Energy Solutions for Wearable Sensors: A Review

Choice of Piezoelectric Element over Accelerometer for an Energy-Autonomous Shoe-Based System

Shoe-based wearable sensor systems are a growing research area in health monitoring, disease diagnosis, rehabilitation, and sports training. These systems-equipped with one or more sensors, either of the same or different types-capture information related to foot movement or pressure maps beneath the foot. This captured information offers an overview of the subject's overall movement, known as the human gait. Beyond sensing, these systems also provide a platform for hosting ambient energy harvesters. They hold the potential to harvest energy from foot movements and operate related low-power devices sustainably. This article proposes two types of strategies (Strategy 1 and Strategy 2) for an energy-autonomous shoe-based system. Strategy 1 uses an accelerometer as a sensor for gait acquisition, which reflects the classical choice. Strategy 2 uses a piezoelectric element for the same, which opens up a new perspective in its implementation. In both strategies, the piezoelectric elements are used to harvest energy from foot activities and operate the system. The article presents a fair comparison between both strategies in terms of power consumption, accuracy, and the extent to which piezoelectric energy harvesters can contribute to overall power management. Moreover, Strategy 2, which uses piezoelectric elements for simultaneous sensing and energy harvesting, is a power-optimized method for an energy-autonomous shoe system.

Recent developments and future perspectives of microfluidics and smart technologies in wearable devices

Wearable devices are gaining popularity in the fields of health monitoring, diagnosis, and drug delivery. Recent advances in wearable technology have enabled real-time analysis of biofluids such as sweat, interstitial fluid, tears, saliva, wound fluid, and urine. The integration of microfluidics and emerging smart technologies, such as artificial intelligence (AI), machine learning (ML), and Internet of Things (IoT), into wearable devices offers great potential for accurate and non-invasive monitoring and diagnosis. This paper provides an overview of current trends and developments in microfluidics and smart technologies in wearable devices for analyzing body fluids. The paper discusses common microfluidic technologies in wearable devices and the challenges associated with analyzing each type of biofluid. The paper emphasizes the importance of combining smart technologies with microfluidics in wearable devices, and how they can aid diagnosis and therapy. Finally, the paper covers recent applications, trends, and future developments in the context of intelligent microfluidic wearable devices.

Advancements in Airborne Viral Nucleic Acid Detection with Wearable Devices

Wearable health sensors for an expanding range of physiological parameters have experienced rapid development in recent years and are poised to disrupt the way healthcare is tracked and administered. The monitoring of environmental contaminants with wearable technologies is an additional layer of personal and public healthcare and is also receiving increased focus. Wearable sensors that detect exposure to airborne viruses could alert wearers of viral exposure and prompt proactive testing and minimization of viral spread, benefitting their own health and decreasing community risk. With the high levels of asymptomatic spread of COVID-19 observed during the pandemic, such devices could dramatically enhance our pandemic response capabilities in the future. To facilitate advancements in this area, this review summarizes recent research on airborne viral detection using wearable sensing devices as well as technologies suitable for wearables. Since the low concentration of viral particles in the air poses significant challenges to detection, methods for airborne viral particle collection and viral sensing are discussed in detail. A special focus is placed on nucleic acid-based viral sensing mechanisms due to their enhanced ability to discriminate between viral subtypes. Important considerations for integrating airborne viral collection and sensing on a single wearable device are also discussed.

Advances in Smart Photovoltaic Textiles

Energy harvesting textiles have emerged as a promising solution to sustainably power wearable electronics. Textile-based solar cells (SCs) interconnected with on-body electronics have emerged to meet such needs. These technologies are lightweight, flexible, and easy to transport while leveraging the abundant natural sunlight in an eco-friendly way. In this Review, we comprehensively explore the working mechanisms, diverse types, and advanced fabrication strategies of photovoltaic textiles. Furthermore, we provide a detailed analysis of the recent progress made in various types of photovoltaic textiles, emphasizing their electrochemical performance. The focal point of this review centers on smart photovoltaic textiles for wearable electronic applications. Finally, we offer insights and perspectives on potential solutions to overcome the existing limitations of textile-based photovoltaics to promote their industrial commercialization.

