Nanomaterials-Based Bioinspired Next Generation Wearable Sensors: A State-of-the-Art Review

With a constantly growing percentage of the population having access to high-quality healthcare facilities, preventable pathogenic illnesses have been nearly eradicated in the developed parts of the world, which has led to a significant rise in the average human life expectancy over the last few decades. In such a highly developed world, age-related illnesses will lead to an immense burden on healthcare providers. Remote health monitoring enabled by wearable sensors will play a significant role in the growth and evolution of Health 3.0 by providing intimate and valuable information to healthcare providers regarding the progression of disease in patients with critical life-altering conditions. Especially, in the case of people suffering from neurodegenerative disorders, inexpensive and user-friendly wearable sensors can enable physiotherapists monitor real-time physiological parameters to design patient-specific treatment plans. This review provides a comprehensive overview of the recent advances and emerging trends at the convergence of biomimicry and nanomaterial sensors, with a specific focus on wearable skin-inspired mechanical sensors for applications in IoT-enabled human physiological parameters monitoring. Skin-inspired wearable mechanical sensors with relevance to the most common types of sensing mechanisms including piezoresistive, piezocapacitive, and triboelectric sensing are discussed along with their current challenges and possible future opportunities

Nanomaterials-Based Bioinspired Next Generation Wearable Sensors: A State-of-the-Art Review

With a constantly growing percentage of the population having access to high-quality healthcare facilities, preventable pathogenic illnesses have been nearly eradicated in the developed parts of the world, which has led to a significant rise in the average human life expectancy over the last few decades. In such a highly developed world, age-related illnesses will lead to an immense burden on healthcare providers. Remote health monitoring enabled by wearable sensors will play a significant role in the growth and evolution of Health 3.0 by providing intimate and valuable information to healthcare providers regarding the progression of disease in patients with critical life-altering conditions. Especially, in the case of people suffering from neurodegenerative disorders, inexpensive and user-friendly wearable sensors can enable physiotherapists monitor real-time physiological parameters to design patient-specific treatment plans. This review provides a comprehensive overview of the recent advances and emerging trends at the convergence of biomimicry and nanomaterial sensors, with a specific focus on wearable skin-inspired mechanical sensors for applications in IoT-enabled human physiological parameters monitoring. Skin-inspired wearable mechanical sensors with relevance to the most common types of sensing mechanisms including piezoresistive, piezocapacitive, and triboelectric sensing are discussed along with their current challenges and possible future opportunities

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

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

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

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