Biophysical Sensors Research Articles

Recent Advances in Nanomaterial-Based Biosignal Sensors.

Recent research for medical fields, robotics, and wearable electronics aims to utilize biosignal sensors to gather bio-originated information and generate new values such as evaluating user well-being, predicting behavioral patterns, and supporting disease diagnosis and prevention. Notably, most biosignal sensors are designed for body placement to directly acquire signals, and the incorporation of nanomaterials such as metal-based nanoparticles or nanowires, carbon-based or polymer-based nanomaterials-offering stretchability, high surface-to-volume ratio, and tunability for various properties-enhances their adaptability for such applications. This review categorizes nanomaterial-based biosignal sensors into three types and analyzes them: 1) biophysical sensors that detect deformation such as folding, stretching, and even pulse, 2) bioelectric sensors that capture electric signal originating from human body such as heart and nerves, and 3) biochemical sensors that catch signals from bio-originated fluids such as sweat, saliva and blood. Then, limitations and improvements to nanomaterial-based biosignal sensors is depicted. Lastly, it is highlighted on deep learning-based signal processing and human-machine interface applications, which can enhance the potential of biosignal sensors. Through thispaper, it is aim to provide an understanding of nanomaterial-based biosignal sensors, outline the current state of the technology, discuss the challenges that be addressed, and suggest directions for development.

Wearable, Battery-Free, Self-Powered Electrochemical Sensors for Personalized Health Monitoring

Recent advances in materials, mechanics, and device architectures form the foundations for rapidly emerging classes of sensors with mechanical characteristics that allow for conformal interfaces with the soft, curvilinear surfaces of the human body. While the field of tissue-integrated biophysical sensors exhibits commendable progress in capturing clinical quality thermal, kinematic, and electrophysiological information, the advancement of complementary biochemical sensors severely lags due to unique challenges associated with seamless integration of delicate biochemical receptors, transducing components, and suitable packaging materials. In this talk, I will discuss non-traditional approaches to address some of these grand challenges. Specifically, I will discuss three technologies that my lab is developing -1) wearable, biofuel cell-inspired sensors for sweat monitoring 2) wearable, soft microfluidics with in-built valving and pumping capabilities for precise, on-demand sensing, and 3) AI-powered, wearable wound monitors for early prediction of chronic wounds.

Standalone Stretchable Biophysical Sensing System Based on Laser Direct Write of Patterned Porous Graphene/Co3O4 Nanocomposites.

Skin-interfaced wearable sensors can continuously monitor various biophysical and biochemical signals for health monitoring and disease diagnostics. However, such devices are typically limited by unsatisfactory and unstable output performance of the power supplies under mechanical deformations and human movements. Furthermore, there is also a lack of a simple and cost-effective fabrication technique to fabricate and integrate varying materials in the device system. Herein, we report a fully integrated standalone stretchable biophysical sensing system by combining wearable biophysical sensors, triboelectric nanogenerator (TENG), microsupercapacitor arrays (MSCAs), power management circuits, and wireless transmission modules. All of the device components and interconnections based on the three-dimensional (3D) networked graphene/Co3O4 nanocomposites are fabricated via low-cost and scalable direct laser writing. The self-charging power units can efficiently harvest energy from body motion into a stable and adjustable voltage/current output to drive various biophysical sensors and wireless transmission modules for continuously capturing, processing, and wirelessly transmitting various signals in real-time. The novel material modification, device configuration, and system integration strategies provide a rapid and scalable route to the design and application of next-generation standalone stretchable sensing systems for health monitoring and human-machine interfaces.

An autonomous wheelchair with health monitoring system based on Internet of Thing

Assistive powered wheelchairs will bring patients and elderly the ability of remain mobile without the direct intervention from caregivers. Vital signs from users can be collected and analyzed remotely to allow better disease prevention and proactive management of health and chronic conditions. This research proposes an autonomous wheelchair prototype system integrated with biophysical sensors based on Internet of Thing (IoT). A powered wheelchair system was developed with three biophysical sensors to collect, transmit and analysis users’ four vital signs to provide real-time feedback to users and clinicians. A user interface software embedded with the cloud artificial intelligence (AI) algorithms was developed for the data visualization and analysis. An improved data compression algorithm Minimalist, Adaptive and Streaming R-bit (O-MAS-R) was proposed to achieve a higher compression ratio with minimum 7.1%, maximum 45.25% compared with MAS algorithm during the data transmission. At the same time, the prototype wheelchair, accompanied with a smart-chair app, assimilates data from the onboard sensors and characteristics features within the surroundings in real-time to achieve the functions including obstruct laser scanning, autonomous localization, and point-to-point route planning and moving within a predefined area. In conclusion, the wheelchair prototype uses AI algorithms and navigation technology to help patients and elderly maintain their independent mobility and monitor their healthcare information in real-time.

