Redox-Concatenated Aptamer Integrated Skin Mimicking Electrochemical Patch for Noninvasive Detection of Cortisol

This research focuses on developing and validating a wearable electrochemical biosensor called the concatenated aptamer integrated skin patch, also known as the Captain Patch. The main objective is to detect cortisol levels in sweat, which can provide valuable insights into an individual's health. The biosensor utilizes a corrugated surface that mimics the skin, allowing for better attachment and an improved electrochemical performance. The study demonstrates the successful application of Captain Patch on the human body by using artificially spiked sweat samples. The results indicate good measurement accuracy and conformity when the patch is worn on the body. However, for long-term usage, the patch needs to be changed every 3-4 h or worn three times a day to enable monitoring of cortisol levels. Despite the need for frequent patch changes, the cost-effectiveness and ease of operation make these skin patches suitable for longitudinal cortisol monitoring and other sweat analytes. By customization of the biorecognition probe, the developed biowearable can be used to monitor a variety of vital biomarkers. Overall, Captain Patch, with its capability of detecting specific health markers such as cortisol, hints at the future potential of wearables to offer valuable data on various other biomarkers. Our approach presents the first step in integrating a cost-effective wearable electrochemical patch integrated with a redox-concatenated aptamer for noninvasive biomarker detection. This personalized approach to monitoring can lead to improved patient outcomes and increased patient engagement in managing their health.

Ultra-Sensitive and Stable Multiplexed Biosensors Array in Fully Printed and Integrated Platforms for Reliable Perspiration Analysis

Electrochemical biosensors have emerged as one of the promising tools for tracking human body physiological dynamics via non-invasive perspiration analysis. However, it remains a key challenge to integrate multiplexed sensors in a highly controllable and reproducible manner to achieve long-term reliable biosensing, especially on flexible platforms. Herein, a fully inkjet printed and integrated multiplexed biosensing patch with remarkably high stability and sensitivity is reported for the first time. These desirable characteristics are enabled by the unique interpenetrating interface design and precise control over active materials mass loading, owing to the optimized ink formulations and droplet-assisted printing processes. The sensors deliver sensitivities of 313.28 µA mm-1 cm-2 for glucose and 0.87 µA mm-1 cm-2 for alcohol sensing with minimal drift over 30 h, which are among the best in the literature. The integrated patch can be used for reliable and wireless diet monitoring or medical intervention via epidermal analysis and would inspire the advances of wearable devices for intelligent healthcare applications.

Wearable Microneedle Patch for Colorimetric Detection of Multiple Signature Biomarkers in vivo Toward Diabetic Diagnosis

Type 2 diabetes is rapidly emerging as a global public health problem. While blood glucose monitoring has been the primary method of managing diabetes for decades, the increasing global prevalence of the disease suggests that there might be a need to identify additional biomarkers for a more precise early diagnosis. Herein, a microneedle patch based wearable sensor is developed for the purpose of diabetic diagnosis. Utilizing methacrylic acid modified gelatin and polyvinyl alcohol in the fabrication of microneedles has improved their mechanical properties for skin penetration and increased swelling capacity for interstitial fluid extraction, thanks to the double crosslinking mechanism. The fabricated microneedles are further integrated with test paper functionalized with enzyme and dye molecules to detect multiple signature biomarkers of diabetes in vivo through a colorimetric reaction. Such a wearable microneedle patch  holds significant promise for the real-time monitoring of various biomarkers related to chronic diseases and aging.

A Comparison of Normalization Techniques for Individual Baseline-Free Estimation of Absolute Hypovolemic Status Using a Porcine Model

Hypovolemic shock is one of the leading causes of death in the military. The current methods of assessing hypovolemia in field settings rely on a clinician assessment of vital signs, which is an unreliable assessment of hypovolemia severity. These methods often detect hypovolemia when interventional methods are ineffective. Therefore, there is a need to develop real-time sensing methods for the early detection of hypovolemia. Previously, our group developed a random-forest model that successfully estimated absolute blood-volume status (ABVS) from noninvasive wearable sensor data for a porcine model (n = 6). However, this model required normalizing ABVS data using individual baseline data, which may not be present in crisis situations where a wearable sensor might be placed on a patient by the attending clinician. We address this barrier by examining seven individual baseline-free normalization techniques. Using a feature-specific global mean from the ABVS and an external dataset for normalization demonstrated similar performance metrics compared to no normalization (normalization: R2 = 0.82 ± 0.025|0.80 ± 0.032, AUC = 0.86 ± 5.5 × 10-3|0.86 ± 0.013, RMSE = 28.30 ± 0.63%|27.68 ± 0.80%; no normalization: R2 = 0.81 ± 0.045, AUC = 0.86 ± 8.9 × 10-3, RMSE = 28.89 ± 0.84%). This demonstrates that normalization may not be required and develops a foundation for individual baseline-free ABVS prediction.

A 3D-Printed Piezoelectric Microdevice for Human Energy Harvesting for Wearable Biosensors

The human body is a source of multiple types of energy, such as mechanical, thermal and biochemical, which can be scavenged through appropriate technological means. Mechanical vibrations originating from contraction and expansion of the radial artery represent a reliable source of displacement to be picked up and exploited by a harvester. The continuous monitoring of physiological biomarkers is an essential part of the timely and accurate diagnosis of a disease with subsequent medical treatment, and wearable biosensors are increasingly utilized for biomedical data acquisition of important biomarkers. However, they rely on batteries and their replacement introduces a discontinuity in measured signals, which could be critical for the patients and also causes discomfort. In the present work, the research into a novel 3D-printed wearable energy harvesting platform for scavenging energy from arterial pulsations via a piezoelectric material is described. An elastic thermoplastic polyurethane (TPU) film, which forms an air chamber between the skin and the piezoelectric disc electrode, was introduced to provide better adsorption to the skin, prevent damage to the piezoelectric disc and electrically isolate components in the platform from the human body. Computational fluid dynamics in the framework of COMSOL Multiphysics 6.1 software was employed to perform a series of coupled time-varying simulations of the interaction among a number of associated physical phenomena. The mathematical model of the harvester was investigated computationally, and quantification of the output energy and power parameters was used for comparisons. A prototype wearable platform enclosure was designed and manufactured using fused filament fabrication (FFF). The influence of the piezoelectric disc material and its diameter on the electrical output were studied and various geometrical parameters of the enclosure and the TPU film were optimized based on theoretical and empirical data. Physiological data, such as interdependency between the harvester skin fit and voltage output, were obtained.

