A wirelessly programmable, skin-integrated thermo-haptic stimulator system for virtual reality.

Sensations of heat and touch produced by receptors in the skin are of essential importance for perceptions of the physical environment, with a particularly powerful role in interpersonal interactions. Advances in technologies for replicating these sensations in a programmable manner have the potential not only to enhance virtual/augmented reality environments but they also hold promise in medical applications for individuals with amputations or impaired sensory function. Engineering challenges are in achieving interfaces with precise spatial resolution, power-efficient operation, wide dynamic range, and fast temporal responses in both thermal and in physical modulation, with forms that can extend over large regions of the body. This paper introduces a wireless, skin-compatible interface for thermo-haptic modulation designed to address some of these challenges, with the ability to deliver programmable patterns of enhanced vibrational displacement and high-speed thermal stimulation. Experimental and computational investigations quantify the thermal and mechanical efficiency of a vertically stacked design layout in the thermo-haptic stimulators that also supports real-time, closed-loop control mechanisms. The platform is effective in conveying thermal and physical information through the skin, as demonstrated in the control of robotic prosthetics and in interactions with pressure/temperature-sensitive touch displays.

E-Tattoos: Toward Functional but Imperceptible Interfacing with Human Skin.

The human body continuously emits physiological and psychological information from head to toe. Wearable electronics capable of noninvasively and accurately digitizing this information without compromising user comfort or mobility have the potential to revolutionize telemedicine, mobile health, and both human-machine or human-metaverse interactions. However, state-of-the-art wearable electronics face limitations regarding wearability and functionality due to the mechanical incompatibility between conventional rigid, planar electronics and soft, curvy human skin surfaces. E-Tattoos, a unique type of wearable electronics, are defined by their ultrathin and skin-soft characteristics, which enable noninvasive and comfortable lamination on human skin surfaces without causing obstruction or even mechanical perception. This review article offers an exhaustive exploration of e-tattoos, accounting for their materials, structures, manufacturing processes, properties, functionalities, applications, and remaining challenges. We begin by summarizing the properties of human skin and their effects on signal transmission across the e-tattoo-skin interface. Following this is a discussion of the materials, structural designs, manufacturing, and skin attachment processes of e-tattoos. We classify e-tattoo functionalities into electrical, mechanical, optical, thermal, and chemical sensing, as well as wound healing and other treatments. After discussing energy harvesting and storage capabilities, we outline strategies for the system integration of wireless e-tattoos. In the end, we offer personal perspectives on the remaining challenges and future opportunities in the field.

Closed-loop network of skin-interfaced wireless devices for quantifying vocal fatigue and providing user feedback.

Vocal fatigue is a measurable form of performance fatigue resulting from overuse of the voice and is characterized by negative vocal adaptation. Vocal dose refers to cumulative exposure of the vocal fold tissue to vibration. Professionals with high vocal demands, such as singers and teachers, are especially prone to vocal fatigue. Failure to adjust habits can lead to compensatory lapses in vocal technique and an increased risk of vocal fold injury. Quantifying and recording vocal dose to inform individuals about potential overuse is an important step toward mitigating vocal fatigue. Previous work establishes vocal dosimetry methods, that is, processes to quantify vocal fold vibration dose but with bulky, wired devices that are not amenable to continuous use during natural daily activities; these previously reported systems also provide limited mechanisms for real-time user feedback. This study introduces a soft, wireless, skin-conformal technology that gently mounts on the upper chest to capture vibratory responses associated with vocalization in a manner that is immune to ambient noises. Pairing with a separate, wirelessly linked device supports haptic feedback to the user based on quantitative thresholds in vocal usage. A machine learning-based approach enables precise vocal dosimetry from the recorded data, to support personalized, real-time quantitation and feedback. These systems have strong potential to guide healthy behaviors in vocal use.

Electronic Skin: Opportunities and Challenges in Convergence with Machine Learning.

