Potentiometric textile-based pH sensor

Determining the pH of sweat provides valuable information for athletes and patient monitoring. This work presents a textile-based, highly sensitive pH sensor for pH determination. Three conductive fabrics (Argenmesh, Ristop silver and Sstainless steel mesh (SSM)) were modified with a pH sensitive electrodeposited iridium oxide film (EIROF). The three electrodeposited fabrics were characterized by impedance measurements. The stainless steel mesh showed the best sensitivity to pH changes and therefore was selected for further experiments. Two configurations of this fabric were evaluated, looking for improvement in pH sensitivity and temperature dependence. The best result was obtained with the configuration that maximizes the contact surface between the stainless steel fibers, showing an error of 0.15% in the pH measurement of a buffer solution. This configuration was also used to perform in vivo measurements, obtaining an error of 4% when compared to the measurements performed with a commercial pH test strip. The implementation of sensor into textiles brings some advantages such as comfort, biocompatibility and washability, among others; making the future incorporation of a sensor into a garment very possible.Fil: Zamora, Martín Lucas. Universidad Nacional de Tucumán. Facultad de Ciencias Exactas y Tecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto Superior de Investigaciones Biológicas. Universidad Nacional de Tucumán. Instituto Superior de Investigaciones Biológicas; ArgentinaFil: Domínguez, Juan Martín. Universidad Nacional de Tucumán. Facultad de Ciencias Exactas y Tecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto Superior de Investigaciones Biológicas. Universidad Nacional de Tucumán. Instituto Superior de Investigaciones Biológicas; ArgentinaFil: Trujillo, Ricardo Matias. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto Superior de Investigaciones Biológicas. Universidad Nacional de Tucumán. Instituto Superior de Investigaciones Biológicas; Argentina. Universidad Nacional de Tucumán. Facultad de Ciencias Exactas y Tecnología; ArgentinaFil: Goy, Carla Belen. Universidad Nacional de Tucumán. Facultad de Ciencias Exactas y Tecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto Superior de Investigaciones Biológicas. Universidad Nacional de Tucumán. Instituto Superior de Investigaciones Biológicas; ArgentinaFil: Sanchez, Maria Alejandra. Universidad Nacional de Tucumán. Facultad de Ciencias Exactas y Tecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto Superior de Investigaciones Biológicas. Universidad Nacional de Tucumán. Instituto Superior de Investigaciones Biológicas; ArgentinaFil: Madrid, Rossana Elena. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto Superior de Investigaciones Biológicas. Universidad Nacional de Tucumán. Instituto Superior de Investigaciones Biológicas; Argentina. Universidad Nacional de Tucumán. Facultad de Ciencias Exactas y Tecnología; Argentin

Design and Validation of a Wearable, Continuous, and Non-Invasive Hydration Monitor that uses Ultrasonic Pulses to Detect Changes in Tissue Hydration Status

Chronic dehydration is an endemic problem for many population groups. Current methods of monitoring hydration status are invasive, time consuming, cannot be performed while exercising, and require lab resources. A proposed solution is a wearable, continuous, and non-invasive device that uses harm-free ultrasonic pulses to detect changes in tissue hydration status over time. Customer and engineering requirements were defined and used to guide the design process. Literature reviews were performed to identify essential information on dehydration, assess current methods, discover state of the art devices, and describe ultrasonic theory. Market research was performed to identify athletes as the target population group. An adjustable elastic nylon bicep band prototype was manufactured and the integration of more advanced components was proposed. The theoretical signal processing method used to detect hydration status was validated through initial tests with a prototype electrical system composed of a Teensy 3.1 board, two 18 kHz piezoceramic disc elements, and an Arduino/LabVIEW interface. Tests with aluminum, rubber, and sponge materials were performed to compare the signal response to propagation through materials with different acoustic properties and water contents. Finally, tests performed with dehydrated bovine muscle tissue revealed a statistically significant difference between hydrated and dehydrated tissue, a promising indication for future device refinement