(Invited) seamless Integration of Electronics, Electrochemistry, Microfluidics, and Materials for Next Generation Tissue-Integrated Sensors and Energy Devices

Recent advances in materials, mechanics, and device architectures form the foundations for rapidly emerging classes of sensors and energy devices with mechanical characteristics that allow for conformal interfaces with the soft, curvilinear surfaces of the human body. While the field of tissue-integrated biophysical sensors exhibits commendable progress in capturing clinical quality thermal, kinematic, and electrophysiological information, the advancement of complementary biochemical sensors severely lags due to unique challenges associated with seamless integration of delicate biochemical receptors, transducing components, and suitable packaging materials. Similarly, the vast majority of demonstrated tissue-mounted energy storage and energy harvesting systems unfortunately rely on toxic components that substantially diminish their attractiveness in bio-related applications. In this talk, I will discuss non-traditional approaches to address some of these grand challenges. Specifically, I will discuss three technologies that my lab is developing -1) wearable, self-powered sweat sensors for non-invasive health monitoring 2) wireless, implantable, battery-free sensors and optoelectronics for neuroscience research, and 3) fully resorbable batteries for broad applications in medicine and consumer electronics.

P‐172: Late‐News Poster: Highly Stretchable OLED Panel with Sensors Embedded for Healthcare Applications

Stretchable display has become emerging technology as the next‐generation form‐factor of flexible and rollable displays. Especially, advanced form of stretchable organic light‐emitting diode (OLED) display plays an increasingly central role in wearable healthcare applications. The stretchability of OLED display platform enable conformal to the curvature of the human body. Therefore, stretchability and the pixel density remain key requirements for the development of highly stretchable OLED display. Here, we report rational structural design for highly stretchable OLED panel with biophysical sensors embedded for healthcare applications. The island and stretchable bridges enable stretchability over 20%. Moreover, stretchable temperature and strain sensors embedded in panel provide new approach toward wearable healthcare applications.

Biophysical Sensors Based on Triboelectric Nanogenerators.

Triboelectric nanogenerators (TENGs) can not only collect mechanical energy around or inside the human body and convert it into electricity but also help monitor our body and the world by providing interpretable electrical signals during energy conversion, thus emerging as an innovative medical solution for both daily health monitoring and clinical treatment and bringing great convenience. This review tries to introduce the latest technological progress of TENGs for applications in biophysical sensors, where a TENG functions as a either a sensor or a power source, and in some cases, as both parts of a self-powered sensor system. From this perspective, this review begins from the fundamental working principles and then concisely illustrates the recent progress of TENGs given structural design, surface modification, and materials selection toward output enhancement and medical application flexibility. After this, the medical applications of TENGs in respiratory status, cardiovascular disease, and human rehabilitation are covered in detail, in the form of either textile or implantable parts for pacemakers, nerve stimulators, and nerve prostheses. In addition, the application of TENGs in driving third-party medical treatment systems is introduced. Finally, shortcomings and challenges in TENG-based biophysical sensors are highlighted, aiming to provide deeper insight into TENG-based medical solutions for the development of TENG-based self-powered electronics with higher performance for practical applications.

Low-delay interactive rendering of virtual acoustic environments with extensions for distributed low-delay transmission of audio and bio-physical sensor data

In this study, we present a system that enables low-delay rendering of interactive virtual acoustics. The tool operates in the time domain based on a physical sound propagation model with basic room acoustic modelling and a block-wise update and interpolation of the environment geometry. During the pandemic, the tool was extended by low-delay network-transmission of audio and sensor data, e.g., from motion sensors or bio-physical sensors such as EEG. With this extension, distributed rendering of turn-taking conversations as well as ensemble music performances with individual head-tracked binaural rendering and interactive movement of directional sources is possible. Interactive communication requires a low time delay in sound transmission, which is particularly critical for musical communication, where the upper limit of tolerable delay is between 30 and 50 ms, depending on the genre. Our system can achieve latencies between 7 (dedicated local network) and 100 ms (intercontinental connection), with typical values of 25–40 ms. This is far below the delay achieved by typical video-conferencing tools and is sufficient for fluent speech communicationand music applications. In addition to a technical description of the system, we show here example measurement data of head motion behaviour in a distributed triadic conversation.

