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

An implantable device for wireless monitoring of diverse physio-behavioral characteristics in freely behaving small animals and interacting groups

Comprehensive, continuous quantitative monitoring of intricately orchestrated physiological processes and behavioral states in living organisms can yield essential data for elucidating the function of neural circuits under healthy and diseased conditions, for defining the effects of potential drugs and treatments, and for tracking disease progression and recovery. Here, we report a wireless, battery-free implantable device and a set of associated algorithms that enable continuous, multiparametric physio-behavioral monitoring in freely behaving small animals and interacting groups. Through advanced analytics approaches applied to mechano-acoustic signals of diverse body processes, the device yields heart rate, respiratory rate, physical activity, temperature, and behavioral states. Demonstrations in pharmacological, locomotor, and acute and social stress tests and in optogenetic studies offer unique insights into the coordination of physio-behavioral characteristics associated with healthy and perturbed states. This technology has broad utility in neuroscience, physiology, behavior, and other areas that rely on studies of freely moving, small animal models.

Skin-interfacing wearable biosensors for smart health monitoring of infants and neonates

Health monitoring of infant patients in intensive care can be especially strenuous for both the patient and their caregiver, as testing setups involve a tangle of electrodes, probes, and catheters that keep the patient bedridden. This has typically involved expensive and imposing machines, to track physiological metrics such as heart rate, respiration rate, temperature, blood oxygen saturation, blood pressure, and ion concentrations. However, in the past couple of decades, research advancements have propelled a world of soft, wearable, and non-invasive systems to supersede current practices. This paper summarizes the latest advancements in neonatal wearable systems and the different approaches to each branch of physiological monitoring, with an emphasis on smart skin-interfaced wearables. Weaknesses and shortfalls are also addressed, with some guidelines provided to help drive the further research needed.

Flexible sensor-based biomechanical evaluation of low-back exoskeleton use in lifting

This study aimed to establish an ambulatory field-friendly system based on miniaturised wireless flexible sensors for studying the biomechanics of human-exoskeleton interactions. Twelve healthy adults performed symmetric lifting with and without a passive low-back exoskeleton, while their movements were tracked using both a flexible sensor system and a conventional motion capture (MoCap) system synchronously. Novel algorithms were developed to convert the raw acceleration, gyroscope, and biopotential signals from the flexible sensors into kinematic and dynamic measures. Results showed that these measures were highly correlated with those obtained from the MoCap system and discerned the effects of the exoskeleton, including increased peak lumbar flexion, decreased peak hip flexion, and decreased lumbar flexion moment and back muscle activities. The study demonstrated the promise of an integrated flexible sensor-based system for biomechanics and ergonomics field studies as well as the efficacy of exoskeleton in relieving the low-back stress associated with manual lifting.

Scalable and Multifunctional Polyurethane/MXene/Carbon Nanotube-Based Fabric Sensor toward Baby Healthcare

Continuous monitoring of physiological health status and effective protection against external hazards is an indispensable aspect of healthcare management for critically vulnerable populations, particularly for infants or babies. So, the exploration of all-in-one devices remains critical to avoiding their injury and illness. The integration of multiple properties such as sensing, electromagnetic protection, warming/cooling, and water/bacterial repellence into a common fabric is no doubt a promising solution to coping with diverse application scenarios. However, achieving simultaneous integration in an effective and durable fashion faces huge challenges. Herein, multifunctional fabric was achieved by sequentially coating MXene, carbon nanotubes (CNTs), and self-healing polyurethane (PU) onto cotton fabric. The outstanding conductivity of MXene and CNTs as well as the self-healing ability of PU synergistically enable a flexible, breathable, protective, and sensing fabric with a good durability. It could detect the body motions like bending of the finger, elbow, wrist, and knee, with a high gauge factor of 8.78 and fast response. Moreover, this sensing fabric could protect the wearers against electromagnetic waves and bacteria, delivering a minimum reflection loss of -57.6 dB at 7.6 GHz and high bacterial inhibition efficiency due to the incorporation of MXene and polyethylenimine. Besides, the electrothermal performance of carbonaceous materials enables them to act as a heater for body warmth. The synergistic design of this multifunctional textile offers a promising strategy for producing advanced smart textiles, holding great promise in infant or baby healthcare.

