Ultralight Weight Piezoresistive Spongy Graphene Sensors for Human Gait Monitoring Applications

This work reports a facile method of fabricating ultralight weight (density of 0.305 g/cm3) and squeezable microporous graphene-PDMS piezoresistive sensors for human gait monitoring applications. The sensor reported in this work demonstrates piezoresistivity by utilizing the conductive domain discontinuity mechanism demonstrated by multilayer graphene nanoflakes populating the inner pore walls of microporous PDMS sponges. Quasi-static compressive strain characterization experiments conducted on the sensor revealed a linear response with a gauge factor of 8.77 for compressive strains up to 9.5%. Two identical graphene-PDMS sponge sensors embedded into a pair of soft shoe-soles were used to demonstrate comprehensive real-time gait monitoring, which includes pressure profiling of the heels of both the legs

Piezoresistive Carbon Nanofiber-Based Cilia-Inspired Flow Sensor

Evolving over millions of years, hair-like natural flow sensors called cilia, which are found in fish, crickets, spiders, and inner ear cochlea, have achieved high resolution and sensitivity in flow sensing. In the pursuit of achieving such exceptional flow sensing performance in artificial sensors, researchers in the past have attempted to mimic the material, morphological, and functional properties of biological cilia sensors, to develop MEMS-based artificial cilia flow sensors. However, the fabrication of bio-inspired artificial cilia sensors involves complex and cumbersome micromachining techniques that lay constraints on the choice of materials, and prolongs the time taken to research, design, and fabricate new and novel designs, subsequently increasing the time-to-market. In this work, we establish a novel process flow for fabricating inexpensive, yet highly sensitive, cilia-inspired flow sensors. The artificial cilia flow sensor presented here, features a cilia-inspired high-aspect-ratio titanium pillar on an electrospun carbon nanofiber (CNF) sensing membrane. Tip displacement response calibration experiments conducted on the artificial cilia flow sensor demonstrated a lower detection threshold of 50 µm. Furthermore, flow calibration experiments conducted on the sensor revealed a steady-state airflow sensitivity of 6.16 mV/(m s−1) and an oscillatory flow sensitivity of 26 mV/(m s−1), with a lower detection threshold limit of 12.1 mm/s in the case of oscillatory flows. The flow sensing calibration experiments establish the feasibility of the proposed method for developing inexpensive, yet sensitive, flow sensors; which will be useful for applications involving precise flow monitoring in microfluidic devices, precise air/oxygen intake monitoring for hypoxic patients, and other biomedical devices tailored for intravenous drip/urine flow monitoring. In addition, this work also establishes the applicability of CNFs as novel sensing elements in MEMS devices and flexible sensors

3D Printed Graphene-Coated Flexible Lattice as Piezoresistive Pressure Sensor

Piezoresistive sponges represent a popular design for highly flexible pressure sensors and are typically fabricated using templating methods. In this work, we used stereolithography (SLA) to 3D-print an elastomeric body-centered cubic (BCC) lattice structure with a relative density of 21% and an elastic modulus of 31.5 kPa. The lattice was dip-coated with graphene nanoplatelets to realize a piezoresistive pressure sensor with excellent performance (gauge factor = 3.25, sensitivity = 0.1 kPa-1), high deformability (up to 60 % strain), and repeatability. The novel approach outlined in this work offers greater control over the microstructure and can be used to fabricate sensors with tunable properties

Electrospun Bundled Carbon Nanofibers for Skin-Inspired Tactile Sensing, Proprioception and Gesture Tracking Applications

Abstract In this work, we report a class of wearable, stitchable, and sensitive carbon nanofiber (CNF)-polydimethylsiloxane (PDMS) composite-based piezoresistive sensors realized by carbonizing electrospun polyacrylonitrile (PAN) nanofibers and subsequently embedding in PDMS elastomeric thin films. Electro-mechanical tactile sensing characterization of the resulting piezoresistive strain sensors revealed a linear response with an average force sensitivity of ~1.82 kN−1 for normal forces up to 20 N. The real-time functionality of the CNF-PDMS composite sensors in wearable body sensor networks and advanced bionic skin applications was demonstrated through human motion and gesture monitoring experiments. A skin-inspired artificial soft sensor capable of demonstrating proprioceptive and tactile sensory perception utilizing CNF bundles has been shown. Furthermore, a 16-point pressure-sensitive flexible sensor array mimicking slow adapting low threshold mechanoreceptors of glabrous skin was demonstrated. Such devices in tandem with neuromorphic circuits can potentially recreate the sense of touch in robotic arms and restore somatosensory perception in amputees

Flexible Graphene-on-PDMS Sensor for Human Motion Monitoring Applications

In this work, a 4-step method of developing flexible, stretchable, and thin graphene-on-polydimethylsiloxane (PDMS) piezoresistive strain sensors is presented. The proposed sensor utilizes the piezoresistive property observed in a dense graphene-nanoflakes percolation network sandwiched between two flexible PDMS layers for strain sensing applications. A gait monitoring system comprising of two identical sensors integrated on the knee region of a sports leggings is developed and demonstrated for real-time human motion monitorin

