

Biomimetic flow-sensor arrays based on the filiform hairs on the cerci of crickets

In this paper we report on the latest developments in biomimetic flow-sensors based on the flow sensitive mechano-sensors of crickets. Crickets have one form of acoustic sensing evolved in the form of mechanoreceptive sensory hairs. These filiform hairs are highly perceptive to low-frequency sound with energy sensitivities close to thermal threshold. Arrays of artificial hair sensors have been fabricated using a surface micromachining technology to form suspended silicon nitride membranes and double-layer SU-8 processing to form 1 mm long hairs. Previously, we have shown that these hairs are sensitive to low-frequency sound, using a laser vibrometer setup to detect the movements of the nitride membranes. We have now realized readout electronics to detect the movements capacitively, using electrodes integrated on the membranes

Model-based optimization and adaptivity of cricket-inspired biomimetic artificial hair sensor arrays

We present a model for our cricket-inspired, biomimetic, artificial hair sensors, to analyze the sensitivity dependence on structural and geometrical parameters. Based on this model, feasible design improvements to achieve an increased sensitivity are discussed and a figure of merit to evaluate sensor performance is defined. Also, we discuss the results of a novel approach to implement adaptive sensor arrays through DC-biasing based on the electrostatic spring-softening effect. Experimental results show a clear theoreti¬cal accordance and tunability of system’s resonance frequency, providing opportunities for frequency focusing and selective sensitivity

Adaptation for frequency focusing and increased sensitivity in biomimetic flow sensors using electrostatic spring softening

This paper presents the results of active adaptation of sensor sensitivity. By applying a DC-bias voltage to the sensing electrodes of a cricket inspired artificial hair sensor the effective spring stiffness can be adapted resulting in a reduced resonance frequency and increased sensitivity. An array of flow sensors was actuated using electrical and acoustical signals at different values of the DC-bias voltage. Characterization was done using a scanning laser vibrometer. Both resonance frequency versus applied DC-bias voltage and deflection-amplitude versus DC-bias voltage behave well in accordance to theory and show that adaptation by DC-biasing can be used for frequency focusing and increasing sensitivity

Highly sensitive biomimetic flow sensor arrays

In this paper, we report, to the best of our knowledge [1], the most sensitive artificial hair-based flow-sensor arrays operating in air, to date. Artificial hair sensors are bio-inspired from crickets’ cerci, one of nature’s best in sensing small air flows. The presented hair sensor arrays aim to realize higher sensitivity by means of model-based design optimizations and fabricated with advanced MEMS technologies. The presented artificial hair-sensor arrays display a clear figure-of-eight response and show remarkable sensitivities to oscillating air flows down to 0.85 mm/s that surpass noise levels even at 1 kHz operational bandwidths