The current healthcare systems based on disease management are suffering from limited, delayed, and inefficient medical services, especially when confronted with the pandemic and the aging population. Health care should move from its current reactive and disease-centric system to a personalized, predictive, preventative, and participatory model with a focus on disease prevention and health promotion. Textiles have been concomitant and played a vital role in the long history of human civilization. Equipping traditional textiles with diagnostic, therapeutic, and power supply capabilities can unlock electronic textiles as a point-of-care system with incomparable wearing comfort. In this talk, I will introduce our research progress in smart textiles for biomonitoring, therapeutics, power supply, and textiles body area network for personalized health care. I will showcase the platform technologies, fabrication strategies, and clinical translation of the smart textiles.

Small artery-related diseases affecting coronary, cerebral, or peripheral regions remain a persistent clinical challenge, primarily due to the enduring risk of thrombosis associated with implanted vascular devices. Despite advances in therapeutic strategies, including the utilization of drug-eluting stents (DES), life-threatening complications, such as late thrombosis, continue to affect patients, leading to severe consequences like heart attacks, strokes, and pulmonary embolisms. To address this critical issue, an innovative in-situ piezoelectric material-based surface treatment system that utilizes arterial pulsation has been studied to treat the surface using arterial pulsation actively and continuously for indwelling endovascular devices. Our novel technology leverages piezoelectric materials to generate a negatively charged surface using arterial pulsation without any battery, actively and effectively repelling platelets adherence to prevent potential clot formation. Hence, substantial reduction in platelet adherence is expected to significantly lower the risk of thrombosis. In this study, a low-profile piezoelectric unit was fabricated and mounted on the coronary artery stent to be deployed and continuously exposed to the blood to assess the device hemocompatibility response, considering typical arterial pulsation, and both circumferential and radial deformation of the endovascular devices. Given the feasibility of achieving platelet-repelling voltages, the pulsation based piezoelectric system presents a promising solution for reducing the platelet adherence in indwelling endovascular devices without the need for passive coating or batteries, which enhances the overall effectiveness of endovascular devices.

Photoplethysmography (PPG) is an optical non-invasive measuring technique and uses a light source and a photodetector to monitor regional blood volume changes in the vessel near the skin. It is a widespread clinical application, and traditionally, PPG signals are used to monitor oxygen saturation and heart rate. However, it can be utilized to extract further valuable information such as blood pressures, cardiac outputs, autonomic functions, and various cardiovascularrelated diseases. Overall, PPG has great potential for providing a simple and convenient but versatile diagnostic tool as an alternative of traditional cardiovascular health monitoring. However, very limited studies have been performed to understand the complex physiological variability in PPG signals measured simultaneously at different body sites. In addition, current PPG devices are relatively bulky and require adhesives or fasteners to collect reliable PPG signals, which make them applicable only for specific body locations and not suitable for long-term, continuous ambulatory monitoring. In this present work, an ultrathin, flexible conformal PPG device is developed. The overall thickness of the flexible circuit is maintained less than 25 μm in order that the circuit can demonstrate a high level of flexibility and conform to the curvilinear surfaces of the skin. Multiple conformal PPG devices are laminated on forehead, wrist, or ankle to monitor PPG signals in a synchronized manner. In addition, the similar setting of conformal PPG devices is used to evaluate cardiovascular changes induced by lower body negative pressures. Overall, our finding demonstrates the feasibility of our multiple conformal PPG device network as an accurate, low-profile, and low-resource monitoring devices for cardiovascular health.

Heat detection and localization are vastly being used in various fields such as navigation systems, autonomous systems in industry, medical and research. To provide a more efficient detection and localization system, feedback capability is significant. Towards that goal, previously shown simultaneous multi-mode Dielectric Elastomer Actuator (DEA) technology can be used together with MEMS technology in a combined manner for development of an interactive sensory system with auditory and haptic feedback. By driving a certain DEA topology with low-frequency and additional high-frequency signal components it is possible to produce multiple independent outputs, like linear movement and sound generation to develop interfaces with simultaneous but independent acoustic and tactile feedback capability.