Advanced Electrode Technologies for Noninvasive Brain-Computer Interfaces

Brain-computer interfaces (BCIs) have garnered significant attention in recent years due to their potential applications in medical, assistive, and communication technologies. Building on this, noninvasive BCIs stand out as they provide a safe and user-friendly method for interacting with the human brain. In this work, we provide a comprehensive overview of the latest developments and advancements in material, design, and application of noninvasive BCIs electrode technology. We also explore the challenges and limitations currently faced by noninvasive BCI electrode technology and sketch out the technological roadmap from three dimensions: Materials and Design; Performances; Mode and Function. We aim to unite research efforts within the field of noninvasive BCI electrode technology, focusing on the consolidation of shared goals and fostering integrated development strategies among a diverse array of multidisciplinary researchers.

Protocol for a randomized controlled trial to evaluate a year-long (NICU-to-home) evidence-based, high dose physical therapy intervention in infants at risk of neuromotor delay

INTRODUCTION

Developmental disabilities and neuromotor delay adversely affect long-term neuromuscular function and quality of life. Current evidence suggests that early therapeutic intervention reduces the severity of motor delay by harnessing neuroplastic potential during infancy. To date, most early therapeutic intervention trials are of limited duration and do not begin soon after birth and thus do not take full advantage of early neuroplasticity. The Corbett Ryan-Northwestern-Shirley Ryan AbilityLab-Lurie Children's Infant Early Detection, Intervention and Prevention Project (Project Corbett Ryan) is a multi-site longitudinal randomized controlled trial to evaluate the efficacy of an evidence-based physical therapy intervention initiated in the neonatal intensive care unit (NICU) and continuing to 12 months of age (corrected when applicable). The study integrates five key principles: active learning, environmental enrichment, caregiver engagement, a strengths-based approach, and high dosage (ClinicalTrials.gov identifier NCT05568264).

METHODS

We will recruit 192 infants at risk for neuromotor delay who were admitted to the NICU. Infants will be randomized to either a standard-of-care group or an intervention group; infants in both groups will have access to standard-of-care services. The intervention is initiated in the NICU and continues in the infant's home until 12 months of age. Participants will receive twice-weekly physical therapy sessions and caregiver-guided daily activities, assigned by the therapist, targeting collaboratively identified goals. We will use various standardized clinical assessments (General Movement Assessment; Bayley Scales of Infant and Toddler Development, 4th Edition (Bayley-4); Test of Infant Motor Performance; Pediatric Quality of Life Inventory Family Impact Module; Alberta Infant Motor Scale; Neurological, Sensory, Motor, Developmental Assessment; Hammersmith Infant Neurological Examination) as well as novel technology-based tools (wearable sensors, video-based pose estimation) to evaluate neuromotor status and development throughout the course of the study. The primary outcome is the Bayley-4 motor score at 12 months; we will compare scores in infants receiving the intervention vs. standard-of-care therapy.

Electronic exoneuron based on liquid metal for the quantitative sensing of the augmented somatosensory system

The increasing demands in augmented somatosensory have promoted quantitative sensing to be an emerging need for athletic training/performance evaluation and physical rehabilitation. Neurons for the somatosensory system in the human body can capture the information of movements in time but only qualitatively. This work presents an electronic Exo-neuron (EEN) that can spread throughout the limbs for realizing augmented somatosensory by recording both muscular activity and joint motion quantitatively without site constraints or drift instability, even in strenuous activities. Simply based on low-cost liquid metal and clinically used adhesive elastomer, the EEN could be easily fabricated in large areas for limbs. It is thin (~120 μm), soft, stretchable (>500%), and conformal and further shows wide applications in sports, rehabilitation, health care, and entertainment.