Federated Feature Selection for Cyber-Physical Systems of Systems

Autonomous vehicles (AVs) generate a massive amount of multi-modal data that once collected and processed through Machine Learning algorithms, enable AI-based services at the Edge. In fact, only a subset of the collected data present informative attributes to be exploited at the Edge. Therefore, extracting such a subset is of utmost importance to limit computation and communication workloads. Doing that in a distributed manner imposes the AVs to cooperate in finding an agreement on which attributes should be sent to the Edge. In this work, we address such a problem by proposing a federated feature selection (FFS) algorithm where the AVs collaborate to filter out, iteratively, the less relevant attributes in a distributed manner, without any exchange of raw data, thought two different components: a Mutual-Information-based feature selection algorithm run by the AVs and a novel aggregation function based on the Bayes theorem executed on the Edge. The FFS algorithm has been tested on two reference datasets: MAV with images and inertial measurements of a monitored vehicle, WESAD with a collection of samples from biophysical sensors to monitor a relative passenger. The numerical results show that the AVs converge to a minimum achievable subset of features with both the datasets, i.e., 24 out of 2166 (99%) in MAV and 4 out of 8 (50%) in WESAD, respectively, preserving the informative content of data.

Screening Biophysical Sensors and Neurite Outgrowth Actuators in Human Induced-Pluripotent-Stem-Cell-Derived Neurons.

All living cells maintain a charge distribution across their cell membrane (membrane potential) by carefully controlled ion fluxes. These bioelectric signals regulate cell behavior (such as migration, proliferation, differentiation) as well as higher-level tissue and organ patterning. Thus, voltage gradients represent an important parameter for diagnostics as well as a promising target for therapeutic interventions in birth defects, injury, and cancer. However, despite much progress in cell and molecular biology, little is known about bioelectric states in human stem cells. Here, we present simple methods to simultaneously track ion dynamics, membrane voltage, cell morphology, and cell activity (pH and ROS), using fluorescent reporter dyes in living human neurons derived from induced neural stem cells (hiNSC). We developed and tested functional protocols for manipulating ion fluxes, membrane potential, and cell activity, and tracking neural responses to injury and reinnervation in vitro. Finally, using morphology sensor, we tested and quantified the ability of physiological actuators (neurotransmitters and pH) to manipulate nerve repair and reinnervation. These methods are not specific to a particular cell type and should be broadly applicable to the study of bioelectrical controls across a wide range of combinations of models and endpoints.

Biocompatible surface functionalization architecture for a diamond quantum sensor

Quantum metrology enables some of the most precise measurements. In the life sciences, diamond-based quantum sensing has led to a new class of biophysical sensors and diagnostic devices that are being investigated as a platform for cancer screening and ultrasensitive immunoassays. However, a broader application in the life sciences based on nanoscale NMR spectroscopy has been hampered by the need to interface highly sensitive quantum bit (qubit) sensors with their biological targets. Here, we demonstrate an approach that combines quantum engineering with single-molecule biophysics to immobilize individual proteins and DNA molecules on the surface of a bulk diamond crystal that hosts coherent nitrogen vacancy qubit sensors. Our thin (sub-5 nm) functionalization architecture provides precise control over the biomolecule adsorption density and results in near-surface qubit coherence approaching 100 μs. The developed architecture remains chemically stable under physiological conditions for over 5 d, making our technique compatible with most biophysical and biomedical applications.