In this study, a single IR sensor is introduced to detect heat in indoor environments and the pixels data from the sensor is transformed into a 32x32 matrix for heatmap generation. The study applies array manipulation to localize and calculate an approximate distance of the target from the source based on surface temperature. A YOLOV8 model is used with a custom dataset for objects and human detection based on generated thermal images derived from our function. The integrated DEA control can adjust feedback autonomously based on the sensor field of view in real-time. The study shows an overall accuracy of more than 90% in continuous based distance estimation when evaluated with depth tracking data from a stereo camera. For detection and classification of heated objects (human, electronics, hot objects) while navigating, the accuracy is above 95%.

Although many people suffer from sleep disorders, most are undiagnosed, leading to impairments in health. However, the existing polysomnography method is not easily accessible, costly, and burdensome to patients, requiring specialized facilities and personnel. Here we report at-home portable wireless sleep sensors and wearable electronics with embedded machine learning and their applications in assessing sleep quality and detecting sleep apnea with multiple patients. Unlike the conventional system using numerous bulky sensors, the soft all-integrated wearable platform offers natural sleep at places users prefer. In a clinical study, the face-mounted patches that detect brain, eye, and muscle signals show comparable performance with polysomnography. When comparing healthy controls to sleep apnea patients, the wearable system can detect obstructive sleep apnea with an accuracy of 88.5%. Furthermore, deep learning offers automated sleep scoring, demonstrating portability and point-of-care usability. At-home wearable electronics could ensure a promising future supporting portable sleep monitoring and home healthcare.

With increasing digitization, the need for highly integrated sensor systems that ensure long-term recording of physical data is also growing. Smart materials are ideal for implementing such systems, as they have the ability to convert mechanical energies in the form of stresses, deformations and vibrations into an electrically measurable quantity and thus fulfil a sensory task. This can be achieved using the direct piezoelectric effect (the inverse or indirect piezoelectric effect can enable an actuator function). In addition, the electrical charge energy generated by the piezoelectric effect can also be fed to an electrical storage device (accumulator, capacitor, etc.) in order to supply energy to a decentrally operating system. In this case, we speak of energy harvesting. The combination of these two technical principles (sensor and energy harvesting) is particularly suitable for the design of decentralized energy-autonomous, highly integrated monitoring systems.

The best-known materials with a piezoelectric effect are ceramic or crystalline materials enabling the design of a wide variety of sensor and harvesting concepts. Due to their high young's modulus, their brittle material behavior and their high specific density, these materials are only suitable to a very limited extent for technical applications in which solutions are sought for integration into flexible systems such as textiles. Alternatives are offered by polymeric materials of which PVDF (polyvinylidene fluoride) has already been considered in several papers. However, these materials are disadvantageous in terms of transducer coefficients. More advantageous are piezoelectric electrets (also called piezoelectrets or ferroelectrets) due to their high piezoelectric coefficients and low mass density. They allow the realization of lightweight transducers with high output power.

In this paper, the results from recently completed research projects are presented and possible applications for ferroelectrets to implement sensors and energy harvesters, especially for smart wearables, are outlined.

Athletes frequently face risks like dehydration, fatigue, and heart issues due to high-intensity performances. Although there have been advancements in sports science training, a wearable system that can monitor multiple health parameters is crucial to prevent these conditions. Existing devices, often bulky and limited to single-parameter monitoring like heart rate, sweat, or skin hydration, focus mainly on performance. We present a multi-sensor wearable system incorporating a microfabricated, ultra-thin, flexible sensor. This system, consisting of mouthguards and chest patches, continuously monitors saliva osmolality, skin temperature, and cardiac function. It offers an athlete's hydration level and physiological stress in intense perspiration and heat conditions. The system's effectiveness in tracking physiological changes was proven in field tests, capturing significant increases in dehydration and physical strain during hour-long training sessions. This demonstration showcases the system's ability to detect rapid physiological changes, offering crucial data for mitigating athletic risks and aiding clinical decisions, ultimately improving medical care in sports.

In this paper, a novel soft origami tripod structure that is scalable and controllable using electrohydraulic actuators is proposed. The parallel designed structure consists of three origami legs connecting the top and bottom plates. The tripod is activated with self-unfolding legs when electrohydraulic actuators are swelled by applied voltage. Each leg has the classic origami pattern waterbomb, which serves as a spherical joint. When the actuator is activated, the legs are stretched, lifting the top plate of the soft tripod in various directions. That is, the tripod has multimodal shape morphing, including linear and tilting motions with only three electrohydraulic actuators.