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.

Smart Detecting and Versatile Wearable Electrical Sensing Mediums for Healthcare

A rapidly expanding global population and a sizeable portion of it that is aging are the main causes of the significant increase in healthcare costs. Healthcare in terms of monitoring systems is undergoing radical changes, making it possible to gauge or monitor the health conditions of people constantly, while also removing some minor possibilities of going to the hospital. The development of automated devices that are either attached to organs or the skin, continually monitoring human activity, has been made feasible by advancements in sensor technologies, embedded systems, wireless communication technologies, nanotechnologies, and miniaturization being ultra-thin, lightweight, highly flexible, and stretchable. Wearable sensors track physiological signs together with other symptoms such as respiration, pulse, and gait pattern, etc., to spot unusual or unexpected events. Help may therefore be provided when it is required. In this study, wearable sensor-based activity-monitoring systems for people are reviewed, along with the problems that need to be overcome. In this review, we have shown smart detecting and versatile wearable electrical sensing mediums in healthcare. We have compiled piezoelectric-, electrostatic-, and thermoelectric-based wearable sensors and their working mechanisms, along with their principles, while keeping in view the different medical and healthcare conditions and a discussion on the application of these biosensors in human health. A comparison is also made between the three types of wearable energy-harvesting sensors: piezoelectric-, electrostatic-, and thermoelectric-based on their output performance. Finally, we provide a future outlook on the current challenges and opportunities.

Sustainable Solutions for Oral Health Monitoring: Biowaste-Derived Triboelectric Nanogenerator

Oral healthcare monitoring is a vital aspect of identifying and addressing oral dental problems including tooth decay, gum pain, and oral cancer. Day by day, healthcare facilities and regular checkups are becoming more costly and time-consuming. In this context, consumers are moving toward advanced technology, such as bite sensors, to obtain regular data about their occlusal chewing patterns and strength. The triboelectric nanogenerator (TENG) can potentially eliminate the need for a battery by simply converting abundant vibrations from nature or human motion into electrical energy. In this work, biomaterials are obtained from biowastes such as cellulose from wood waste, chitosan from crab shells, and gelatin from fish scales. All wastes are biodegradable, and our work aims at sustainability and waste hierarchy. The single electrode mode-based TENG was designed and fabricated using biodegradable poly(vinyl alcohol) (PVA)-biomaterial composites, rice paper as a substrate, and edible silver leaf as an electrode. The highest electrical output was obtained for PVA/chitosan 10 wt % composite-based TENG (PC10) of about 20 V, 200 nA, and 12 nC. The biomechanical energy harvesting was measured, and powering of LED was demonstrated using a PC10 TENG device. A biocompatible bite sensor based on the TENG was used to measure the biting force of a dummy teeth model to demonstrate its potential use in dental health applications. It indicates the promising future value of disposable oral medication devices without any invasive surgery or injection.

Electronic Design for Wearables Devices Addressed from a Gender Perspective: Cross-Influences and a Methodological Proposal

The design of wearable devices has been approached from many perspectives over the years, mainly from a functionality, electronics, mechanics, usability, wearability, or product design perspective. However, there is a missing point in these approaches: the gender perspective. Gender intersects with every approach and, considering the interrelationships and dependencies, can achieve a better adherence, reach a wider audience, and even change the conception of the wearables design paradigm. The electronics design addressed from a gender perspective must consider both the morphological and anatomical impacts and those emanating from socialization. This paper presents an analysis of the different factors to consider when designing the electronics of a wearable device, including the functionality to implement, sensors, communications, or the location, together with their interdependencies, and proposes a user-centered methodology that contemplates a gender perspective at every stage. Finally, we present a use case that validates the proposed methodology in a real design of a wearable device for the prevention of gender-based violence cases. For the application of the methodology, 59 experts have been interviewed, 300 verbatims have been extracted and analyzed, a dataset from the data of 100 women has been created and the wearable devices have been tested for a week by 15 users. The electronics design needs to be addressed from a multidisciplinary approach, by rethinking the decisions taken for granted and analyzing the implications and interrelationships from a gender perspective. We need to enroll more diverse people at every design stage and include gender as one of the variables to study.