Microfluidic-Based Non-Invasive Wearable Biosensors for Real-Time Monitoring of Sweat Biomarkers

Wearable biosensors are attracting great interest thanks to their high potential for providing clinical-diagnostic information in real time, exploiting non-invasive sampling of biofluids. In this context, sweat has been demonstrated to contain physiologically relevant biomarkers, even if it has not been exhaustively exploited till now. This biofluid has started to gain attention thanks to the applications offered by wearable biosensors, as it is easily collectable and can be used for continuous monitoring of some parameters. Several studies have reported electrochemical and optical biosensing strategies integrated with flexible, biocompatible, and innovative materials as platforms for biospecific recognition reactions. Furthermore, sampling systems as well as the transport of fluids by microfluidics have been implemented into portable and compact biosensors to improve the wearability of the overall analytical device. In this review, we report and discuss recent pioneering works about the development of sweat sensing technologies, focusing on opportunities and open issues that can be decisive for their applications in routine-personalized healthcare practices.

The 3D Printing of Nanocomposites for Wearable Biosensors: Recent Advances, Challenges, and Prospects

Notably, 3D-printed flexible and wearable biosensors have immense potential to interact with the human body noninvasively for the real-time and continuous health monitoring of physiological parameters. This paper comprehensively reviews the progress in 3D-printed wearable biosensors. The review also explores the incorporation of nanocomposites in 3D printing for biosensors. A detailed analysis of various 3D printing processes for fabricating wearable biosensors is reported. Besides this, recent advances in various 3D-printed wearable biosensors platforms such as sweat sensors, glucose sensors, electrocardiography sensors, electroencephalography sensors, tactile sensors, wearable oximeters, tattoo sensors, and respiratory sensors are discussed. Furthermore, the challenges and prospects associated with 3D-printed wearable biosensors are presented. This review is an invaluable resource for engineers, researchers, and healthcare clinicians, providing insights into the advancements and capabilities of 3D printing in the wearable biosensor domain.

Human behavior recognition based on sparse transformer with channel attention mechanism

Human activity recognition (HAR) has recently become a popular research field in the wearable sensor technology scene. By analyzing the human behavior data, some disease risks or potential health issues can be detected, and patients' rehabilitation progress can be evaluated. With the excellent performance of Transformer in natural language processing and visual tasks, researchers have begun to focus on its application in time series. The Transformer model models long-term dependencies between sequences through self-attention mechanisms, capturing contextual information over extended periods. In this paper, we propose a hybrid model based on the channel attention mechanism and Transformer model to improve the feature representation ability of sensor-based HAR tasks. Extensive experiments were conducted on three public HAR datasets, and the results show that our network achieved accuracies of 98.10%, 97.21%, and 98.82% on the HARTH, PAMAP2, and UCI-HAR datasets, respectively, The overall performance is at the level of the most advanced methods.

Advanced Textile-Based Wearable Biosensors for Healthcare Monitoring

With the innovation of wearable technology and the rapid development of biosensors, wearable biosensors based on flexible textile materials have become a hot topic. Such textile-based wearable biosensors promote the development of health monitoring, motion detection and medical management, and they have become an important support tool for human healthcare monitoring. Textile-based wearable biosensors not only non-invasively monitor various physiological indicators of the human body in real time, but they also provide accurate feedback of individual health information. This review examines the recent research progress of fabric-based wearable biosensors. Moreover, materials, detection principles and fabrication methods for textile-based wearable biosensors are introduced. In addition, the applications of biosensors in monitoring vital signs and detecting body fluids are also presented. Finally, we also discuss several challenges faced by textile-based wearable biosensors and the direction of future development.

The time is ripe for the renaissance of autism treatments: evidence from clinical practitioners

Introduction

Recent changes in diagnostics criteria have contributed to the broadening of the autism spectrum disorders and left clinicians ill-equipped to treat the highly heterogeneous spectrum that now includes toddlers and children with sensory and motor issues.

Methods

To uncover the clinicians' critical needs in the autism space, we conducted surveys designed collaboratively with the clinicians themselves. Board Certified Behavioral Analysts (BCBAs) and developmental model (DM) clinicians obtained permission from their accrediting boards and designed surveys to assess needs and preferences in their corresponding fields.

Results

92.6% of BCBAs are open to diversified treatment combining aspects of multiple disciplines; 82.7% of DMs also favor this diversification with 21.8% valuing BCBA-input and 40.6% neurologists-input; 85.9% of BCBAs and 85.3% of DMs advocate the use of wearables to objectively track nuanced behaviors in social exchange; 76.9% of BCBAs and 57.0% DMs feel they would benefit from augmenting their knowledge about the nervous systems of Autism (neuroscience research) to enhance treatment and planning programs; 50.0% of BCBAs feel they can benefit for more training to teach parents.

Discussion

Two complementary philosophies are converging to a more collaborative, integrative approach favoring scalable digital technologies and neuroscience. Autism practitioners seem ready to embrace the Digital-Neuroscience Revolutions under a new cooperative model.