We have successfully demonstrated a diaphragm-type pneumatic valve capable of amplifying electrostatic actuation and attenuating air pressure applied onto the diaphragm. When a high voltage is applied between the flexible electrode coated on top of the diaphragm and an underneath ground electrode, the electrostatic attraction induces a zipping motion of the diaphragm. The actuation of the pneumatic valve can seal an air chamber and maintain its internal pressure at a high level, which drives a circular elastomer membrane to form a bump and stimulate the skin. If the applied voltage falls below a certain threshold, air bypasses the diaphragm to the atmosphere and causes a sharp drop of the inter pressure, whose magnitude is controlled by a dedicated fluidic resistor located upstream. By manipulating pressure, the electrically-driven valve can control the movement of the membrane and the stimulation to the skin. In the prototype demonstration, structures are 3D manufactured, selectively coated with silver electrodes, and integrated to realize the proposed actuator with 1 cm³ in volume. The fabricated circular elastomer membrane of 3 mm in diameter and 0.1 mm in thickness forms a bump of 0.5 mm in height under an air pressure of 10 kPa, which requires a voltage of >472 V for the valve to maintain. While the voltage is lower than 472 V, the pressure drops and the membrane moves down. Once a voltage of >814 V is applied, it seals the chamber and forms the bump again. Therefore, haptic actuation can be generated as desired.

In the recent years triboelectric energy harvesting has gained a lot of research attention, and numerous triboelectric harvester designs have been proposed. We introduce a novel triboelectric energy harvesting architecture, where animal hair is used as the active material with a high positive charge affinity. To induce the triboelectric effect, animal hair is then brought into contact with polytetrafluoroethylene which in turn has a high negative charge affinity. In our approach, the electrodes are built as an array of individual charge collecting pins, which protrude into and interweave with the animal hair and skin and act as the net charge collector. The generators are built with two different approaches: a) by using 3D-printed structures with miniature electrode arrays and b) by using conductive fabrics arranged in a specific laminated structure. These are then tested in the laboratory in interaction with different animal hair materials with a novel methodology based on using a robotic manipulator test bed.

Implantable vascular sensors can offer advantageous alternatives to the existing invasive and repetitive procedures that provide incomplete views of vascular health. However, device manufacturability, alongside strict requirements of size, mechanics, and sensing capability, have hindered the development of implantable vascular sensors. Here, we report an implantable sensing system based upon an electronic vascular stent and printed soft sensors capable of monitoring a variety of hemodynamics and vascular conditions. Fabrication strategies, materials, and sensing designs are studied to create a flexible and miniaturized passive, wireless sensor compatible with conventional minimally invasive endovascular surgical procedures. Vascular medical stents are redesigned and a rotational laser-based micromachining process is optimized to create multi-material, 3D structures that mechanically serve as a medical stent while electronically acting as an inductor for passive sensing. Mechanical and electrical performance of the inductive stent is comprehensively characterized. Soft sensors are manufactured via multi-layered aerosol jet printing of silver nanoparticles and polymers before packaging with electronic stents. Sensing mechanisms and performance are studied to enable low-profile form factors and high sensitivity. The integrated stent and sensor system is wirelessly monitored by inductive coupling after implantation via catheter. Highlighting the adaptability of this implantable platform, we create different sets of sensing systems to target monitoring of pressure, flow, and arterial stiffness. In vitro studies demonstrate wireless sensing of vascular health. Collectively, the studies of device fabrication and sensor design provide promising strategies for vascular electronics.

In this study, we present the mechano-luminescence-optoelectronic (MLO) strip capable of DC-based strain sensing. The conceptual design of the MLO strip was presented and the MLO strip prototype was fabricated to measure tensile strains in a distributed manner. The MLO strip has three MLO-based sensor nodes along the strip. The MLO is composed of two functional constituents – the mechano-luminescent (ML) copper-doped zinc sulfide (ZnS:Cu)-embedded polydimethylsiloxane (PDMS) (ZnS:Cu-PDMS) micro-composites and the mechano-optoelectronic (MO) poly(3- hexylthiophene) (P3HT-based thin films. The ML and MO functional constituents were assembled and encased using the PDMS in a strip mold to complete the preparation of the MLO strip prototype. The MLO strip prototypes were subjected to cyclic tensile loadings while measuring DC output from the sensor nodes in the MLO strip.

