Assessing the performance of a robust multiparametric wearable patch integrating silicon-based sensors for real-time continuous monitoring of sweat biomarkers.

The development of wearable devices for sweat analysis has experienced significant growth in the last two decades, being the main focus the monitoring of athletes health during workouts. One of the main challenges of these approaches has been to attain the continuous monitoring of sweat for time periods over 1 h. This is the main challenge addressed in this work by designing an analytical platform that combines the high performance of potentiometric sensors and a fluidic structure made of a plastic fabric into a multiplexed wearable device. The platform comprises Ion-Sensitive Field-Effect Transistors (ISFETs) manufactured on silicon, a tailor-made solid-state reference electrode, and a temperature sensor integrated into a patch-like polymeric substrate, together with the component that easily collects and drives samples under continuous capillary flow to the sensor areas. ISFET sensors for measuring pH, sodium, and potassium ions were fully characterized in artificial sweat solutions, providing reproducible and stable responses. Then, the real-time and continuous monitoring of the biomarkers in sweat with the wearable platform was assessed by comparing the ISFETs responses recorded during an 85-min continuous exercise session with the concentration values measured using commercial Ion-Selective Electrodes (ISEs) in samples collected at certain times during the session. The developed sensing platform enables the continuous monitoring of biomarkers and facilitates the study of the effects of various real working conditions, such as cycling power and skin temperature, on the target biomarker concentration levels.

Digital manufacturing of personalised footwear with embedded sensors.

The strong clinical demand for more accurate and personalized health monitoring technologies has called for the development of additively manufactured wearable devices. While the materials palette for additive manufacturing continues to expand, the integration of materials, designs and digital fabrication methods in a unified workflow remains challenging. In this work, a 3D printing platform is proposed for the integrated fabrication of silicone-based soft wearables with embedded piezoresistive sensors. Silicone-based inks containing cellulose nanocrystals and/or carbon black fillers were thoroughly designed and used for the direct ink writing of a shoe insole demonstrator with encapsulated sensors capable of measuring both normal and shear forces. By fine-tuning the material properties to the expected plantar pressures, the patient-customized shoe insole was fully 3D printed at room temperature to measure in-situ gait forces during physical activity. Moreover, the digitized approach allows for rapid adaptation of the sensor layout to meet specific user needs and thereby fabricate improved insoles in multiple quick iterations. The developed materials and workflow enable a new generation of fully 3D printed soft electronic devices for health monitoring.

MEMS inductor fabrication and emerging applications in power electronics and neurotechnologies.

MEMS inductors are used in a wide range of applications in micro- and nanotechnology, including RF MEMS, sensors, power electronics, and Bio-MEMS. Fabrication technologies set the boundary conditions for inductor design and their electrical and mechanical performance. This review provides a comprehensive overview of state-of-the-art MEMS technologies for inductor fabrication, presents recent advances in 3D additive fabrication technologies, and discusses the challenges and opportunities of MEMS inductors for two emerging applications, namely, integrated power electronics and neurotechnologies. Among the four top-down MEMS fabrication approaches, 3D surface micromachining and through-substrate-via (TSV) fabrication technology have been intensively studied to fabricate 3D inductors such as solenoid and toroid in-substrate TSV inductors. While 3D inductors are preferred for their high-quality factor, high power density, and low parasitic capacitance, in-substrate TSV inductors offer an additional unique advantage for 3D system integration and efficient thermal dissipation. These features make in-substrate TSV inductors promising to achieve the ultimate goal of monolithically integrated power converters. From another perspective, 3D bottom-up additive techniques such as ice lithography have great potential for fabricating inductors with geometries and specifications that are very challenging to achieve with established MEMS technologies. Finally, we discuss inspiring and emerging research opportunities for MEMS inductors.

Inkjet-Printed Membrane for a Capacitive Acoustic Sensor: Development and Characterization Using Laser Vibrometer.

This paper describes the fabrication process and the method to determine the membrane tension and defects of an inkjet-printed circular diaphragm. The membrane tension is an important parameter to design and fabricate an acoustic sensor and resonator with the highest sensitivity and selectivity over a determined range of frequency. During this work, the diaphragms are fabricated by inkjet printing of conductive silver ink on pre-strained Mylar thin films, and the membrane tension is determined using the resonant frequency obtained from its measured surface velocity response to an acoustic excitation. The membrane is excited by an acoustic pressure generated by a loudspeaker, and its displacement (response) is acquired using a laser Doppler vibrometer (LDV). The response of the fabricated membrane demonstrates good correlation with the numerical result. However, the inkjet-printed membrane exhibits undesired peaks, which appeared to be due to defects at their boundaries as observed from the scanning mode of LDV.

Fabrication of capacitive acoustic resonators combining 3D printing and 2D inkjet printing techniques.

A capacitive acoustic resonator developed by combining three-dimensional (3D) printing and two-dimensional (2D) printed electronics technique is described. During this work, a patterned bottom structure with rigid backplate and cavity is fabricated directly by a 3D printing method, and then a direct write inkjet printing technique has been employed to print a silver conductive layer. A novel approach has been used to fabricate a diaphragm for the acoustic sensor as well, where the conductive layer is inkjet-printed on a pre-stressed thin organic film. After assembly, the resulting structure contains an electrically conductive diaphragm positioned at a distance from a fixed bottom electrode separated by a spacer. Measurements confirm that the transducer acts as capacitor. The deflection of the diaphragm in response to the incident acoustic single was observed by a laser Doppler vibrometer and the corresponding change of capacitance has been calculated, which is then compared with the numerical result. Observation confirms that the device performs as a resonator and provides adequate sensitivity and selectivity at its resonance frequency.

Optimization of capacitive acoustic resonant sensor using numerical simulation and design of experiment.

Optimization of the acoustic resonant sensor requires a clear understanding of how the output responses of the sensor are affected by the variation of different factors. During this work, output responses of a capacitive acoustic transducer, such as membrane displacement, quality factor, and capacitance variation, are considered to evaluate the sensor design. The six device parameters taken into consideration are membrane radius, backplate radius, cavity height, air gap, membrane tension, and membrane thickness. The effects of factors on the output responses of the transducer are investigated using an integrated methodology that combines numerical simulation and design of experiments (DOE). A series of numerical experiments are conducted to obtain output responses for different combinations of device parameters using finite element methods (FEM). Response surface method is used to identify the significant factors and to develop the empirical models for the output responses. Finally, these results are utilized to calculate the optimum device parameters using multi-criteria optimization with desirability function. Thereafter, the validating experiments are designed and deployed using the numerical simulation to crosscheck the responses.