Recent advancements in soft electronic skin (e-skin) have led to the development of human-like devices that reproduce the skin's functions and physical attributes. These devices are being explored for applications in robotic prostheses as well as for collecting biopotentials for disease diagnosis and treatment, as exemplified by biomedical e-skins. More recently, machine learning (ML) has been utilized to enhance device control accuracy and data processing efficiency. The convergence of e-skin technologies with ML is promoting their translation into clinical practice, especially in healthcare. This review highlights the latest developments in ML-reinforced e-skin devices for robotic prostheses and biomedical instrumentations. We first describe technological breakthroughs in state-of-the-art e-skin devices, emphasizing technologies that achieve skin-like properties. We then introduce ML methods adopted for control optimization and pattern recognition, followed by practical applications that converge the two technologies. Lastly, we briefly discuss the challenges this interdisciplinary research encounters in its clinical and industrial transition.

Dynamics of plosive consonants via imaging, computations, and soft electronics.

A quantitative understanding of the coupled dynamics of flow and particles in aerosol and droplet transmission associated with speech remains elusive. Here, we summarize an effort that integrates insights into flow-particle dynamics induced by the production plosive sounds during speech with skin-integrated electronic systems for monitoring the production of these sounds. In particular, we uncover diffusive and ballistic regimes separated by a threshold particle size and characterize the Lagrangian acceleration and pair dispersion. Lagrangian dynamics of the particles in the diffusive regime exhibit features of isotropic turbulence. These fundamental findings highlight the value in skin-interfaced wireless sensors for continuously measuring critical speech patterns in clinical settings, work environments, and the home, based on unique neck biomechanics associated with the generation of plosive sounds. We introduce a wireless, soft device that captures these motions to enable detection of plosive sounds in multiple languages through a convolutional neural network approach. This work spans fundamental flow-particle physics to soft electronic technology, with implications in monitoring and studying critical speech patterns associated with aerosol and droplet transmissions relevant to the spread of infectious diseases.

Wireless, soft electronics for rapid, multisensor measurements of hydration levels in healthy and diseased skin.

Precise, quantitative measurements of the hydration status of skin can yield important insights into dermatological health and skin structure and function, with additional relevance to essential processes of thermoregulation and other features of basic physiology. Existing tools for determining skin water content exploit surrogate electrical assessments performed with bulky, rigid, and expensive instruments that are difficult to use in a repeatable manner. Recent alternatives exploit thermal measurements using soft wireless devices that adhere gently and noninvasively to the surface of the skin, but with limited operating range (∼1 cm) and high sensitivity to subtle environmental fluctuations. This paper introduces a set of ideas and technologies that overcome these drawbacks to enable high-speed, robust, long-range automated measurements of thermal transport properties via a miniaturized, multisensor module controlled by a long-range (∼10 m) Bluetooth Low Energy system on a chip, with a graphical user interface to standard smartphones. Soft contact to the surface of the skin, with almost zero user burden, yields recordings that can be quantitatively connected to hydration levels of both the epidermis and dermis, using computational modeling techniques, with high levels of repeatability and insensitivity to ambient fluctuations in temperature. Systematic studies of polymers in layered configurations similar to those of human skin, of porcine skin with known levels of hydration, and of human subjects with benchmarks against clinical devices validate the measurement approach and associated sensor hardware. The results support capabilities in characterizing skin barrier function, assessing severity of skin diseases, and evaluating cosmetic and medication efficacy, for use in the clinic or in the home.

Automated, multiparametric monitoring of respiratory biomarkers and vital signs in clinical and home settings for COVID-19 patients.

Capabilities in continuous monitoring of key physiological parameters of disease have never been more important than in the context of the global COVID-19 pandemic. Soft, skin-mounted electronics that incorporate high-bandwidth, miniaturized motion sensors enable digital, wireless measurements of mechanoacoustic (MA) signatures of both core vital signs (heart rate, respiratory rate, and temperature) and underexplored biomarkers (coughing count) with high fidelity and immunity to ambient noises. This paper summarizes an effort that integrates such MA sensors with a cloud data infrastructure and a set of analytics approaches based on digital filtering and convolutional neural networks for monitoring of COVID-19 infections in sick and healthy individuals in the hospital and the home. Unique features are in quantitative measurements of coughing and other vocal events, as indicators of both disease and infectiousness. Systematic imaging studies demonstrate correlations between the time and intensity of coughing, speaking, and laughing and the total droplet production, as an approximate indicator of the probability for disease spread. The sensors, deployed on COVID-19 patients along with healthy controls in both inpatient and home settings, record coughing frequency and intensity continuously, along with a collection of other biometrics. The results indicate a decaying trend of coughing frequency and intensity through the course of disease recovery, but with wide variations across patient populations. The methodology creates opportunities to study patterns in biometrics across individuals and among different demographic groups.