A soft, bioinspired artificial lymphatic system for interactive ascites transfer

Low-flow removal of refractory ascites is critical to treating cirrhosis and digestive system tumor, and thus, commercial ascites pump emerged lately. The rigid structure of clinically available pumps rises complication rate and lack of flow rate monitoring hinders early warning of abnormalities. Herein, a soft artificial system was proposed inspired by lymph for interactive ascites transfer with great biocompatibility. The implantable system is composed of pump cavity, valves and tubes, which are soft and flexible made by silica gel. Therefore, the system possesses similar modulus to tissues and can naturally fit surrounding tissues. The cavity with magnetic tablet embedded is driven by extracorporeal magnetic field. Subsequently, the system can drain ascites with a top speed of 23 mL min-1, much higher than that of natural lymphatic system and state-of-art devices. Moreover, integrated flexible sensors enable wireless, real-time flow rate monitoring, serving as proof of treatment adjustment, detection and locating of malfunction at early stage. The liver function of experimental objects was improved, and no severe complications occurred for 4 weeks, which proved its safety and benefit to treatment. This artificial lymphatic system can serve as a bridge to recovery and pave the way for further clinical research.

Continuous sensing and quantification of body motion in infants: A systematic review

Abnormal body motion in infants may be associated with neurodevelopmental delay or critical illness. In contrast to continuous patient monitoring of the basic vitals, the body motion of infants is only determined by discrete periodic clinical observations of caregivers, leaving the infants unattended for observation for a longer time. One step to fill this gap is to introduce and compare different sensing technologies that are suitable for continuous infant body motion quantification. Therefore, we conducted this systematic review for infant body motion quantification based on the PRISMA method (Preferred Reporting Items for Systematic Reviews and Meta-Analyses). In this systematic review, we introduce and compare several sensing technologies with motion quantification in different clinical applications. We discuss the pros and cons of each sensing technology for motion quantification. Additionally, we highlight the clinical value and prospects of infant motion monitoring. Finally, we provide suggestions with specific needs in clinical practice, which can be referred by clinical users for their implementation. Our findings suggest that motion quantification can improve the performance of vital sign monitoring, and can provide clinical value to the diagnosis of complications in infants.

High-efficiency stretchable light-emitting polymers from thermally activated delayed fluorescence

Stretchable light-emitting materials are the key components for realizing skin-like displays and optical biostimulation. All the stretchable emitters reported to date, to the best of our knowledge, have been based on electroluminescent polymers that only harness singlet excitons, limiting their theoretical quantum yield to 25%. Here we present a design concept for imparting stretchability onto electroluminescent polymers that can harness all the excitons through thermally activated delayed fluorescence, thereby reaching a near-unity theoretical quantum yield. We show that our design strategy of inserting flexible, linear units into a polymer backbone can substantially increase the mechanical stretchability without affecting the underlying electroluminescent processes. As a result, our synthesized polymer achieves a stretchability of 125%, with an external quantum efficiency of 10%. Furthermore, we demonstrate a fully stretchable organic light-emitting diode, confirming that the proposed stretchable thermally activated delayed fluorescence polymers provide a path towards simultaneously achieving desirable electroluminescent and mechanical characteristics, including high efficiency, brightness, switching speed and stretchability as well as low driving voltage.

Barcoding, linear and nonlinear analysis of full-day leg movements in infants with typical development and infants at risk of developmental disabilities: Cross-sectional study

Traditional methods do not capture the multidimensional domains and dynamic nature of infant behavioral patterns. We aim to compare full-day, in-home leg movement data between infants with typical development (TD) and infants at risk of developmental disabilities (AR) using barcoding and nonlinear analysis. Eleven infants with TD (2-10 months) and nine infants AR (adjusted age: 2-14 months) wore a sensor on each ankle for 7 days. We calculated the standard deviation for linear variability and sample entropy (SampEn) of leg acceleration and angular velocity for nonlinear variability. Movements were also categorized into 16 barcoding states, and we calculated the SampEn and proportions of the barcoding. All variables were compared between the two groups using independent-samples t-test or Mann-Whitney U test. The AR group had larger linear variability compared to the TD group. SampEn was lower in the AR group compared to TD group for both acceleration and angular velocity. Two barcoding states' proportions were significantly different between the two groups. The results showed that nonlinear analysis and barcoding could be used to identify the difference of dynamic multidimensional movement patterns between infants AR and infants with TD. This information may help early diagnosis of developmental disabilities in the future.