(Invited) Exploring the Easy, Cost-Effective Fabrications of Multifunctional on-Skin Wearable Bioelectronic Devices

As compared to conventional, rigid, bulky physiological monitoring tools, emerging on-skin wearable bioelectronic devices are ultrathin, lightweight, and small footprint and can find wide applications in point-of-care diagnostics because of their easy deployment outside hospital settings. At present, on-skin wearables are usually fabricated by patterning conventional inorganic materials, novel organic materials, or emerging nanomaterials on flexible supporting substrates. Consequently, the state-of-the-art on-skin wearables often suffer from expensive precursor materials, costly fabrication facilities, complex fabrication processes, and limited functionalities and disposability. By using widely accessible pencils and papers as the fabrication tools, we have developed a rich variety of cost-effective, disposable on-skin bioelectronic devices, ranging from biophysical sensors (e.g., temperature sensors, electrophysiological sensors) and sweat biochemical sensors (pH sensors, uric acid sensors) to thermal stimulators, humidity energy harvesters, and transdermal drug delivery systems. The enabled devices can find wide applications in point-of-care diagnostics, particularly in low-resource environments owing to their low-cost resources, handy operation, time-saving fabrication, and abundant potential designs. In addition, with laser-assisted patterning of conductive and semiconductive materials on flexible substrates, the maskless, scalable fabrications of on-skin wearable bioelectronic devices can be achieved.

Anisotropic circular topological structures

We design cylindrical multilayer structures characterized by anisotropy and topological features. This provides a new approach to tailor electromagnetic fields into desired patterns with orbital angular momentum in cylindrical geometries as ring resonators and fibers. We use transformation optics to deal with anisotropic circular structures, and rigorously define the edge states. The resulting topologically protected high-localized modes, at the core/cladding interface, with angular momentum may trigger the developments of new disorder-robust devices and high Q-microcavities for applications in light transmission, quantum technology, nonlinear optics, TeraHertz devices, and biophysical sensors.

Employing Genetically Encoded, Biophysical Sensors to Understand WNT/Frizzled Interaction and Receptor Complex Activation.

The Frizzled (FZD) family of WNT receptors consists of ten paralogues in mammals. They belong to the superfamily of G protein-coupled receptors and regulate crucial processes during embryonic development. Dysregulated FZD signaling leads to disease, most prominently to diverse forms of cancer, which renders these receptors attractive for drug discovery. Recent advances in assay development and the design of genetically encoded biosensors monitoring ligand-receptor interaction, conformational dynamics, and protein-protein interaction have allowed for a better pharmacological understanding of WNT/FZD signal transduction and open novel avenues for mechanism-based drug discovery and screening. In this chapter, we summarize the recent progress in the molecular dissection of FZD activation based on advanced biosensors.

Biomechano-Interactive Materials and Interfaces.

The reciprocal mechanical interaction of engineered materials with biointerfaces have long been observed and exploited in biomedical applications. It contributes to the rise of biomechano-responsive materials and biomechano-stimulatory materials, constituting the biomechano-interactive interfaces. Here, endogenous and exogenous biomechanical stimuli available for mechanoresponsive interfaces are briefed and their mechanistic responses, including deformation and volume change, mechanomanipulation of physical and chemical bonds, dissociation of assemblies, and coupling with thermoresponsiveness are summarized. The mechanostimulatory materials, however, are capable of delivering mechanical cues, including stiffness, viscoelasticity, geometrical constraints, and mechanical loads, to modulate physiological and pathological behaviors of living tissues through the adaptive cellular mechanotransduction. The biomechano-interactive materials and interfaces are widely implemented in such fields as mechanotriggered therapeutics and diagnosis, adaptive biophysical sensors, biointegrated soft actuators, and mechanorobust tissue engineering, which have offered unprecedented opportunities for precision and personalized medicine. Pending challenges are also addressed to shed a light on future advances with respect to translational implementations.

Definition of Motion and Biophysical Indicators for Home-Based Rehabilitation through Serious Games

In this paper, we describe Remote Monitoring Validation Engineering System (ReMoVES), a newly-developed platform for motion rehabilitation through serious games and biophysical sensors. The main features of the system are highlighted as follows: motion tracking capabilities through Microsoft Kinect V2 and Leap Motion are disclosed and compared with other solutions; the emotional state of the patient is evaluated with heart rate measurements and electrodermal activity monitored by Microsoft Band 2 during the execution of the functional exercises planned by the therapist. The ReMoVES platform is conceived for home-based rehabilitation after the hospitalisation period, and the system will deploy machine learning techniques to provide an automated evaluation of the patient performance during the training. The algorithms should deliver effective reports to the therapist about the training performance while the patient exercises on their own. The game features that will be described in this manuscript represent the input for the training set, while the feedback provided by the therapist is the output. To face this supervised learning problem, we are describing the most significant features to be used as key indicators of the patient’s performance along with the evaluation of their accuracy in discriminating between good or bad patient actions.

