Search for: All records

Out-of-surface microchannels (OSMiCs) are arched, monolithic PDMS structures that shrink under tensile strain, directly converting skin stretching into fluid pressure and addressing a critical challenge in wearable microfluidics. 

Abstract An integrated strain sensor system that has a unique response to a specific (set of) human movement(s) has the potential to impact various musculoskeletal health tracking applications akin to the step counter's impact on physical activity tracking. It is determined that an open circuit state of a sensor can be used as such a unique response. With this consideration, a digital strain sensor (DigSS) that exhibits a binary (i.e., ON/OFF) response when a threshold strain level is exceeded is developed. The channel geometry dependence of the corner flow in capillaric strain sensors (CSS) resulting in an electrofluidic switch is used. It is demonstrated that through the coalescence and breakup of a liquid meniscus, DigSS operates for hundreds of cycles with a strain limit of detection of 0.0026. To facilitate integration, a linear optimization‐based computer‐aided design tool for the integrated DigSS (iDigSS) is created. Experimental validation shows that the iDigSS distinguishes a target strain‐field profile from 35 of 36 theoretically distinguishable profiles without requiring signal processing. Human subject trials demonstrate the system's ability to differentiate a specific shoulder movement from five others and to wirelessly record wrist extension counts and durations. 

Capillaric strain sensors (CSSs) operate based on the volume expansion of closed microfluidic networks in response to linear strain and have tunable directionality and sensitivity in a large range. The unique advantages of CSSs for integrated sensor development can simplify the human movement recognition by eliminating the need for intensive computational power and reliance on machine learning algorithms. We borrowed strategies from electrical digital circuits for the integration of CSSs in OR and AND configurations. We have fabricated devices according to these strategies. To validate their functionality, we first performed tests on a benchtop model. We have mapped the strain field on the sensors using digital image correlation and used it in combination with a mathematical procedure that we have developed to accurately predict the response of the integrated CSSs (iCSSs). Finally, we have skin mounted the iCSS patches (2 × 2 cm 2 ) and conducted tests on a human subject. The results demonstrate that skin-strain-field mapping will be an enabling tool for iCSS design toward the recognition of human movements. 

Abstract Microinjection is an essential process in genetic engineering that is used to deliver genetic materials into various biological specimens. Considering the high-throughput requirement for microinjection applications ranging from gene editing to cell therapies, there is a need for an automated, highly parallelized, reproducible, and easy-to-use microinjection strategy. Here we report an on-chip, microfluidic microinjection module designed for compatibility with microfluidic large-scale integration technology that can be fabricated via standard, multilayer soft lithography techniques. The needle-on-chip (NOC) module consists of a two-layer polydimethylsiloxane-based microfluidic module whose puncture and injection operations are reliant solely on Quake valve actuation. As a proof-of-concept, we designed a NOC module to conduct the microinjection of a common genetics model organism, Caenorhabditis elegans ( C. elegans ). The NOC design was analyzed using finite element method simulations for a large range of practically viable geometrical parameters. The computational results suggested that a slight lateral offset (>10 μ m) of the control channel is sufficient for a successful NOC operation with a large fabrication tolerance (50 μ m, 50% channel width). To demonstrate proof-of-concept, the microinjection platform was fabricated and utilized to perform a successful injection of a tracer dye into C. elegans .