Wireless monitoring devices in hospitalized children: a scoping review

The purpose of this study is to provide a structured overview of existing wireless monitoring technologies for hospitalized children. A systematic search of the literature published after 2010 was conducted in Medline, Embase, Scielo, Cochrane, and Web of Science. Two investigators independently reviewed articles to determine eligibility for inclusion. Information on study type, hospital setting, number of participants, use of a reference sensor, type and number of vital signs monitored, duration of monitoring, type of wireless information transfer, and outcomes of the wireless devices was extracted. A descriptive analysis was applied. Of the 1130 studies identified from our search, 42 met eligibility for subsequent analysis. Most included studies were observational studies with sample sizes of 50 or less published between 2019 and 2022. Common problems pertaining to study methodology and outcomes observed were short duration of monitoring, single focus on validity, and lack information on wireless transfer and data management.  Conclusion: Research on the use of wireless monitoring for children in hospitals has been increasing in recent years but often limited by methodological problems. More rigorous studies are necessary to establish the safety and accuracy of novel wireless monitoring devices in hospitalized children. What is Known: • Continuous monitoring of vital signs using wired sensors is the standard of care for hospitalized pediatric patients. However, the use of wires may pose significant challenges to optimal care. What is New: • Interest in wireless monitoring for hospitalized pediatric patients has been rapidly growing in recent years. • However, most devices are in early stages of clinical testing and are limited by inconsistent clinical and technological reporting.

Artificial intelligence-driven wearable technologies for neonatal cardiorespiratory monitoring: Part 1 wearable technology

With the development of Artificial Intelligence techniques, smart health monitoring is becoming more popular. In this study, we investigate the trend of wearable sensors being adopted and developed in neonatal cardiorespiratory monitoring. We performed a search of papers published from the year 2000 onwards. We then reviewed the advances in sensor technologies and wearable modalities for this application. Common wearable modalities included clothing (39%); chest/abdominal belts (25%); and adhesive patches (15%). Popular singular physiological information from sensors included electrocardiogram (15%), breathing (24%), oxygen saturation and photoplethysmography (13%). Many studies (46%) incorporated a combination of these signals. There has been extensive research in neonatal cardiorespiratory monitoring using both single and multi-parameter systems. Poor data quality is a common issue and further research into combining multi-sensor information to alleviate this should be investigated. IMPACT STATEMENT: State-of-the-art review of sensor technology for wearable neonatal cardiorespiratory monitoring. Review of the designs for wearable neonatal cardiorespiratory monitoring. The use of multi-sensor information to improve physiological data quality has been limited in past research. Several sensor technologies have been implemented and tested on adults that have yet to be explored in the newborn population.

Soft skin-interfaced mechano-acoustic sensors for real-time monitoring and patient feedback on respiratory and swallowing biomechanics

Swallowing is a complex neuromuscular activity regulated by the autonomic nervous system. Millions of adults suffer from dysphagia (impaired or difficulty swallowing), including patients with neurological disorders, head and neck cancer, gastrointestinal diseases, and respiratory disorders. Therapeutic treatments for dysphagia include interventions by speech-language pathologists designed to improve the physiology of the swallowing mechanism by training patients to initiate swallows with sufficient frequency and during the expiratory phase of the breathing cycle. These therapeutic treatments require bulky, expensive equipment to synchronously record swallows and respirations, confined to use in clinical settings. This paper introduces a wireless, wearable technology that enables continuous, mechanoacoustic tracking of respiratory activities and swallows through movements and vibratory processes monitored at the skin surface. Validation studies in healthy adults (n = 67) and patients with dysphagia (n = 4) establish measurement equivalency to existing clinical standard equipment. Additional studies using a differential mode of operation reveal similar performance even during routine daily activities and vigorous exercise. A graphical user interface with real-time data analytics and a separate, optional wireless module support both visual and haptic forms of feedback to facilitate the treatment of patients with dysphagia.