Mobile Sensing in Environmental Health and Neighborhood Research.

Public health research has witnessed a rapid development in the use of location, environmental, behavioral, and biophysical sensors that provide high-resolution objective time-stamped data. This burgeoning field is stimulated by the development of novel multisensor devices that collect data for an increasing number of channels and algorithms that predict relevant dimensions from one or several data channels. Global positioning system (GPS) tracking, which enables geographic momentary assessment, permits researchers to assess multiplace personal exposure areas and the algorithm-based identification of trips and places visited, eventually validated and complemented using a GPS-based mobility survey. These methods open a new space-time perspective that considers the full dynamic of residential and nonresidential momentary exposures; spatially and temporally disaggregates the behavioral and health outcomes, thus replacing them in their immediate environmental context; investigates complex time sequences; explores the interplay among individual, environmental, and situational predictors; performs life-segment analyses considering infraindividual statistical units using case-crossover models; and derives recommendations for just-in-time interventions.

Mechano-Based Transductive Sensing for Wearable Healthcare.

Wearable healthcare presents exciting opportunities for continuous, real-time, and noninvasive monitoring of health status. Even though electrochemical and optical sensing have already made great advances, there is still an urgent demand for alternative signal transformation in terms of miniaturization, wearability, conformability, and stretchability. Mechano-based transductive sensing, referred to the efficient transformation of biosignals into measureable mechanical signals, is claimed to exhibit the aforementioned desirable properties, and ultrasensitivity. In this Concept, a focus on pressure, strain, deflection, and swelling transductive principles based on micro-/nanostructures for wearable healthcare is presented. Special attention is paid to biophysical sensors based on pressure/strain, and biochemical sensors based on microfluidic pressure, microcantilever, and photonic crystals. There are still many challenges to be confronted in terms of sample collection, miniaturization, and wireless data readout. With continuing efforts toward solving those problems, it is anticipated that mechano-based transduction will provide an accessible route for multimode wearable healthcare systems integrated with physical, electrophysiological, and biochemical sensors.

High Frequency Asynchronous Rotation of Magnetic Microspheres and Biophysical Applications - Higher Sensitivity Regime for Magnetic Bead Biosensors

Asynchronous rotation is an emerging platform technique with applications ranging from micro mixing to femtoliter viscometry and biophysical sensors (Applied Physics Letters 91, 224105 (2007)). Asynchronous rotation occurs when a driving magnetic field exceeds a critical frequency, above which the driving field is rotating faster than the driven body. The critical frequency depends on the viscosity of the fluid, size of the driven system, and the strength and quality of the driving field. The dynamics of a magnetic bead rotating at high frequencies were studied using a simple setup, consisting of a bright field microscope that was used to focus a 5 mW laser onto the particle of interest.

Measuring metabolism and biophysical flux in the tissue, cellular and sub-cellular domains: Recent developments in self-referencing amperometry for physiological sensing

Ultimately, advances in genomics, proteomics and metabolomics will be realized by combining these approaches with biophysical sensors for understanding the functional and structural (physiological) aspects of sub-cellular systems (cytomics). Therefore, the emergence of the new fields of cytomics and physiomics will require new technologies to probe the functional realm of living cells. While amperometric sensors have been used, their sensitivity and reliability are significantly improved through the development of new strategies and data acquisition systems for the operation of the sensors. This includes the application of the principles of the vibrating or self-referencing microsensor to the operation of amperometric sensors. The development of self-referencing amperometry (SRA) is significant because it effectively converts static concentration sensors into dynamic biophysical sensors that directly monitor physiological flux. SRA has been developed for analytes such as O2, NO, H2O2 and ascorbate. These sensors have been validated against non-biological microscopic flux sources that were theoretically modeled, before being applied to biological research. This new sensor technology has been shown, through research in a wide variety of biological and biomedical research projects, to be an important new tool in the arsenal of the cell biologist. SRA technology has been adapted through SRA-H2O2 and SRA-NADH sensors, for electrochemically coupled enzyme based self-referencing biosensors (SRB) for glucose, glutamate and ethanol. These developments in self-referencing sensor technologies offer great promise in extending electroanalytical chemistry and biosensor technologies from the micro to the nanoscale where researchers can study physiology at the sub-cellular and organellar levels.