Recent Advances in Cardiovascular Disease Biosensors and Monitoring Technologies

Cardiovascular disease (CVD) causes significant mortality and remains the leading cause of death globally. Thus, to reduce mortality, early diagnosis by measurement of cardiac biomarkers and heartbeat signals presents fundamental importance. Traditional CVD examination requires bulky hospital instruments to conduct electrocardiography recording and immunoassay analysis, which are both time-consuming and inconvenient. Recently, development of biosensing technologies for rapid CVD marker screening attracted great attention. Thanks to the advancement in nanotechnology and bioelectronics, novel biosensor platforms are developed to achieve rapid detection, accurate quantification, and continuous monitoring throughout disease progression. A variety of sensing methodologies using chemical, electrochemical, optical, and electromechanical means are explored. This review first discusses the prevalence and common categories of CVD. Then, heartbeat signals and cardiac blood-based biomarkers that are widely employed in clinic, as well as their utilizations for disease prognosis, are summarized. Emerging CVD wearable and implantable biosensors and monitoring bioelectronics, allowing these cardiac markers to be continuously measured are introduced. Finally, comparisons of the pros and cons of these biosensing devices along with perspectives on future CVD biosensor research are presented.

Biocompatible and Long-Term Monitoring Strategies of Wearable, Ingestible and Implantable Biosensors: Reform the Next Generation Healthcare

Sensors enable the detection of physiological indicators and pathological markers to assist in the diagnosis, treatment, and long-term monitoring of diseases, in addition to playing an essential role in the observation and evaluation of physiological activities. The development of modern medical activities cannot be separated from the precise detection, reliable acquisition, and intelligent analysis of human body information. Therefore, sensors have become the core of new-generation health technologies along with the Internet of Things (IoTs) and artificial intelligence (AI). Previous research on the sensing of human information has conferred many superior properties on sensors, of which biocompatibility is one of the most important. Recently, biocompatible biosensors have developed rapidly to provide the possibility for the long-term and in-situ monitoring of physiological information. In this review, we summarize the ideal features and engineering realization strategies of three different types of biocompatible biosensors, including wearable, ingestible, and implantable sensors from the level of sensor designing and application. Additionally, the detection targets of the biosensors are further divided into vital life parameters (e.g., body temperature, heart rate, blood pressure, and respiratory rate), biochemical indicators, as well as physical and physiological parameters based on the clinical needs. In this review, starting from the emerging concept of next-generation diagnostics and healthcare technologies, we discuss how biocompatible sensors revolutionize the state-of-art healthcare system unprecedentedly, as well as the challenges and opportunities faced in the future development of biocompatible health sensors.

Wearable Biosensors in Congenital Heart Disease: Needs to Advance the Field

Traditional measures of clinical status and physiology have generally been based in health care settings, episodic, short in duration, and performed at rest. Wearable biosensors provide an opportunity to obtain continuous non-invasive physiologic data from patients with congenital heart disease (CHD) in the real-world setting, over longer durations, and across varying levels of activity. However, there are significant technical limitations to the use of wearable biosensors in CHD. Here, we review current applications of wearable biosensors in CHD; how clinical and research uses of wearable biosensors must consider various CHD physiologies; the technical challenges in developing wearable biosensors for CHD; and special considerations for digital biomarkers in CHD.

Spatiotemporal Modeling of Grip Forces Captures Proficiency in Manual Robot Control

New technologies for monitoring grip forces during hand and finger movements in non-standard task contexts have provided unprecedented functional insights into somatosensory cognition. Somatosensory cognition is the basis of our ability to manipulate and transform objects of the physical world and to grasp them with the right amount of force. In previous work, the wireless tracking of grip-force signals recorded from biosensors in the palm of the human hand has permitted us to unravel some of the functional synergies that underlie perceptual and motor learning under conditions of non-standard and essentially unreliable sensory input. This paper builds on this previous work and discusses further, functionally motivated, analyses of individual grip-force data in manual robot control. Grip forces were recorded from various loci in the dominant and non-dominant hands of individuals with wearable wireless sensor technology. Statistical analyses bring to the fore skill-specific temporal variations in thousands of grip forces of a complete novice and a highly proficient expert in manual robot control. A brain-inspired neural network model that uses the output metric of a self-organizing pap with unsupervised winner-take-all learning was run on the sensor output from both hands of each user. The neural network metric expresses the difference between an input representation and its model representation at any given moment in time and reliably captures the differences between novice and expert performance in terms of grip-force variability.Functionally motivated spatiotemporal analysis of individual average grip forces, computed for time windows of constant size in the output of a restricted amount of task-relevant sensors in the dominant (preferred) hand, reveal finger-specific synergies reflecting robotic task skill. The analyses lead the way towards grip-force monitoring in real time. This will permit tracking task skill evolution in trainees, or identify individual proficiency levels in human robot-interaction, which represents unprecedented challenges for perceptual and motor adaptation in environmental contexts of high sensory uncertainty. Cross-disciplinary insights from systems neuroscience and cognitive behavioral science, and the predictive modeling of operator skills using parsimonious Artificial Intelligence (AI), will contribute towards improving the outcome of new types of surgery, in particular the single-port approaches such as NOTES (Natural Orifice Transluminal Endoscopic Surgery) and SILS (Single-Incision Laparoscopic Surgery).

Recent Advances in Wearable Biosensors for Non-Invasive Detection of Human Lactate

Lactate, a crucial product of the anaerobic metabolism of carbohydrates in the human body, is of enormous significance in the diagnosis and treatment of diseases and scientific exercise management. The level of lactate in the bio-fluid is a crucial health indicator because it is related to diseases, such as hypoxia, metabolic disorders, renal failure, heart failure, and respiratory failure. For critically ill patients and those who need to regularly control lactate levels, it is vital to develop a non-invasive wearable sensor to detect lactate levels in matrices other than blood. Due to its high sensitivity, high selectivity, low detection limit, simplicity of use, and ability to identify target molecules in the presence of interfering chemicals, biosensing is a potential analytical approach for lactate detection that has received increasing attention. Various types of wearable lactate biosensors are reviewed in this paper, along with their preparation, key properties, and commonly used flexible substrate materials including polydimethylsiloxane (PDMS), polyethylene terephthalate (PET), paper, and textiles. Key performance indicators, including sensitivity, linear detection range, and detection limit, are also compared. The challenges for future development are also summarized, along with some recommendations for the future development of lactate biosensors.