Stroke-induced hemiparesis is associated with loss of mobility and independence, preventing survivors from participation in activities of daily living. Survivors can recover motor function of their paretic limbs by adhering to a rehabilitation regimen, consisting of repetitive, high-intensity exercises. In telerehabilitation, information and communication technologies are leveraged to deliver such physical therapy to patients’ homes. However, monitoring motor performance remotely remains a challenging task, especially in light of high variability of motor impairments among patients. In order to evaluate motor performance, therapists require the aid of technicians, who would analyze sensor data and produce meaningful metrics. The therapists would then provide patients with feedback, after a few days at best. To automate this process and offer patients real-time feedback, we propose to train machine learning algorithms that detect impaired movements. We test this approach with ten healthy participants who interact with a low-cost telerehabilitation platform we have previously developed. The platform engages users in bimanual training, where movement of the affected arm is supported by the unaffected arm, and relies on a Microsoft Kinect sensor to record user movement. We report the accuracy of a classification algorithm in distinguishing movements of simulated of disability from normal ones. This effort constitutes a significant step toward programmed assessment of upper-limb movements in authentic telerehabilitation paradigms.

Stroke-induced motor impairment often prevents survivors from participating in activities of daily living, adversely impacting their quality of life. Desktop delta robots such as the Novint Falcon have been utilized in various home-settings to help recover fine-motor skills. They are compact and affordable, and can provide programmable sensorimotor feedback. In spite of these favorable features, it is presently not possible to directly measure the user’s wrist angles while interacting with these robots, which undermines their prospective use in telerehabilitation as patients’ motor performance cannot be reliably assessed. Here, we propose an experimental set-up where patients strap a smartphone device to their forearm and manipulate a haptic robot. In this setting, data from inertial sensors embedded in the smartphone will be integrated with data from the robot in a classification algorithm that infers the wrist angle. To study the viability of this approach, we perform experiments with one healthy user. We fix two inertial measurement units on their body, one on their forearm and one on the back of their hand, to measure the true wrist angle as they perform a motor task with a Novint Falcon device. We train a machine learning algorithm that predicts wrist angles from a single wearable sensor and the Novint Falcon movements. This effort constitutes a step toward automatic assessment of wrist movements in fine motor telerehabilitation and could enable real-time feedback in the absence of a therapist.

This study proposed a high intensity and single-mode cross-fishnet grating based single-electron near infrared (NIR) free -electron laser (FEL). We have numerically investigated the achievable laser emission from a single electron and atop a nano-grating silicon waveguide in order to envision a chip-size free-electron laser as a potent research tool, for the first time. A single 45-keV electron generates 1.14 μm laser-like radiation at the Bragg resonance of a 31 μm long silicon grating with a 250-nm thickness and 1.23- μm period. The FEL is capable of producing a high intensity Electric field of 7.45× 10^-10 V/m, and magnetic field of 6.0× 10^-12 A/m. Besides, the FEL can generate a single-mode emission of radiation at 0.2629 PHz. This research suggests that electrons might interact with the structure more effectively by utilizing methods from both electron beam physics and nanophotonic design to create high-brightness photon sources for potential applications in the NIR wavelengths. It would also be fascinating to look deeper into the possibility of single-photon sources for quantum optics in nano-grating generated by a single keV electron.