Miniaturized wireless, skin-integrated sensor networks for quantifying full-body movement behaviors and vital signs in infants.

Early identification of atypical infant movement behaviors consistent with underlying neuromotor pathologies can expedite timely enrollment in therapeutic interventions that exploit inherent neuroplasticity to promote recovery. Traditional neuromotor assessments rely on qualitative evaluations performed by specially trained personnel, mostly available in tertiary medical centers or specialized facilities. Such approaches are high in cost, require geographic proximity to advanced healthcare resources, and yield mostly qualitative insight. This paper introduces a simple, low-cost alternative in the form of a technology customized for quantitatively capturing continuous, full-body kinematics of infants during free living conditions at home or in clinical settings while simultaneously recording essential vital signs data. The system consists of a wireless network of small, flexible inertial sensors placed at strategic locations across the body and operated in a wide-bandwidth and time-synchronized fashion. The data serve as the basis for reconstructing three-dimensional motions in avatar form without the need for video recordings and associated privacy concerns, for remote visual assessments by experts. These quantitative measurements can also be presented in graphical format and analyzed with machine-learning techniques, with potential to automate and systematize traditional motor assessments. Clinical implementations with infants at low and at elevated risks for atypical neuromotor development illustrates application of this system in quantitative and semiquantitative assessments of patterns of gross motor skills, along with body temperature, heart rate, and respiratory rate, from long-term and follow-up measurements over a 3-mo period following birth. The engineering aspects are compatible for scaled deployment, with the potential to improve health outcomes for children worldwide via early, pragmatic detection methods.

Comprehensive pregnancy monitoring with a network of wireless, soft, and flexible sensors in high- and low-resource health settings.

Vital signs monitoring is a fundamental component of ensuring the health and safety of women and newborns during pregnancy, labor, and childbirth. This monitoring is often the first step in early detection of pregnancy abnormalities, providing an opportunity for prompt, effective intervention to prevent maternal and neonatal morbidity and mortality. Contemporary pregnancy monitoring systems require numerous devices wired to large base units; at least five separate devices with distinct user interfaces are commonly used to detect uterine contractility, maternal blood oxygenation, temperature, heart rate, blood pressure, and fetal heart rate. Current monitoring technologies are expensive and complex with implementation challenges in low-resource settings where maternal morbidity and mortality is the greatest. We present an integrated monitoring platform leveraging advanced flexible electronics, wireless connectivity, and compatibility with a wide range of low-cost mobile devices. Three flexible, soft, and low-profile sensors offer comprehensive vital signs monitoring for both women and fetuses with time-synchronized operation, including advanced parameters such as continuous cuffless blood pressure, electrohysterography-derived uterine monitoring, and automated body position classification. Successful field trials of pregnant women between 25 and 41 wk of gestation in both high-resource settings (n = 91) and low-resource settings (n = 485) demonstrate the system's performance, usability, and safety.

Soft, skin-interfaced microfluidic systems with integrated immunoassays, fluorometric sensors, and impedance measurement capabilities.

Soft microfluidic systems that capture, store, and perform biomarker analysis of microliter volumes of sweat, in situ, as it emerges from the surface of the skin, represent an emerging class of wearable technology with powerful capabilities that complement those of traditional biophysical sensing devices. Recent work establishes applications in the real-time characterization of sweat dynamics and sweat chemistry in the context of sports performance and healthcare diagnostics. This paper presents a collection of advances in biochemical sensors and microfluidic designs that support multimodal operation in the monitoring of physiological signatures directly correlated to physical and mental stresses. These wireless, battery-free, skin-interfaced devices combine lateral flow immunoassays for cortisol, fluorometric assays for glucose and ascorbic acid (vitamin C), and digital tracking of skin galvanic responses. Systematic benchtop evaluations and field studies on human subjects highlight the key features of this platform for the continuous, noninvasive monitoring of biochemical and biophysical correlates of the stress state.