Prediction of Individual Dynamic Thermal Sensation in Subway Commute Using Smart Face Mask

Wearable sensors and machine learning algorithms are widely used for predicting an individual's thermal sensation. However, most of the studies are limited to controlled laboratory experiments with inconvenient wearable sensors without considering the dynamic behavior of ambient conditions. In this study, we focused on predicting individual dynamic thermal sensation based on physiological and psychological data. We designed a smart face mask that can measure skin temperature (SKT) and exhaled breath temperature (EBT) and is powered by a rechargeable battery. Real-time human experiments were performed in a subway cabin with twenty male students under natural conditions. The data were collected using a smartphone application, and we created features using the wavelet decomposition technique. The bagged tree algorithm was selected to train the individual model, which showed an overall accuracy and f-1 score of 98.14% and 96.33%, respectively. An individual's thermal sensation was significantly correlated with SKT, EBT, and associated features.

Recent Advances, Opportunities, and Challenges in Developing Nucleic Acid Integrated Wearable Biosensors for Expanding the Capabilities of Wearable Technologies in Health Monitoring

Wearable biosensors are becoming increasingly popular due to the rise in demand for non-invasive, real-time monitoring of health and personalized medicine. Traditionally, wearable biosensors have explored protein-based enzymatic and affinity-based detection strategies. However, in the past decade, with the success of nucleic acid-based point-of-care diagnostics, a paradigm shift has been observed in integrating nucleic acid-based assays into wearable sensors, offering better stability, enhanced analytical performance, and better clinical applicability. This narrative review builds upon the current state and advances in utilizing nucleic acid-based assays, including oligonucleotides, nucleic acid, aptamers, and CRISPR-Cas, in wearable biosensing. The review also discusses the three fundamental blocks, i.e., fabrication requirements, biomolecule integration, and transduction mechanism, for creating nucleic acid integrated wearable biosensors.

Airline Point-of-Care System on Seat Belt for Hybrid Physiological Signal Monitoring

With a focus on disease prevention and health promotion, a reactive and disease-centric healthcare system is revolutionized to a point-of-care model by the application of wearable devices. The convenience and low cost made it possible for long-term monitoring of health problems in long-distance traveling such as flights. While most of the existing health monitoring systems on aircrafts are limited for pilots, point-of-care systems provide choices for passengers to enjoy healthcare at the same level. Here in this paper, an airline point-of-care system containing hybrid electrocardiogram (ECG), breathing, and motion signals detection is proposed. At the same time, we propose the diagnosis of sleep apnea-hypopnea syndrome (SAHS) on flights as an application of this system to satisfy the inevitable demands for sleeping on long-haul flights. The hardware design includes ECG electrodes, flexible piezoelectric belts, and a control box, which enables the system to detect the original data of ECG, breathing, and motion signals. By processing these data with interval extraction-based feature selection method, the signals would be characterized and then provided for the long short-term memory recurrent neural network (LSTM-RNN) to classify the SAHS. Compared with other machine learning methods, our model shows high accuracy up to 84-85% with the lowest overfit problem, which proves its potential application in other related fields.

Wearable biosensors for human fatigue diagnosis: A review

Fatigue causes deleterious effects to physical and mental health of human being and may cause loss of lives. Therefore, the adverse effects of fatigue on individuals and the society are massive. With the ever-increasing frequency of overtraining among modern military and sports personnel, timely, portable and accurate fatigue diagnosis is essential to avoid fatigue-induced accidents. However, traditional detection methods require complex sample preparation and blood sampling processes, which cannot meet the timeliness and portability of fatigue diagnosis. With the development of flexible materials and biosensing technology, wearable biosensors have attracted increased attention to the researchers. Wearable biosensors collect biomarkers from noninvasive biofluids, such as sweat, saliva, and tears, followed by biosensing with the help of biosensing modules continuously and quantitatively. The detection signal can then be transmitted through wireless communication modules that constitute a method for real-time understanding of abnormality. Recent developments of wearable biosensors are focused on miniaturized wearable electrochemistry and optical biosensors for metabolites detection, of which, few have exhibited satisfactory results in medical diagnosis. However, detection performance limits the wide-range applicability of wearable fatigue diagnosis. In this article, the application of wearable biosensors in fatigue diagnosis has been discussed. In fact, exploration of the composition of different biofluids and their potential toward fatigue diagnosis have been discussed here for the very first time. Moreover, discussions regarding the current bottlenecks in wearable fatigue biosensors and the latest advancements in biochemical reaction and data communication modules have been incorporated herein. Finally, the main challenges and opportunities were discussed for wearable fatigue diagnosis in the future.

Wearable Sensors for the Detection of Biomarkers for Wound Infection

Infection represents a major complication that can affect wound healing in any type of wound, especially in chronic ones. There are currently certain limitations to the methods that are used for establishing a clinical diagnosis of wound infection. Thus, new, rapid and easy-to-use strategies for wound infection diagnosis need to be developed. To this aim, wearable sensors for infection diagnosis have been recently developed. These sensors are incorporated into the wound dressings that are used to treat and protect the wound, and are able to detect certain biomarkers that can be correlated with the presence of wound infection. Among these biomarkers, the most commonly used ones are pH and uric acid, but a plethora of others (lactic acid, oxygenation, inflammatory mediators, bacteria metabolites or bacteria) have also been detected using wearable sensors. In this work, an overview of the main types of wearable sensors for wound infection detection will be provided. These sensors will be divided into electrochemical, colorimetric and fluorimetric sensors and the examples will be presented and discussed comparatively.