Three-Stage Power Supply System Model for a Wearable IoT Device for COVID-19 Patients

During the current crisis caused by the COVID-19 pandemic, Wearable IoT (WIoT) health devices have become essential resources for remote monitoring of the main physiological signs affected by this disease. As well as sensors, microprocessor, and wireless communication elements are widely studied, the power supply unit has the same importance for the WIoT technology, since the autonomy of the system between recharges is of great importance. This letter presents the design of the power supply system of a WIoT device capable of monitoring oxygen saturation and body temperature, sending the collected data to an IoT platform. The supply system is based on a three-stage block consisting of a rechargeable battery, battery charge controller, and dc voltage converter. The power supply system is designed and implemented as a prototype in order to test performance and efficiency. The results show that the designed block provides a stable supply voltage avoiding energy losses, which makes it an efficient and rapidly developing system.

Skin-Interfaced Wearable Sweat Sensors for Precision Medicine

Wearable sensors hold great potential in empowering personalized health monitoring, predictive analytics, and timely intervention toward personalized healthcare. Advances in flexible electronics, materials science, and electrochemistry have spurred the development of wearable sweat sensors that enable the continuous and noninvasive screening of analytes indicative of health status. Existing major challenges in wearable sensors include: improving the sweat extraction and sweat sensing capabilities, improving the form factor of the wearable device for minimal discomfort and reliable measurements when worn, and understanding the clinical value of sweat analytes toward biomarker discovery. This review provides a comprehensive review of wearable sweat sensors and outlines state-of-the-art technologies and research that strive to bridge these gaps. The physiology of sweat, materials, biosensing mechanisms and advances, and approaches for sweat induction and sampling are introduced. Additionally, design considerations for the system-level development of wearable sweat sensing devices, spanning from strategies for prolonged sweat extraction to efficient powering of wearables, are discussed. Furthermore, the applications, data analytics, commercialization efforts, challenges, and prospects of wearable sweat sensors for precision medicine are discussed.

IoT and Deep Learning-Based Farmer Safety System

Farming is a fundamental factor driving economic development in most regions of the world. As in agricultural activity, labor has always been hazardous and can result in injury or even death. This perception encourages farmers to use proper tools, receive training, and work in a safe environment. With the wearable device as an Internet of Things (IoT) subsystem, the device can read sensor data as well as compute and send information. We investigated the validation and simulation dataset to determine whether accidents occurred with farmers by applying the Hierarchical Temporal Memory (HTM) classifier with each dataset input from the quaternion feature that represents 3D rotation. The performance metrics analysis showed a significant 88.00% accuracy, precision of 0.99, recall of 0.04, F_Score of 0.09, average Mean Square Error (MSE) of 5.10, Mean Absolute Error (MAE) of 0.19, and a Root Mean Squared Error (RMSE) of 1.51 for the validation dataset, 54.00% accuracy, precision of 0.97, recall of 0.50, F_Score of 0.66, MSE = 0.06, MAE = 3.24, and = 1.51 for the Farming-Pack motion capture (mocap) dataset. The computational framework with wearable device technology connected to ubiquitous systems, as well as statistical results, demonstrate that our proposed method is feasible and effective in solving the problem's constraints in a time series dataset that is acceptable and usable in a real rural farming environment for optimal solutions.