Electronic devices for monitoring and controlling falls are currently classified into three categories: manual, automatic or intelligent. Manual devices are those characterized by being activated by mechanical activation, arising from the physical action of the user, in the face of a possible fall or emergency risk situation, and they cannot be activated with the use of the hands by individuals with reduced motor capacity, people with cognitive restrictions or bedridden individuals due to a serious immobilizing illness. Automatic devices are presented as an evolution, when compared to manual ones, since they allow the use of sensors to monitor the individual and are independent of the user's condition, or his will to carry out the monitoring. On the other hand, intelligent electronic devices, object of study of this research that was developed in a hospital environment, in addition to having all the previous advantages of the automatic device, can recognize the individual's behavior through artificial intelligence, indicating the time spent per position, trend of movements and imminence of risk conditions and/or subject to pressure sores while bedridden. After the literature review stage on the epidemiology, pathophysiology of falls, risk stratification of falls, cost of falls and currently existing solutions, the health telemetry device denominated Stakecare was developed, which integrates hardware and software. The health telemetry device constructed in this work is Stakecare device which is attached to the human body by means of an anti-allergic material, consisting of a fixation strap, a fixation system, in the anterior part of the thorax and under the human sternum bone. This position has multiple advantages over existing solutions, as in this location the device can present information regarding its functionalities to users and/or health professionals through its luminous display. The device integrates in a single portable system, light, small and easy to handle, all the sensors that are responsible for acquiring data in real time or less than 4 seconds for the reading referring to the geopositioning of the individual (angulation, rotation and acceleration), measurement of body temperature, measurement of heart rate and measurement of oxygen saturation in the blood. As it is a new telemetry technology in health, the Stakecare software also presents, in a versatile and innovative way, indicators associated with the Morse scale, Braden scale and medication control. The main result obtained with the development of Stakecare device (hardware and software) is in the electronic circuit of the device, which has a dedicated and programmable data processing unit, with an optimized algorithm developed to know and learn from the individual's behavior, using embedded artificial intelligence, which indicates the permanence time per position, trend of movements and imminence of risk conditions.

Shape memory alloys (SMA)-textile-based actuators have gained significant attention for their applications in various fields, including soft robotics and wearable devices. Nowadays, soft actuators are created using SMA and macro fiber composites (MFC). SMA is a highly nonlinear material, and textile fiber-wrapped SMA wires are employed to craft shape-morphing structures and actuation sheets through the knitting method. This process requires expertise and time, leading to high costs for producing an actuation sheet. In this research work, ABAQUS is utilized to construct an equivalent unit cell model based on linear constitutive equations for analyzing the behavior of knitted SMA-textile-based actuators. The actuation deformation of the P-loop is obtained using the user material subroutine (UMAT). Strain is the primary output focused on in this study, with elastic material properties and electric field as the input parameters. By incorporating the linear constitutive equations, the actuation of basic patterns and derived patterns is successfully compared with experimental results. The proposed model predicts a similar deformation of the actuation pattern sheets of the SMA-textile-based actuator, justifying the proposed equivalent unit cell model.

The fusion of the Internet of Things and artificial intelligence demands a broad sensor network. However, traditional sensors rely on external power sources and has challenges such as high maintenance, cost, and environmental issues. Recent research focuses on self-powering sensors, especially triboelectric nanogenerators (TENG), as promising energy harvesters. Nevertheless, conventional TENG-based force sensors are material dependent which impacts to the sensor accuracy. Addressing this, we propose the Pantograph structure-based self-powered force sensor (PF-TENG) system. PFTENG converts vertical input into horizontal movement, measuring force through peak count for material-independent accuracy. Its dynamic range adjusts via spring selection, achieving 92.7% sensing accuracy. Introducing lubricant oil extends its lifespan, demonstrating durability even after 225,000 cycles. Additionally, PF-TENG showcases potential as a tactile sensor, achieving 92% accuracy in recognizing varying Young's modulus of material. This multimodal capability makes PF-TENG promising for diverse applications. The PF-TENG system represents a significant advancement, offering precise force measurement across a wide dynamic range, non-material-dependent operation, and enhanced durability. The deep-learning approach further enhances its utility, allowing accurate tactile recognition. This research presents a novel method for developing non-material dependent TENG sensors, enabling interaction with diverse material surfaces and offering solutions in cutting-edge technology.

Triboelectric nanogenerator (TENG) is promising technology for harvesting sound input, but increasing their electrical output remains a challenge. The capacitor-based sound TENG (CS-TENG) is proposed as a capacitor-based sound triboelectric generator, which can enhance the electrical output of the device by accumulating electrical charges on its capacitor electrodes. The CS-TENG has high mechanical durability by preventing contact between the vibrating diaphragm and electrode and producing electrical output through electrostatic induction. The CS-TENG exhibits a peak open-circuit voltage of 14.24 V and a peak closed-circuit current of 0.87 μA under a 90 dB sound pressure at 200 Hz. The CS-TENG is a powerful generator that can generate significant electrical energy and function as a real-time detection sensor for various sounds.