A Colorimetric Dermal Tattoo Biosensor Fabricated by Microneedle Patch for Multiplexed Detection of Health-Related Biomarkers

Detection of biomarkers associated with body conditions provides in-depth healthcare information and benefits to disease management, where the key challenge is to develop a minimally invasive platform with the ability to directly detect multiple biomarkers in body fluid. Dermal tattoo biosensor holds the potential to simultaneously detect multiple health-related biomarkers in skin interstitial fluid because of the features of minimal invasion, easy operation, and equipment-free result reading. Herein, a colorimetric dermal tattoo biosensor fabricated by a four-area segmented microneedle patch is developed for multiplexed detection of health-related biomarkers. The biosensor exhibits color changes in response to the change of biomarker concentration (i.e., pH, glucose, uric acid, and temperature), which can be directly read by naked eyes or captured by a camera for semi-quantitative measurement. It is demonstrated that the colorimetric dermal tattoo biosensor can simultaneously detect multiple biomarkers in vitro, ex vivo, and in vivo, and monitor the changes of the biomarker concentration for at least 4 days, showing its great potential for long-term health monitoring.

Conducting Polymer-Reinforced Laser-Irradiated Graphene as a Heterostructured 3D Transducer for Flexible Skin Patch Biosensors

Flexible skin patch biosensors are promising for the noninvasive determination of physiological parameters in perspiration for fitness and health monitoring. However, various prerequisites need to be met for the development of such biosensors, including the creation of a flexible conductive platform, bending/contact stability, fast electrochemical kinetics, and immobilization of biomolecules. Here, we describe a conducting polymer-reinforced laser-irradiated graphene (LIG) network as a heterostructured three-dimensional (3D) transducer for flexible skin patch biosensors. LIG with a hierarchically interconnected graphene structure is geometrically patterned on polyimide via localized laser irradiation as a flexible conductive platform, which is then reinforced by poly(3,4-ethylenedioxythiophene) (PEDOT) as a conductive binder (PEDOT/LIG) with improved structural/contact stability and electrochemical kinetics. The interconnected pores of the reinforced PEDOT/LIG function as a 3D host matrix for high loading of "artificial" (Prussian blue, PB) and natural enzymes (lactate oxidase, LOx), forming a compact and heterostructured 3D transducer (LOx/PB-PEDOT/LIG) for lactate biosensing with excellent sensitivity (11.83 μA mM^-1). We demonstrated the fabrication of flexible skin patch biosensors comprising a custom-built integrated three-electrode system achieve amperometric detection of lactate in artificial sweat over a wide physiological linear range of 0-18 mM. The advantage of this facile and versatile transducer is further illustrated by the development of a folded 3D wristband lactate biosensor and a dual channel biosensors for simultaneous monitoring of lactate and glucose. This innovative design concept of a heterostructured transducer for flexible biosensors combined with a versatile fabrication approach could potentially drive the development of new wearable and skin-mountable biosensors for monitoring various physiological parameters in biofluids for noninvasive fitness and health management.

Lab under the Skin: Microneedle Based Wearable Devices

While the current smartwatches and cellphones can readily track mobility and vital signs, a new generation of wearable devices is rapidly developing to enable users to monitor their health parameters at the molecular level. Within this emerging class of wearables, microneedle-based transdermal sensors are in a prime position to play a key role in synergizing the significant advantages of dermal interstitial fluid (ISF) as a rich source of clinical indicators and painless skin pricking to allow the collection of real-time diagnostic information. While initial efforts of microneedle sensing focused on ISF extraction coupled with either on-chip analysis or off-chip instrumentation, the latest trend has been oriented toward assembling electrochemical biosensors on the tip of microneedles to allow direct continuous chemical measurements. In this context, significant advances have recently been made in exploiting microneedle-based devices for real-time monitoring of various metabolites, electrolytes, and therapeutics and toward the simultaneous multiplexed detection of key chemical markers; yet, there are several grand challenges that still exist. In this review, we outline current progress, recent trends, and new capabilities of microneedle-empowered sensors, along with the current unmet challenges and a future roadmap toward transforming the latest innovations in the field to commercial products.

Usability and Acceptance of Wearable Biosensors in Forensic Psychiatry: Cross-sectional Questionnaire Study

Background

The use of wearable biosensor devices for monitoring and coaching in forensic psychiatric settings yields high expectations for improved self-regulation of emotions and behavior in clients and staff members. More so, if clients have mild intellectual disabilities (IQ 50-85), they might benefit from these biosensors as they are easy to use in everyday life, which ensures that clients can practice with the devices in multiple stress and arousal-inducing situations. However, research on (continuous) use and acceptance of biosensors in forensic psychiatry for clients with mild intellectual disabilities and their caretakers is scarce. Although wearable biosensors show promise for health care, recent research showed that the acceptance and continuous use of wearable devices in consumers is not as was anticipated, probably due to low expectations.

Objective

The main goal of this study was to investigate the associations between and determinants of the expectation of usability, the actual experienced usability, and the intention for continuous use of biosensors.

Methods

A total of 77 participants (31 forensic clients with mild intellectual disabilities and 46 forensic staff members) participated in a 1-week trial. Preceding the study, we selected 4 devices thought to benefit the participants in domains of self-regulation, physical health, or sleep. Qualitative and quantitative questionnaires were used that explored the determinants of usability, acceptance, and continuous use of biosensors. Questionnaires consisted of the System Usability Scale, the Technology Acceptance Model questionnaire, and the extended expectation confirmation model questionnaire.

Results

Only the experienced usability of the devices was associated with intended continuous use. Forensic clients scored higher on acceptance and intention for continuous use than staff members. Moderate associations were found between usability with acceptance and continuous use. Staff members showed stronger associations between usability and acceptance (r=.80, P<.001) and usability and continuous use (r=.79, P<.001) than clients, who showed more moderate correlations between usability and acceptance (r=.46, P=.01) and usability and continuous use (r=.52, P=.003). The qualitative questionnaires in general indicated that the devices were easy to use and gave clear information.

Conclusions

Contrary to expectations, it was the actual perceived usability of wearing a biosensor that was associated with continuous use and to a much lesser extent the expectancy of usability. Clients scored higher on acceptance and intention for continuous use, but associations between usability and both acceptance and continuous use were markedly stronger in staff members. This study provides clear directions on how to further investigate these associations. For example, whether this is a true effect or due to a social desirability bias in the client group must be investigated. Clients with mild intellectual disabilities might benefit from the ease of use of these devices and their continuing monitoring and coaching apps. For these clients, it is especially important to develop easy-to-use biosensors with a minimum requirement on cognitive capacity to increase usability, acceptance, and continuous use.