Encephalitis and antibodies to dipeptidyl-peptidase-like protein-6, a subunit of Kv4.2 potassium channels.

OBJECTIVE: To report a novel cell surface autoantigen of encephalitis that is a critical regulatory subunit of the Kv4.2 potassium channels. METHODS: Four patients with encephalitis of unclear etiology and antibodies with a similar pattern of neuropil brain immunostaining were selected for autoantigen characterization. Techniques included immunoprecipitation, mass spectrometry, cell-base experiments with Kv4.2 and several dipeptidyl-peptidase-like protein-6 (DPPX) plasmid constructs, and comparative brain immunostaining of wild-type and DPPX-null mice. RESULTS: Immunoprecipitation studies identified DPPX as the target autoantigen. A cell-based assay confirmed that all 4 patients, but not 210 controls, had DPPX antibodies. Symptoms included agitation, confusion, myoclonus, tremor, and seizures (1 case with prominent startle response). All patients had pleocytosis, and 3 had severe prodromal diarrhea of unknown etiology. Given that DPPX tunes up the Kv4.2 potassium channels (involved in somatodendritic signal integration and attenuation of dendritic back-propagation of action potentials), we determined the epitope distribution in DPPX, DPP10 (a protein homologous to DPPX), and Kv4.2. Patients' antibodies were found to be specific for DPPX, without reacting with DPP10 or Kv4.2. The unexplained diarrhea led to a demonstration of a robust expression of DPPX in the myenteric plexus, which strongly reacted with patients' antibodies. The course of neuropsychiatric symptoms was prolonged and often associated with relapses during decreasing immunotherapy. Long-term follow-up showed substantial improvement in 3 patients (1 was lost to follow-up). INTERPRETATION: Antibodies to DPPX are associated with a protracted encephalitis characterized by central nervous system hyperexcitability (agitation, myoclonus, tremor, seizures), pleocytosis, and frequent diarrhea at symptom onset. The disorder is potentially treatable with immunotherapy.

Materials and Device Designs for Wireless Monitoring of Temperature and Thermal Transport Properties of Wound Beds during Healing.

Chronic wounds represent a major health risk for diabetic patients. Regeneration of such wounds requires regular medical treatments over periods that can extend for several months or more. Schemes for monitoring the healing process can provide important feedback to the patient and caregiver. Although qualitative indicators such as malodor or fever can provide some indirect information, quantitative measurements of the wound bed have the potential to yield important insights. The work presented here introduces materials and engineering designs for a wireless system that captures spatio-temporal temperature and thermal transport information across the wound continuously throughout the healing process. Systematic experimental and computational studies establish the materials aspects and basic capabilities of this technology. In vivo studies reveal that both the temperature and the changes in this quantity offer information on wound status, with indications of initial exothermic reactions and mechanisms of scar tissue formation. Bioresorbable materials serve as the foundations for versions of this device that create possibilities for monitoring on and within the wound site, in a way that bypasses the risks of physical removal.

A Novel Method for Tracking Neck Motions Using a Skin-Conformable Wireless Accelerometer: A Pilot Study.

Introduction: Cervical spine disease is a leading cause of pain and disability. Degenerative conditions of the spine can result in neurologic compression of the cervical spinal cord or nerve roots and may be surgically treated with an anterior cervical discectomy and fusion (ACDF) in up to 137,000 people per year in the United States. A common sequelae of ACDF is reduced cervical range of motion (CROM) with patient-based complaints of stiffness and neck pain. Currently, tools for assessment of CROM are manual, subjective, and only intermittently utilized during doctor or physical therapy visits. We propose a skin-mountable acousto-mechanic sensor (ADvanced Acousto-Mechanic sensor; ADAM) as a tool for continuous neck motion monitoring in postoperative ACDF patients. We have developed and validated a machine learning neck motion classification algorithm to differentiate between eight neck motions (right/left rotation, right/left lateral bending, flexion, extension, retraction, protraction) in healthy normal subjects and patients. Methods: Sensor data from 12 healthy normal subjects and 5 patients were used to develop and validate a Convolutional Neural Network (CNN). Results: An average algorithm accuracy of 80.0 ± 3.8% was obtained for healthy normal subjects (94% for right rotation, 98% for left rotation, 65% for right lateral bending, 87% for left lateral bending, 89% for flexion, 77% for extension, 50% for retraction, 84% for protraction). An average accuracy of 67.5 ± 5.8% was obtained for patients. Discussion: ADAM, with our algorithm, may serve as a rehabilitation tool for neck motion monitoring in postoperative ACDF patients. Sensor-captured vital signs and other events (extubation, vocalization, physical therapy, walking) are potential metrics to be incorporated into our algorithm to offer more holistic monitoring of patients after cervical spine surgery.