Ultralightweight and 3D Squeezable Graphene-Polydimethylsiloxane Composite Foams as Piezoresistive Sensors

The growing demand for flexible, ultrasensitive, squeezable, skin-mountable and wearable sensors tailored to the requirements of personalized health care monitoring has fueled the necessity to explore novel nanomaterial-polymer composite-based sensors. Herein, we report a sensitive, 3D squeezable graphene-polydimethylsiloxane (PDMS) foam-based piezoresistive sensor realized by infusing multi-layered graphene nanoparticles into a sugar scaffolded porous PDMS foam structure. Static and dynamic compressive strain testing of the resulting piezoresistive foams sensors revealed two linear response regions with an average gauge factor of 2.87 ~ 8.77 over a strain range of 0-50 %. Furthermore, the dynamic stimulus-response revealed the ability of the sensors to effectively track dynamic pressure up to a frequency of 70 Hz. In addition, the sensors displayed a high stability over 36000 cycles of cyclic compressive loading and 100 cycles of complete human gait motion. The 3D sensing foams were applied to experimentally demonstrate accurate human gait monitoring through both simulated gait models and real-time gait characterization experiments. The real-time gait experiments conducted demonstrate that the information of the pressure profile obtained at three locations in the shoe sole could not only differentiate between different kinds of human gait including walking and running, but also identify possible fall conditions. This work also demonstrates the capability of the sensors to differentiate between foot anatomies, such as a flat foot (low central arch) and a medium arch foot which is biomechanically more efficient. Furthermore, the sensors were able to sense various basic joint movement responses demonstrating their suitability for personalized healthcare applications

Nature-Inspired Self-Powered Sensors and Energy Harvesters

Chapter 3 presents a comprehensive review of the various biomimetic self-powered and low-powered MEMS pressure and flow sensors that take inspiration from the biological flow sensors found in the marine world. The sensing performance of the biological flow sensors in marine animals has inspired engineers and scientists to develop efficient state-of-the-art sensors for a variety of real-life applications. In an attempt to achieve high-performance artificial flow sensors, researchers have mimicked the morphology, sensing principle, materials, and functionality of the biological sensors. Inspiration was derived from the survival hydrodynamics featured by various marine animals to develop sensors for sensing tasks in underwater vehicles. The mechanoreceptors of crocodiles have inspired the development of slowly and rapidly adapting MEMS sensory domes for passive underwater sensing. Likewise, the lateral line sensing system in fishes which is capable of generating a three-dimensional map of the surroundings was mimicked to achieve artificial hydrodynamic vision on underwater vehicles. Harbor seals are known to achieve high sensitivity in sensing flows within the wake street of a swimming fish due to the undulatory geometry of the whiskers. Whisker inspired structures were embedded into MEMS sensing membranes to understand their vortex shedding behavior. At the outset, this work comprehensively reviews the sensing mechanisms observed in fishes, crocodiles, and harbor seals. In addition, this chapter presents an in-depth commentary on the recent developments in this area where different researchers have taken inspiration from these aforementioned underwater creatures and developed some of the most efficient artificial sensing systems

Source Seeking Control of Unicycle Robots with 3-D-Printed Flexible Piezoresistive Sensors

We present the design and experimental validation of source seeking control algorithms for a unicycle mobile robot that is equipped with novel 3D-printed flexible graphene-based piezoresistive airflow sensors. Based solely on a local gradient measurement from the airflow sensors, we propose and analyze a projected gradient ascent algorithm to solve the source seeking problem. In the case of partial sensor failure, we propose a combination of Extremum-Seeking Control with our projected gradient ascent algorithm. For both control laws, we prove the asymptotic convergence of the robot to the source. Numerical simulations were performed to validate the algorithms and experimental validations are presented to demonstrate the efficacy of the proposed methods

PDMS Flow Sensors With Graphene Piezoresistors Using 3D Printing and Soft Lithography

This paper reports the fabrication and characterization of a flexible piezoresistive flow sensor comprising a polydimethylsiloxane (PDMS) cantilever with a serpentine graphene nanoplatelets (GNP) strain gauge embedded at the cantilever base. A facile and cleanroom-free processing work flow involving a combination of high-resolution powder bed fusion and soft lithography was used to fabricate PDMS cantilevers (aspect ratio 20) with 150 µm × 150 µm microchannels on its surface. A high gauge factor of 55 (up to 5 times higher than reported in comparable piezoresistive flow sensors) was achieved using drop-casted GNP ink as the piezoresistive sensing element in the aforementioned microchannels. Finally, the use of the PDMS-graphene cantilever as an airflow sensor with enhanced sensitivity (20 times more than comparable piezoresistive cantilever sensors), low hysteresis, good repeatability, and bidirectional sensing capability was demonstrated