Remote Monitoring of Critically-Ill Post-Surgical Patients: Lessons from a Biosensor Implementation Trial

Biosensors represent one of the numerous promising technologies envisioned to extend healthcare delivery. In perioperative care, the healthcare delivery system can use biosensors to remotely supervise patients who would otherwise be admitted to a hospital. This novel technology has gained a foothold in healthcare with significant acceleration due to the COVID-19 pandemic. However, few studies have attempted to narrate, or systematically analyze, the process of their implementation. We performed an observational study of biosensor implementation. The data accuracy provided by the commercially available biosensors was compared to those offered by standard clinical monitoring on patients admitted to the intensive care unit/perioperative unit. Surveys were also conducted to examine the acceptance of technology by patients and medical staff. We demonstrated a significant difference in vital signs between sensors and standard monitoring which was very dependent on the measured variables. Sensors seemed to integrate into the workflow relatively quickly, with almost no reported problems. The acceptance of the biosensors was high by patients and slightly less by nurses directly involved in the patients’ care. The staff forecast a broad implementation of biosensors in approximately three to five years, yet are eager to learn more about them. Reliability considerations proved particularly troublesome in our implementation trial. Careful evaluation of sensor readiness is most likely necessary prior to system-wide implementation by each hospital to assess for data accuracy and acceptance by the staff.

Alcohol Use Disorder in the Age of Technology: A Review of Wearable Biosensors in Alcohol Use Disorder Treatment

Biosensors enable observation and understanding of latent physiological occurrences otherwise unknown or invasively detected. Wearable biosensors monitoring physiological constructs across a wide variety of mental and physical health conditions have become an important trend in innovative research methodologies. Within substance use research, explorations of biosensor technology commonly focus on identifying physiological indicators of intoxication to increase understanding of addiction etiology and to inform treatment recommendations. In this review, we examine the state of research in this area as it pertains to treatment of alcohol use disorders specifically highlighting the gaps in our current knowledge with recommendations for future research. Annually, alcohol use disorders affect approximately 15 million individuals. A primary focus of existing wearable technology-based research among people with alcohol use disorders is identifying alcohol intoxication. A large benefit of wearable biosensors for this purpose is they provide continuous readings in a passive manner compared with the gold standard measure of blood alcohol content (BAC) traditionally measured intermittently by breathalyzer or blood draw. There are two primary means of measuring intoxication with biosensors: gait and sweat. Gait changes have been measured via smart sensors placed on the wrist, in the shoe, and mobile device sensors in smart phones. Sweat measured by transdermal biosensors detects the presence of alcohol in the blood stream correlating to BAC. Transdermal biosensors have been designed in tattoos/skin patches, shirts, and most commonly, devices worn on the ankle or wrist. Transdermal devices were initially developed to help monitor court-ordered sobriety among offenders with alcohol use disorder. These devices now prove most useful in continuously tracking consumption throughout clinical trials for behavioral treatment modalities. More recent research has started exploring the uses for physical activity trackers and physiological arousal sensors to guide behavioral interventions for relapse prevention. While research has begun to demonstrate wearable devices' utility in reducing alcohol consumption among individuals aiming to cutdown on their drinking, monitoring sustained abstinence in studies exploring contingency management for alcohol use disorders, and facilitating engagement in activity-based treatment interventions, their full potential to further aid in understanding of, and treatment for, alcohol use disorders has yet to be explored.

Recent Progress in Wearable Biosensors: From Healthcare Monitoring to Sports Analytics

Recent advances in lab-on-a-chip technology establish solid foundations for wearable biosensors. These newly emerging wearable biosensors are capable of non-invasive, continuous monitoring by miniaturization of electronics and integration with microfluidics. The advent of flexible electronics, biochemical sensors, soft microfluidics, and pain-free microneedles have created new generations of wearable biosensors that explore brand-new avenues to interface with the human epidermis for monitoring physiological status. However, these devices are relatively underexplored for sports monitoring and analytics, which may be largely facilitated by the recent emergence of wearable biosensors characterized by real-time, non-invasive, and non-irritating sensing capacities. Here, we present a systematic review of wearable biosensing technologies with a focus on materials and fabrication strategies, sampling modalities, sensing modalities, as well as key analytes and wearable biosensing platforms for healthcare and sports monitoring with an emphasis on sweat and interstitial fluid biosensing. This review concludes with a summary of unresolved challenges and opportunities for future researchers interested in these technologies. With an in-depth understanding of the state-of-the-art wearable biosensing technologies, wearable biosensors for sports analytics would have a significant impact on the rapidly growing field-microfluidics for biosensing.

Organic Electrochemical Transistors (OECTs) Toward Flexible and Wearable Bioelectronics

Organic electronics have emerged as a fascinating area of research and technology in the past two decades and are anticipated to replace classic inorganic semiconductors in many applications. Research on organic light-emitting diodes, organic photovoltaics, and organic thin-film transistors is already in an advanced stage, and the derived devices are commercially available. A more recent case is the organic electrochemical transistors (OECTs), whose core component is a conductive polymer in contact with ions and solvent molecules of an electrolyte, thus allowing it to simultaneously regulate electron and ion transport. OECTs are very effective in ion-to-electron transduction and sensor signal amplification. The use of synthetically tunable, biocompatible, and depositable organic materials in OECTs makes them specially interesting for biological applications and printable devices. In this review, we provide an overview of the history of OECTs, their physical characterization, and their operation mechanism. We analyze OECT performance improvements obtained by geometry design and active material selection (i.e., conductive polymers and small molecules) and conclude with their broad range of applications from biological sensors to wearable devices.