Development of a miniaturized mechanoacoustic sensor for continuous, objective cough detection, characterization and physiologic monitoring in children with cystic fibrosis.

Cough is an important symptom in children with acute and chronic respiratory disease. Daily cough is common in Cystic Fibrosis (CF) and increased cough is a symptom of pulmonary exacerbation. To date, cough assessment is primarily subjective in clinical practice and research. Attempts to develop objective, automatic cough counting tools have faced reliability issues in noisy environments and practical barriers limiting long-term use. This single-center pilot study evaluated usability, acceptability and performance of a mechanoacoustic sensor (MAS), previously used for cough classification in adults, in 36 children with CF over brief and multi-day periods in four cohorts. Children whose health was at baseline and who had symptoms of pulmonary exacerbation were included. We trained, validated, and deployed custom deep learning algorithms for accurate cough detection and classification from other vocalization or artifacts with an overall area under the receiver-operator characteristic curve (AUROC) of 0.96 and average precision (AP) of 0.93. Child and parent feedback led to a redesign of the MAS towards a smaller, more discreet device acceptable for daily use in children. Additional improvements optimized power efficiency and data management. The MAS's ability to objectively measure cough and other physiologic signals across clinic, hospital, and home settings is demonstrated, particularly aided by an AUROC of 0.97 and AP of 0.96 for motion artifact rejection. Examples of cough frequency and physiologic parameter correlations with participant-reported outcomes and clinical measurements for individual patients are presented. The MAS is a promising tool in objective longitudinal evaluation of cough in children with CF.

Improvement of textural and sensory characteristics of aged rice using hydrothermal treatment with xanthan gum.

Aged rice (AR) was mildly heated in aqueous dispersions containing different amounts of xanthan gum (Xan) at 60 °C for 1 h, and then dried in a humidity chamber (50 °C, 80% RH) for 12 h. The AR kernels treated without Xan showed a coarse surface with many pores after cooking, whereas the same rice treated with Xan showed a smooth and uniform surface. Prior to the treatment, the cooked AR was harder and less sticky than the cooked fresh rice (FR). The hydrothermal treatment softened the cooked AR although did not change its adhesiveness. The same treatment in the presence of Xan could increase the adhesiveness of AR, making the textural characteristics of AR similar to those of FR. Sensory evaluation revealed that the mild heat treatment in the presence of Xan restored the eating quality and acceptability of cooked AR which had been lost by aging. Supplementary Information: The online version contains supplementary material available at 10.1007/s10068-023-01306-0.

Responsive materials and mechanisms as thermal safety systems for skin-interfaced electronic devices.

Soft, wireless physiological sensors that gently adhere to the skin are capable of continuous clinical-grade health monitoring in hospital and/or home settings, of particular value to critically ill infants and other vulnerable patients, but they present risks for injury upon thermal failure. This paper introduces an active materials approach that automatically minimizes such risks, to complement traditional schemes that rely on integrated sensors and electronic control circuits. The strategy exploits thin, flexible bladders that contain small volumes of liquid with boiling points a few degrees above body temperature. When the heat exceeds the safe range, vaporization rapidly forms highly effective, thermally insulating structures and delaminates the device from the skin, thereby eliminating any danger to the skin. Experimental and computational thermomechanical studies and demonstrations in a skin-interfaced mechano-acoustic sensor illustrate the effectiveness of this simple thermal safety system and suggest its applicability to nearly any class of skin-integrated device technology.