Topographic design in wearable MXene sensors with in-sensor machine learning for full-body avatar reconstruction

Wearable strain sensors that detect joint/muscle strain changes become prevalent at human–machine interfaces for full-body motion monitoring. However, most wearable devices cannot offer customizable opportunities to match the sensor characteristics with specific deformation ranges of joints/muscles, resulting in suboptimal performance. Adequate wearable strain sensor design is highly required to achieve user-designated working windows without sacrificing high sensitivity, accompanied with real-time data processing. Herein, wearable Ti₃C₂T_x MXene sensor modules are fabricated with in-sensor machine learning (ML) models, either functioning via wireless streaming or edge computing, for full-body motion classifications and avatar reconstruction. Through topographic design on piezoresistive nanolayers, the wearable strain sensor modules exhibited ultrahigh sensitivities within the working windows that meet all joint deformation ranges. By integrating the wearable sensors with a ML chip, an edge sensor module is fabricated, enabling in-sensor reconstruction of high-precision avatar animations that mimic continuous full-body motions with an average avatar determination error of 3.5 cm, without additional computing devices.

Wearable sensors with edge computing are desired for human motion monitoring. Here, the authors demonstrate a topographic design for wearable MXene sensor modules with wireless streaming or in-sensor computing models for avatar reconstruction.

Intelligent wearable allows out-of-the-lab tracking of developing motor abilities in infants

Background

Early neurodevelopmental care needs better, effective and objective solutions for assessing infants' motor abilities. Novel wearable technology opens possibilities for characterizing spontaneous movement behavior. This work seeks to construct and validate a generalizable, scalable, and effective method to measure infants' spontaneous motor abilities across all motor milestones from lying supine to fluent walking.

Methods

A multi-sensor infant wearable was constructed, and 59 infants (age 5-19 months) were recorded during their spontaneous play. A novel gross motor description scheme was used for human visual classification of postures and movements at a second-level time resolution. A deep learning -based classifier was then trained to mimic human annotations, and aggregated recording-level outputs were used to provide posture- and movement-specific developmental trajectories, which enabled more holistic assessments of motor maturity.

Results

Recordings were technically successful in all infants, and the algorithmic analysis showed human-equivalent-level accuracy in quantifying the observed postures and movements. The aggregated recordings were used to train an algorithm for predicting a novel neurodevelopmental measure, Baba Infant Motor Score (BIMS). This index estimates maturity of infants' motor abilities, and it correlates very strongly (Pearson's r = 0.89, p < 1e-20) to the chronological age of the infant.

Conclusions

The results show that out-of-hospital assessment of infants' motor ability is possible using a multi-sensor wearable. The algorithmic analysis provides metrics of motility that are transparent, objective, intuitively interpretable, and they link strongly to infants' age. Such a solution could be automated and scaled to a global extent, holding promise for functional benchmarking in individualized patient care or early intervention trials.

Stretchable, Multi-Layered Stack Antenna for Smart/Wearable Electronic Applications

The development of microelectronics has been achieved by improving its performance through miniaturization. This was possible through the development of silicon-based semiconductor process technology, but recently, the demand for wearable or flexible devices has increased. These devices are made using various functional elements based on materials that are difficult to utilize with semiconductor devices that contain existing hard silicon-based materials and are bent or flexibly stretched. In this study, wireless antennas suitable for wearable devices were implemented in a stretchable form. It was possible to stably receive a wireless signal, even with a strain of 20% or more, and power light-emitting diodes (LEDs), microheaters, etc. By devising a multi-layered stack antenna without the existing semiconductor process, it was possible to improve the antenna’s reception performance. It is expected that this can be applied in various ways to smart wireless sensors and wearable biomedical devices using the near-field communication (NFC) of smartphones.