Towards More Accurate Determination of the Thermoelectric Properties of Bi2Se3 Epifilms by Suspension via Nanomachining Techniques

We report on the characterization of the thermoelectric properties of Bi2Se3 epifilms. MBE-grown Bi2Se3 films on GaAs (111) A are nanomachined with integrated Pt elements serving as local joule heaters, thermometers, and voltage probes. We suspended a 4 µm × 120 µm Bi2Se3 by nanomachining techniques. Specifically, we selectively etched GaAs buffer/substrate layers by citric acid solution followed by a critical point drying method. We found that the self-heating 3ω method is an appropriate technique for the accurate measurement of the thermal conductivity of suspended Bi2Se3. The measured thermoelectric properties of 200 nm thick Bi2Se3 at room temperature were κ=1.95 W/m K, S=−102.8 μV/K, σ = 75,581 S/m and the figure of merit was ZT=0.12. The study introduces a method to measure thermal conductivity accurately by suspending thin films.

Self-Sustainable Biomedical Devices Powered by RF Energy: A Review

Wearable and implantable medical devices (IMDs) have come a long way in the past few decades and have contributed to the development of many personalized health monitoring and therapeutic applications. Sustaining these devices with reliable and long-term power supply is still an ongoing challenge. This review discusses the challenges and milestones in energizing wearable and IMDs using the RF energy harvesting (RFEH) technique. The review highlights the main integrating frontend blocks such as the wearable and implantable antenna design, matching network, and rectifier topologies. The advantages and bottlenecks of adopting RFEH technology in wearable and IMDs are reviewed, along with the system elements and characteristics that enable these devices to operate in an optimized manner. The applications of RFEH in wearable and IMDs medical devices are elaborated in the final section of this review. This article summarizes the recent developments in RFEH, highlights the gaps, and explores future research opportunities.

Proof-of-concept of a mattress based power harvesting system architecture suitable for wireless physiological monitoring systems

This work investigates the feasibility of having a mattress based wireless power transfer system with transfer efficiency such that the received power could potentially be enough to fully power up wearable systems intended to provide some level of continuous physiological monitoring; hence eliminating the need for users to ever have to recharge the systems. The novel architecture proposed in this work, to optimise power transfer efficiency against angular misalignment typical of non-static use is based on a non-coupling coil structure combined with a magnetic beamforming scheme. The coil system also incorporates a non-coupling relay array to overcome the significant loss in power transfer efficiency associated to increasing distances between transmitters and receivers. The system is proven to be able to deliver around 11.8mW of power in the worst-case scenario, with a receiver 25cm above the transmitters, whilst meeting the safety requirements associated to electromagnetic exposure to the human body.

Rotating Gate-Driven Solution-Processed Triboelectric Transistors

Among various energy harvesting technologies, triboelectricity is an epoch-making discovery that can convert energy loss caused by the mechanical vibration or friction of parts into energy gain. As human convenience has emerged as an important future value, wireless devices have attracted widespread attention; thus, it is essential to extend the duration and lifespan of batteries through energy harvesting or the application of self-powered equipment. Here, we report a transistor, in which the gate rotates and rubs against the dielectric and utilizes the triboelectricity generated rather than the switching voltage of the transistor. The device is a triboelectric transistor with a simple structure and is manufactured using a simple process. Compared to that at the stationary state, the output current of the triboelectric transistor increased by 207.66 times at the maximum rotation velocity. The approach reported in this paper could be an innovative method to enable a transistor to harness its own power while converting energy loss in any rotating object into harvested energy.

A vision for the future of wearable sensors in spine care and its challenges: narrative review

OBJECTIVE

This review aimed to: (I) provide a brief overview of some topical areas of current literature regarding applications of wearable sensors in the management of low back pain (LBP); (II) present a vision for a future comprehensive system that integrates wearable sensors to measure multiple parameters in the real world that contributes data to guide treatment selection (aided by artificial intelligence), uses wearables to aid treatment support, adherence and outcome monitoring, and interrogates the response of the individual patient to the prescribed treatment to guide future decision support for other individuals who present with LBP; and (III) consider the challenges that will need to be overcome to make such a system a reality.