Simple, miniaturized biosensors for wireless mapping of thermoregulatory responses.

Temperature is the most commonly collected vital sign in all of clinical medicine; it plays a critical role in care decisions related to topics ranging from infection to inflammation, sleep, and fertility. Most assessments of body temperature occur at isolated anatomical locations (e.g. axilla, rectum, temporal artery, or oral cavity). Even this relatively primitive mode for monitoring can be challenging with vulnerable patient populations due to physical encumbrances and artifacts associated with the sizes, weights, shapes and mechanical properties of the sensors and, for continuous monitoring, their hard-wired interfaces to data collection units. Here, we introduce a simple, miniaturized, lightweight sensor as a wireless alternative, designed to address demanding applications such as those related to the care of neonates in high ambient humidity environments with radiant heating found in incubators in intensive care units. Such devices can be deployed onto specific anatomical locations of premature infants for homeostatic assessments. The estimated core body temperature aligns, to within 0.05 °C, with clinical grade, wired sensors, consistent with regulatory medical device requirements. Time-synchronized, multi-device operation across multiple body locations supports continuous, full-body measurements of spatio-temporal variations in temperature and additional modes of determining tissue health status in the context of sepsis detection and various environmental exposures. In addition to thermal sensing, these same devices support measurements of a range of other essential vital signs derived from thermo-mechanical coupling to the skin, for applications ranging from neonatal and infant care to sleep medicine and even pulmonary medicine.

Wireless broadband acousto-mechanical sensing system for continuous physiological monitoring.

The human body generates various forms of subtle, broadband acousto-mechanical signals that contain information on cardiorespiratory and gastrointestinal health with potential application for continuous physiological monitoring. Existing device options, ranging from digital stethoscopes to inertial measurement units, offer useful capabilities but have disadvantages such as restricted measurement locations that prevent continuous, longitudinal tracking and that constrain their use to controlled environments. Here we present a wireless, broadband acousto-mechanical sensing network that circumvents these limitations and provides information on processes including slow movements within the body, digestive activity, respiratory sounds and cardiac cycles, all with clinical grade accuracy and independent of artifacts from ambient sounds. This system can also perform spatiotemporal mapping of the dynamics of gastrointestinal processes and airflow into and out of the lungs. To demonstrate the capabilities of this system we used it to monitor constrained respiratory airflow and intestinal motility in neonates in the neonatal intensive care unit (n = 15), and to assess regional lung function in patients undergoing thoracic surgery (n = 55). This broadband acousto-mechanical sensing system holds the potential to help mitigate cardiorespiratory instability and manage disease progression in patients through continuous monitoring of physiological signals, in both the clinical and nonclinical setting.

Highly efficient assay of circulating tumor cells by selective sedimentation with a density gradient medium and microfiltration from whole blood.

Isolation of circulating tumor cells (CTCs) by size exclusion can yield poor purity and low recovery rates, due to large variations in size of CTCs, which may overlap with leukocytes and render size-based filtration methods unreliable. This report presents a very sensitive, selective, fast, and novel method for isolation and detection of CTCs. Our assay platform consists of three steps: (i) capturing CTCs with anti-EpCAM conjugated microbeads, (ii) removal of unwanted hematologic cells (e.g., leukocytes, erythrocytes, etc.) by selective sedimentation of CTCs within a density gradient medium, and (iii) simple microfiltration to collect these cells. To demonstrate the efficacy of this assay, MCF-7 breast cancer cells (average diameter, 24 µm) and DMS-79 small cell lung cancer cells (average diameter, 10 µm) were used to model CTCs. We investigated the relative sedimentation rates for various cells and/or particles, such as CTCs conjugated with different types of microbeads, leukocytes, and erythrocytes, in order to maximize differences in the physical properties. We observed that greater than 99% of leukocytes in whole blood were effectively removed at an optimal centrifugal force, due to differences in their sedimentation rates, yielding a much purer sample compared to other filter-based methods. We also investigated not only the effect of filtration conditions on recovery rates and sample purity but also the sensitivity of our assay platform. Our results showed a near perfect recovery rate (~99%) for MCF-7 cells and very high recovery rate (~89%) for DMS-79 cells, with minimal amounts of leukocytes present.