Towards Real-Time Predictive Health Monitoring from Sweat Wearables

Sweat biomarkers offer valuable insights into the health conditions of individuals. Despite the recent advances in wearable technologies that enable real-time monitoring of sweat biomarkers, their potential to infer health conditions remains largely unexplored. This thesis, conducted as part of the WeCare project, leverages machine learning (ML) models including deep neural networks (DNNs), for real-time predictive health monitoring using these sweat biomarkers. Our research primarily focuses on predicting physiological states such as hydration status and core body temperature during exercise. One version of the wearable sweat patch developed by our WeCare partner at the Instituto de Microelectrónica de Barcelona (IMB-CNM) uses ion-sensitive field-effect transistors (ISFETs). While these sensors are sensitive, lightweight, and cost-effective, they are prone to sensor drift. Previous work shows that DNNs are promising for predicting ionic concentration from ISFET sensor readings with the presence of sensor drift. However, training DNNs requires large labeled datasets that are difficult to collect. To address this, we first construct a physical model for ISFET sensors that simulates sensor readings and takes into account sensor drift. We then train an end-to-end prediction neural network as a sensor calibration tool on these simulated readings. Our prediction network outperforms two manual calibration methods in predicting sodium concentration from uncalibrated real-world sodium ISFET readings, suggesting its promise for future calibration of wearable patches using ISFETs. Next, we carry out a study aimed at designing personalized hydration strategies based on noninvasive biomarkers. We examine the feasibility of using ML models to predict the hydration status of an athlete using physiological and sweat biomarker recordings collected from a subject during a set of indoor cycling sessions supervised by the Lausanne University Hospital (CHUV). Because the wearable sweat patches were still under development at that stage, absorbent patches were used for sweat sample collection. We also compared the performance of nonlinear ML models with the linear model on this predictive task. This investigation provides insights for future hydration status predictions using ML models on sweat biomarker data collected from wearable sweat patches. Finally, following the available printed sensor patch developed by the Soft Transducers Lab at École Polytechnique Fédérale de Lausanne (EPFL-LMTS), we determine the prediction accuracy of core body temperature during exercise using real-time sweat biomarkers measured with this wearable prototype and with the addition of other biomarker data collected with commercial devices. All experimental sessions were conducted at CHUV. Our results indicate that DNNs can accurately and continuously predict core body temperature solely from sweat biomarker data, specifically sweat sodium and potassium concentrations collected from the wearable patch. Moreover, our analysis of the collected sweat biomarker data shows that they can be used to predict future core body temperature values. Our findings highlight the potential of integrating advanced predictive models with wearable sweat patches for real-time and accurate prediction of physiological states

Development of electrochemical biosensors and sensors for the determination of interest analytes

Se han puesto a punto varios métodos electroquímicos para la determinación de varios analitos de interés, como lactato, cloruro, bromuro y yoduro utilizando sistemas electródicos serigrafiados (SPEs). Su bajo costo, tamaño pequeño, portabilidad para aplicaciones in situ, así como su facilidad de modificación, les confiere gran versatilidad, para ser usados como transductores en sensores y biosensores electroquímicos con gran precisión y sensibilidad en distintas matrices. Concretamente, se ha desarrollado un biosensor amperométrico para la determinación de lactato, basado en la utilización de la enzima lactato oxidasa. El biosensor ha permitido la determinación de este ácido orgánico en líquidos biológicos como saliva y sudor y en productos alimentarios como vinos. Se incluyen también estudios de los mecanismos de inhibición de las enzimas utilizadas en los biosensores. También se han puesto a punto sensores para la determinación de haluros, que han mostrado su aplicabilidad para su cuantificación en varios tipos de muestras

Embroidered textile frequency-splitting sensor based on stepped-impedance resonators

©2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.This paper presents an embroidered textile frequency-splitting microwave sensor based on a pair of identical stepped-impedance resonators (SIRs) loading a microstrip transmission line. The sensor is implemented by means of conductive threads. The sensing region of the proposed structure is the capacitive square patch of one of the SIRs. If such region is kept unaltered, the structure is symmetric, and the frequency response (transmission coefficient) exhibits a single transmission zero. However, if symmetry is broken (e.g., through liquid absorption in the sensing region), the frequency response of the proposed sensor exhibits two transmission zeros (frequency splitting). The difference (in frequency and magnitude) between such zeros (or notches) is intimately related to the dielectric properties of the absorbed liquids to be sensed / detected. The proposed sensing structure is applied to the detection of deionized (DI) water absorption, and to the quantification of the number of DI water drops. The maximum measured sensitivity is found to be 2.70 MHz /µl and 0.03 dB /µl for the incremental frequency and incremental magnitude of the notches.This work was supported by MICIIN-Spain (projects PID2019-103904RB-I00, TEC2016-79465-R, and PDC2021-121085-I00),Generalitat de Catalunya (project 2017SGR-1159), Institució Catalana de Recerca i Estudis Avançats (who awarded Ferran Martín), and by FEDER funds.Peer ReviewedPostprint (author's final draft