BACKGROUND

Advances in wearable sensor technologies are opening new opportunities for the assessment and management of spinal conditions. Although evidence of improvements in outcomes for individuals with LBP from the use of sensors is limited, there is enormous future potential.

METHODS

Narrative review and literature synthesis.

CONCLUSIONS

Substantial research is underway by groups internationally to develop and test elements of this system, to design innovative new sensors that enable recording of new data in new ways, and to fuse data from multiple sources to provide rich information about an individual's experience of LBP. Together this system, incorporating data from wearable sensors has potential to personalise care in ways that were hitherto thought impossible. The potential is high but will require concerted effort to develop and ultimately will need to be feasible and more effective than existing management.

Ambient Light Energy Harvesting and Numerical Modeling of Non-Linear Phenomena

Ambient light is an energy-harvesting source that can recharge a battery with less human interaction and can be used to prolong the operational time of the Internet of Things, e.g., mobile phones and wearable devices. Available light energy is insufficient for directly charging mobile phones and wearable devices, but it can supplement batteries to power some low-energy-consuming critical functions of the wearable device, especially in low-power consumption wearables. However, in an emergency scenario when the battery’s operational time is not sufficient or a battery charging source is unavailable, a solution is required to extend the limited battery span for mobile and wearable devices. This work presents the bottlenecks and new advancements in the commercialization of photovoltaics for smartphones and wearable technologies based on ambient light energy harvesting. A new technique, in which a smartphone cover is used as a solar concentrator to enhance light energy harvesting associated with algorithms, is experimentally demonstrated. Our research outcomes show that solar concentrators can improve light intensity by approximately 1.85 and 1.43 times at 90° and 71° angles, respectively, thus harvesting more ambient light energy at 2500 lx light intensity in a typical office environment. Type-1 PV and Type-2 PV cells were able to charge the additional battery in 8 h under 2500 lx lighting intensity in an indoor office environment. A system and logic algorithm technique is presented to efficiently transfer harvested light energy to perform low-energy consumption operations in a device, in order to improve the operational time of the device’s battery.

Communication Requirements in 5G-Enabled Healthcare Applications: Review and Considerations

Fifth generation (5G) mobile communication technology can enable novel healthcare applications and augment existing ones. However, 5G-enabled healthcare applications demand diverse technical requirements for radio communication. Knowledge of these requirements is important for developers, network providers, and regulatory authorities in the healthcare sector to facilitate safe and effective healthcare. In this paper, we review, identify, describe, and compare the requirements for communication key performance indicators in relevant healthcare use cases, including remote robotic-assisted surgery, connected ambulance, wearable and implantable devices, and service robotics for assisted living, with a focus on quantitative requirements. We also compare 5G-healthcare requirements with the current state of 5G capabilities. Finally, we identify gaps in the existing literature and highlight considerations for this space.

The status and perspectives of nanostructured materials and fabrication processes for wearable piezoresistive sensors

The wearable sensors have attracted a growing interest in different markets, including health, fitness, gaming, and entertainment, due to their outstanding characteristics of convenience, simplicity, accuracy, speed, and competitive price. The development of different types of wearable sensors was only possible due to advances in smart nanostructured materials with properties to detect changes in temperature, touch, pressure, movement, and humidity. Among the various sensing nanomaterials used in wearable sensors, the piezoresistive type has been extensively investigated and their potential have been demonstrated for different applications. In this review article, the current status and challenges of nanomaterials and fabrication processes for wearable piezoresistive sensors are presented in three parts. The first part focuses on the different types of sensing nanomaterials, namely, zero-dimensional (0D), one-dimensional (1D), two-dimensional (2D), and three-dimensional (3D) piezoresistive nanomaterials. Then, in second part, their fabrication processes and integration are discussed. Finally, the last part presents examples of wearable piezoresistive sensors and their applications.