Correlating Grip Force Signals from Multiple Sensors Highlights Prehensile Control Strategies in a Complex Task-User System

Wearable sensor systems with transmitting capabilities are currently employed for the biometric screening of exercise activities and other performance data. Such technology is generally wireless and enables the non-invasive monitoring of signals to track and trace user behaviors in real time. Examples include signals relative to hand and finger movements or force control reflected by individual grip force data. As will be shown here, these signals directly translate into task, skill, and hand-specific (dominant versus non-dominant hand) grip force profiles for different measurement loci in the fingers and palm of the hand. The present study draws from thousands of such sensor data recorded from multiple spatial locations. The individual grip force profiles of a highly proficient left-hander (expert), a right-handed dominant-hand-trained user, and a right-handed novice performing an image-guided, robot-assisted precision task with the dominant or the non-dominant hand are analyzed. The step-by-step statistical approach follows Tukey's "detective work" principle, guided by explicit functional assumptions relating to somatosensory receptive field organization in the human brain. Correlation analyses (Person's product moment) reveal skill-specific differences in co-variation patterns in the individual grip force profiles. These can be functionally mapped to from-global-to-local coding principles in the brain networks that govern grip force control and its optimization with a specific task expertise. Implications for the real-time monitoring of grip forces and performance training in complex task-user systems are brought forward.

Validation of Fabric-Based Thigh-Wearable EMG Sensors and Oximetry for Monitoring Quadriceps Activity during Strength and Endurance Exercises

Muscle oximetry based on near-infrared spectroscopy (NIRS) and electromyography (EMG) techniques in adherent clothing might be used to monitor the muscular activity of selected muscle groups while exercising. The fusion of these wearable technologies in sporting garments can allow the objective assessment of the quality and the quantity of the muscle activity as well as the continuous monitoring of exercise programs. Several prototypes integrating EMG and NIRS have been developed previously; however, most devices presented the limitations of not measuring regional muscle oxyhemoglobin saturation and did not embed textile sensors for EMG. The purpose of this study was to compare regional muscle oxyhemoglobin saturation and surface EMG data, measured under resting and dynamic conditions (treadmill run and strength exercises) by a recently developed wearable integrated quadriceps muscle oximetry/EMG system adopting smart textiles for EMG, with those obtained by using two "gold standard" commercial instrumentations for EMG and muscle oximetry. The validity and agreement between the wearable integrated muscle oximetry/EMG system and the "gold standard" instrumentations were assessed by using the Bland-Altman agreement plots to determine the bias. The results support the validity of the data provided by the wearable electronic garment developed purposely for the quadriceps muscle group and suggest the potential of using such device to measure strength and endurance exercises in vivo in various populations.

Microfluidics by Additive Manufacturing for Wearable Biosensors: A Review

Wearable devices are nowadays at the edge-front in both academic research as well as in industry, and several wearable devices have been already introduced in the market. One of the most recent advancements in wearable technologies for biosensing is in the area of the remote monitoring of human health by detection on-the-skin. However, almost all the wearable devices present in the market nowadays are still providing information not related to human ‘metabolites and/or disease’ biomarkers, excluding the well-known case of the continuous monitoring of glucose in diabetic patients. Moreover, even in this last case, the glycaemic level is acquired under-the-skin and not on-the-skin. On the other hand, it has been proven that human sweat is very rich in molecules and other biomarkers (e.g., ions), which makes sweat a quite interesting human liquid with regards to gathering medical information at the molecular level in a totally non-invasive manner. Of course, a proper collection of sweat as it is emerging on top of the skin is required to correctly convey such liquid to the molecular biosensors on board of the wearable system. Microfluidic systems have efficiently come to the aid of wearable sensors, in this case. These devices were originally built using methods such as photolithographic and chemical etching techniques with rigid materials. Nowadays, fabrication methods of microfluidic systems are moving towards three-dimensional (3D) printing methods. These methods overcome some of the limitations of the previous method, including expensiveness and non-flexibility. The 3D printing methods have a high speed and according to the application, can control the textures and mechanical properties of an object by using multiple materials in a cheaper way. Therefore, the aim of this paper is to review all the most recent advancements in the methods for 3D printing to fabricate wearable fluidics and provide a critical frame for the future developments of a wearable device for the remote monitoring of the human metabolism directly on-the-skin.

Alveolus-Inspired Active Membrane Sensors for Self-Powered Wearable Chemical Sensing and Breath Analysis

Fossil fuel internal combustion engines generate and release a huge amount of nitrogen dioxide, leading to respiratory and allergic diseases such as asthma, pneumonia, and possibly tuberculosis. Here we develop an alveolus-inspired membrane sensor (AIMS) for self-powered wearable nitrogen dioxide detection and personal physiological assessment. The bionic AIMS exhibits an excellent sensitivity up to 452.44%, a good linearity of 0.976, and superior selectivity under a NO₂ concentration of 50 ppm. Furthermore, the AIMS can also be employed to diagnose human breath behaviors for breath analysis. The fundamental sensing mechanism is established using a combination of thermodynamic analysis, finite-element analysis, and phase-field simulations. It is found that the depolarization field inside the sensitive materials plays a crucial role in the self-powered gas-sensing performance. This work not only provides an efficient, low-cost, portable, and environmentally friendly means for active environmental assessment and personal biomonitoring but also provides a deep understanding of the gas-sensing mechanisms.

Roll-to-Roll Gravure Printed Electrochemical Sensors for Wearable and Medical Devices

As recent developments in noninvasive biosensors spearhead the thrust toward personalized health and fitness monitoring, there is a need for high throughput, cost-effective fabrication of flexible sensing components. Toward this goal, we present roll-to-roll (R2R) gravure printed electrodes that are robust under a range of electrochemical sensing applications. We use inks and electrode morphologies designed for electrochemical and mechanical stability, achieving devices with uniform redox kinetics printed on 150 m flexible substrate rolls. We show that these electrodes can be functionalized into consistently high performing sensors for detecting ions, metabolites, heavy metals, and other small molecules in noninvasively accessed biofluids, including sensors for real-time, in situ perspiration monitoring during exercise. This development of robust and versatile R2R gravure printed electrodes represents a key translational step in enabling large-scale, low-cost fabrication of disposable wearable sensors for personalized health monitoring applications.