A comprehensive survey of wireless body area networks on PHY, MAC, and network layers solutions

Recent advances in microelectronics and integrated circuits, system-on-chip design, wireless communication and intelligent low-power sensors have allowed the realization of a Wireless Body Area Network (WBAN). A WBAN is a collection of low-power, miniaturized, invasive/non-invasive lightweight wireless sensor nodes that monitor the human body functions and the surrounding environment. In addition, it supports a number of innovative and interesting applications such as ubiquitous healthcare, entertainment, interactive gaming, and military applications. In this paper, the fundamental mechanisms of WBAN including architecture and topology, wireless implant communication, low-power Medium Access Control (MAC) and routing protocols are reviewed. A comprehensive study of the proposed technologies for WBAN at Physical (PHY), MAC, and Network layers is presented and many useful solutions are discussed for each layer. Finally, numerous WBAN applications are highlighted

Review—Lab-in-a-Mouth and Advanced Point-of-Care Sensing Systems: Detecting Bioinformation from the Oral Cavity and Saliva

Cavitas sensors and point-of-need sensors capable of providing physical and biochemical information from the oral cavity and saliva have attracted great attention because they offer remarkable advantages for noninvasive sensing systems. Herein, we introduce the basic anatomy and physiology of important body cavities to understand their characteristics as it is a pivotal foundation for the successful development of in-mouth devices. Next, the advanced development in lab-in-a-mouth sensors and point-of-need sensors for analyzing saliva are explained. In addition, we discuss the integrations of artificial intelligence and electronic technologies in smart sensing networks for healthcare systems. This review ends with a discussion of the challenges, future research trends, and opportunities in relevant disciplines. Mouthguard-based sensors and conventional salivary sensing devices will continue to be significant for the progress in the next-generation sensing technologies and smart healthcare systems.ope

Electrochemical biosensors based on nanomodified screen-printed electrodes: Recent applications in clinical analysis

This review addresses recent advances in the development of screen-printed electrode based biosensors modified with different nanomaterials such as carbon nanotubes, graphene, metallic nanoparticles as gold, silver and magnetic nanoparticles, and mediator nanoparticles (Prussian Blue, Cobalt Phthalocyanine, etc.), coupled with biological recognition elements such as enzymes, antibodies, DNA and aptamers to obtain probes with improved analytical features. Examples of clinical applications are illustrated, together with examples of paper-based electrochemical devices, of multiple detections using arrays of screen printed electrodes, and of the most recent developments in the field of wearable biosensors. Also the use of smartphones as final detectors is briefly depicted. © 2016 Elsevier B.V

Development, Optimisation and Applications of Screen-Printed Electrochemical Sensors

The sustainability of healthcare delivery depends on the adoption of new low-cost devices to support the transition of services from centralised generic models to home and community-based care models, through which the patient status can be monitored remotely. Easily accessible body fluids (like saliva, sweat and interstitial fluids) represent alternative sampling media to blood that in principle can be conveniently analysed through wearable sensors. For instance, continuous monitoring of pH in saliva would allow a better clinical management of pathologies that alter acid contents within the mouth. Similarly, the real-time tracking of sodium levels in sweat and other body fluids can assist clinicians in the diagnosis and treatment of Cystic Fibrosis. Furthermore, athletes could reap many benefits from an optimal strategy for personalised rehydration, which might be informed by continuously measuring the amount of minerals lost in sweat. Electrochemical sensors based on the combination of screen-printed working and solid-contact reference electrodes are versatile and low-cost tools that are effective in facing many of the challenges in current sensing technology. They can be readily adapted for the detection of several ionic species, and in this thesis, as an example, two electrochemical platforms to monitor pH in saliva and sodium in sweat are going to be presented. The final devices are minimally-invasive and wearable, with a compact format due to the integration of miniaturised solid state ion-selective and reference electrodes. The technological advancements developed for their realisation are significant contributions for the more flexible design of novel miniaturised sensors for remote monitoring in general. Future developments of this technology could be pivotal for realising devices for applications as diverse as sensors integrated into fabrics for personal health monitoring, or autonomous sensors deployed in rivers and lakes for monitoring water quality