Introduced in the 1970s, Spinal Cord Stimulator (SCS) devices have played a crucial role in managing a wide range of chronic pains, particularly back and leg pain. Currently, cylindrical and paddle leads are two primary types of leads widely used for pain management. Cylindrical leads, due to their small size, are susceptible to movement and migration, leading to device displacement and associated complications that often necessitate additional surgical interventions. On the other hand, paddle leads offer a larger surface area and secure placement but require a relatively large incision for device placement. To address these limitations, a new SCS device has been developed that contains a low-profile, deployable, and retrievable. This device is able to collapse into a 14-gauge needle (1.5-1.6 𝑚𝑚 in diameter), and then expand into a paddle-shape lead in the affected site after the deployment. Using advanced manufacturing processes, the first prototype is fabricated, and the deployment procedure is validated. This novel SCS design effectively prevents device dislocation and migration, while also providing a larger surface area for minimally invasive pain management.

Electro-ionic soft actuators have the advantages of being possible to drive at low voltage and to operate in the air by using ionic liquid. However, they have a disadvantage of slow response. This paper proposes to accelerate electro-ionic soft actuators by feedforward control. Feedforward control can automatically generate online pulse-shaped input signals from any reference signals and is easy to implement. The experimental results show that the feedforward control can automatically generate control inputs for any references and achieve 2 times faster than the no-control case. In addition, it was found that the control performance was significantly degraded when a voltage limit was set to protect the actuator.

Outdoor workers, such as construction workers, are exposed to the risk of heat-related illnesses (HRIs) due to prolonged heat stress and heavy labor. Heat-related illnesses include heat stroke, heat exhaustion, heavy dehydration, and the like, which can lead to highly dangerous accidents on work sites. Thus, the prevention of HRIs is crucial. To address this, we developed wireless biopatches that can measure various physiological signals in real time, ensuring the worker's convenience. The biopatch directly monitors electrocardiogram (ECG), 3-axis acceleration, skin impedance, photoplethysmography (PPG), and skin temperature. It is designed as a rigid-flex system to ensure mechanical reliability and maintain conformal contact with the skin. The biopatch does not impede the workers' tasks with its small form factor. The developed biopatch was attached to the subject’s chest, allowing continuous physiological signal collection in real-time over a full working period (over 5 hours), displayed on a mobile phone via Bluetooth. These physiological signals can serve as biomarkers for diagnosing HRIs. With this approach, the biopatch shows a high potential for preventing HRIs in outdoor workers.

The goal of the present work is to create a miniature 2D light scanning device without any moving parts using integrated electro-optic (EO) liquid crystal (LC) material. The design is based on changing the propagation direction of a light beam when it is incident to an electro-optic medium with a voltage-controlled index of refraction. To achieve 2D beam steering and scanning, the device is designed in two stages. For horizontal beam steering, a LC prism (thickness = 10 μm) created between two glasses is used to deflect beam by refraction due to change in refractive index of LC. For vertical beam steering, a virtual prism is created between two glasses by offsetting top and bottom electrodes. When an electric field is applied to the electrodes, LC directors create a virtual prism due to physical offset between top and bottom electrodes help to achieve beam deflection in vertical direction. In this work, a simulation study is conducted on the proposed design to achieve 2D deflection of laser beam (λ=632 nm). According to Snell’s law, theoretically, a maximum horizontal deflection of 10.52° is achieved at a prism angle, and incident angle of 66.1° and 21.99° respectively. Whereas through a simulation study, maximum horizontal deflection of 34° and maximum vertical deflection of 13° is achieved at given incident angle. This low-cost and lightweight optical scanner can fit inside a tube with a diameter of less than 5 mm and can be implemented for augmented reality (AR), virtual reality (VR), or standalone microdisplay applications.

The thermoelectric generator (TEG) is commonly used to harvest or scavenge the remnant energy from waste heat sources, such as automotive exhaust systems, cooling line of power plants, ocean temperature difference, human body, and industrial processes. The performance of TEG depends on the thermoelectric material and its structural configuration. To obtain the maximum power from TEG module, the optimal design of heat exchanger is required to realize the full potential of power generating system. The internal structure of heat exchanger plays a critical role to determine the efficiency of TEG by enhancing heat transfer between the hot and cold sides of the TEG module. We studied the effect of internal fin structure in heat exchanger with hot water feeding condition to obtain the best performance of TEG module array by using computational simulations and compared with the experimental results.