Methylxanthine Drug Monitoring with Wearable Sweat Sensors

Drug monitoring plays crucial roles in doping control and precision medicine. It helps physicians tailor drug dosage for optimal benefits, track patients' compliance to prescriptions, and understand the complex pharmacokinetics of drugs. Conventional drug tests rely on invasive blood draws. While urine and sweat are attractive alternative biofluids, the state-of-the-art methods require separate sample collection and processing steps and fail to provide real-time information. Here, a wearable platform equipped with an electrochemical differential pulse voltammetry sensing module for drug monitoring is presented. A methylxanthine drug, caffeine, is selected to demonstrate the platform's functionalities. Sweat caffeine levels are monitored under various conditions, such as drug doses and measurement time after drug intake. Elevated sweat caffeine levels upon increasing dosage and confirmable caffeine physiological trends are observed. This work leverages a wearable sweat sensing platform toward noninvasive and continuous point-of-care drug monitoring and management.

A Wearable Microfluidic Sensing Patch for Dynamic Sweat Secretion Analysis

Wearable sweat sensing is a rapidly rising research area driven by its promising potential in health, fitness, and diagnostic applications. Despite the growth in the field, major challenges in relation to sweat metrics remain to be addressed. These challenges include sweat rate monitoring for its complex relation with sweat compositions and sweat sampling for sweat dynamics studies. In this work, we present a flexible microfluidic sweat sensing patch that enhances real-time electrochemical sensing and sweat rate analysis via sweat sampling. The device contains a spiral-patterned microfluidic component that is embedded with ion-selective sensors and an electrical impedance-based sweat rate sensor on a flexible plastic substrate. The patch is enabled to autonomously perform sweat analysis by interfacing the sensing component with a printed circuit board that is capable of on-site signal conditioning, analysis, and transmission. Progressive sweat flow in the microfluidic device, governed by the pressure induced by the secreted sweat, enhances sweat sampling and electrochemical detection via a defined sweat collection chamber and a directed sweat route. The characteristic of the sweat rate sensor is validated through a theoretical simulation, and the precision and accuracy of the flow rate is verified with a commercial syringe pump and a Macroduct sweat collector. On-body simultaneous monitoring of ion (H⁺, Na⁺, K⁺, Cl^-) concentration and sweat rate is also demonstrated for sensor functionality. This sweat sensing patch provides an integrated platform for a comprehensive sweat secretion analysis and facilitates physiological and clinical investigations by closely monitoring interrelated sweat parameters.

Coverage of Emotion Recognition for Common Wearable Biosensors

The present research proposes a novel emotion recognition framework for the computer prediction of human emotions using common wearable biosensors. Emotional perception promotes specific patterns of biological responses in the human body, and this can be sensed and used to predict emotions using only biomedical measurements. Based on theoretical and empirical psychophysiological research, the foundation of autonomic specificity facilitates the establishment of a strong background for recognising human emotions using machine learning on physiological patterning. However, a systematic way of choosing the physiological data covering the elicited emotional responses for recognising the target emotions is not obvious. The current study demonstrates through experimental measurements the coverage of emotion recognition using common off-the-shelf wearable biosensors based on the synchronisation between audiovisual stimuli and the corresponding physiological responses. The work forms the basis of validating the hypothesis for emotional state recognition in the literature and presents coverage of the use of common wearable biosensors coupled with a novel preprocessing algorithm to demonstrate the practical prediction of the emotional states of wearers.

A Wearable Electrochemical Platform for Noninvasive Simultaneous Monitoring of Ca(2+) and pH

Homeostasis of ionized calcium in biofluids is critical for human biological functions and organ systems. Measurement of ionized calcium for clinical applications is not easily accessible due to its strict procedures and dependence on pH. pH balance in body fluids greatly affects metabolic reactions and biological transport systems. Here, we demonstrate a wearable electrochemical device for continuous monitoring of ionized calcium and pH of body fluids using a disposable and flexible array of Ca(2+) and pH sensors that interfaces with a flexible printed circuit board. This platform enables real-time quantitative analysis of these sensing elements in body fluids such as sweat, urine, and tears. Accuracy of Ca(2+) concentration and pH measured by the wearable sensors is validated through inductively coupled plasma-mass spectrometry technique and a commercial pH meter, respectively. Our results show that the wearable sensors have high repeatability and selectivity to the target ions. Real-time on-body assessment of sweat is also performed, and our results indicate that calcium concentration increases with decreasing pH. This platform can be used in noninvasive continuous analysis of ionized calcium and pH in body fluids for disease diagnosis such as primary hyperparathyroidism and kidney stones.

Features and application of wearable biosensors in medical care

One of the new technologies in the field of health is wearable biosensor, which provides vital signs monitoring of patients, athletes, premature infants, children, psychiatric patients, people who need long-term care, elderly, and people in impassable regions far from health and medical services. The aim of this study was to explain features and applications of wearable biosensors in medical services. This was a narrative review study that done in 2015. Search conducted with the help of libraries, books, conference proceedings, through databases of Science Direct, PubMed, Proquest, Springer, and SID (Scientific Information Database). In our searches, we employed the following keywords and their combinations; vital sign monitoring, medical smart shirt, smart clothing, wearable biosensors, physiological monitoring system, remote detection systems, remote control health, and bio-monitoring system. The preliminary search resulted in 54 articles, which published between 2002 and 2015. After a careful analysis of the content of each paper, 41 sources selected based on their relevancy. Although the use of wearable in healthcare is still in an infant stage, it could have a magic effect on healthcare. Smart wearable in the technology industry for 2015 is one that is looking to be a big and profitable market. Wearable biosensors capable of continuous vital signs monitoring and feedback to the user will be significantly effective in timely prevention, diagnosis, treatment, and control of diseases.