Research and Application Progress of Intelligent Wearable Devices

Anti-Freezing Conductive Ionic Hydrogel-Enabled Triboelectric Nanogenerators for Wearable Speech Recognition

Flexible wearable electronics face critical challenges in achieving reliable physiological monitoring, particularly due to the trade-off between sensitivity and durability in flexible electrodes, compounded by mechanical modulus mismatch with biological tissues. To address these limitations, we develop an anti-freezing ionic hydrogel through a chitosan/acrylamide/LiCl system engineered via the solution post-treatment strategy. The optimized hydrogel exhibits exceptional ionic conductivity (24.1 mS/cm at 25 °C) and excellent cryogenic tolerance. Leveraging these attributes, we construct a gel-based triboelectric nanogenerator (G-TENG) that demonstrates ultrahigh sensitivity (1.56 V/kPa) under low pressure. The device enables the precise capture of subtle vibrations at a frequency of 1088 Hz with a signal-to-noise ratio of 16.27 dB and demonstrates operational stability (>16,000 cycles), successfully differentiating complex physiological activities including swallowing, coughing, and phonation. Through machine learning-assisted analysis, the system achieves 96.56% recognition accuracy for five words and demonstrates good signal recognition ability in different ambient sound scenarios. This work provides a paradigm for designing environmentally adaptive wearable sensors through interfacial modulus engineering and ion transport optimization.

Machine Learning-Assisted Gesture Sensor Made with Graphene/Carbon Nanotubes for Sign Language Recognition

Gesture sensors are essential to collect human movements for human-computer interfaces, but their application is normally hampered by the difficulties in achieving high sensitivity and an ultrawide response range simultaneously. In this article, inspired by the spider silk structure in nature, a novel gesture sensor with a core-shell structure is proposed. The sensor offers a high gauge factor of up to 340 and a wide response range of 60%. Moreover, the sensor combining with a deep learning technique creates a system for precise gesture recognition. The system demonstrated an impressive 99% accuracy in single gesture recognition tests. Meanwhile, by using the sliding window technology and large language model, a high performance of 97% accuracy is achieved in continuous sentence recognition. In summary, the proposed high-performance sensor significantly improves the sensitivity and response range of the gesture recognition sensor. Meanwhile, the neural network technology is combined to further improve the way of daily communication by sign language users.

A wearable microfluidic system for efficient sweat collection and real-time detection

Sweat is an important biofluid with rich physiological information that can evaluate human health condition. Wearable sweat sensors have received widespread attention in recent years due to the benefits of non-invasive, continuous, and real-time monitoring. Currently, an efficient device integrating sweat collection and detection is still needed. Here, a wearable sweat microfluidic system was fabricated for real-time collection and analysis of sweat. The fabricated microfluidic system consisted of four layers, including a skin adhesive layer, a microfluidic layer, an electrode layer, and a capping layer. The sweat collection rate was around 0.79 μL/min, which demonstrated efficient sweat sampling, storage, and refreshing capabilities. Simultaneous detection of multiple sweat biomarkers was achieved with a screen-printed sweat sensing array, which could realize high-precision detection of Na+, K+, and glucose. Moreover, the sensing array also showed good repeatability and stability, with a relative standard deviation of sensitivity of less than 5%. Additionally, human testing was conducted to demonstrate that this microfluidic system can continuously monitor Na+, K+, and glucose in subjects' sweat during exercise, which showed high potential for non-invasive human health monitoring.

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

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

Progress in the design of portable colorimetric chemical sensing devices

The need for precise determination of heavy metals, anions, biomolecules, pesticides, drugs, and other substances is vital across clinical, environmental, and food safety domains. Recent years have seen significant progress in portable colorimetric chemical sensing devices, revolutionizing on-the-spot analysis. This review offers a comprehensive overview of these advancements, covering handheld colorimetry, RGB-based colorimetry, paper-based colorimetry, and wearable colorimetry devices. It explores the underlying principles, functional materials (chromophoric reagents/dyes and nanoparticles), detection mechanisms, and their applications in environmental monitoring, clinical care, and food safety. Noble metal nanoparticles (NPs) have arisen as promising substitutes in the realm of sensing materials. They display notable advantages, including heightened sensitivity, the ability to fine-tune their plasmonic characteristics for improved selectivity, and the capacity to induce visible color changes, and simplifying detection. Integration of NPs fabricated paper device with smartphones and wearables facilitates reagent-free, cost-effective, and portable colorimetric sensing, enabling real-time analysis and remote monitoring.

Insole Systems for Disease Diagnosis and Rehabilitation: A Review

Some chronic diseases, including Parkinson's disease (PD), diabetic foot, flat foot, stroke, elderly falling, and knee osteoarthritis (KOA), are related to orthopedic organs, nerves, and muscles. The interaction of these three parts will generate a comprehensive result: gait. Furthermore, the lesions in these regions can produce abnormal gait features. Therefore, monitoring the gait features can assist medical professionals in the diagnosis and analysis of these diseases. Nowadays, various insole systems based on different sensing techniques have been developed to monitor gait and aid in medical research. Hence, a detailed review of insole systems and their applications in disease management can greatly benefit researchers working in the field of medical engineering. This essay is composed of the following sections: the essay firstly provides an overview of the sensing mechanisms and parameters of typical insole systems based on different sensing techniques. Then this essay respectively discusses the three stages of gait parameters pre-processing, respectively: pressure reconstruction, feature extraction, and data normalization. Then, the relationship between gait features and pathogenic mechanisms is discussed, along with the introduction of insole systems that aid in medical research; Finally, the current challenges and future trends in the development of insole systems are discussed.

Self-Generation of Distinguishable Fluorescent Probes via a One-Pot Process for Multiple MicroRNA Detection by Liquid Chromatography

To address the challenge of signal production and separation for multiple microRNA (miRNA) detection, in this work, a "one-pot" process to self-generate distinguishable fluorescent probes was developed. Based on a long and short probe amplification strategy, the generated G-quadruplex fluorescent dye-free probes can be separated and detected by a high-performance liquid chromatography-fluorescence platform. The free hairpin probes enriched in guanine with different lengths and base sequences were designed and could be opened by the target miRNAs (miRNA-10b, miRNA-21, and miRNA-210). Cleaved G-quadruplex probes with fluorescent signal could be generated in a one-pot process after a duplex-specific nuclease-based cleavage, and the detection of multiple miRNAs could be realized in one run. No solid nanomaterials were applied in the assay, which avoided the blocking of the column. Moreover, without modification of expensive fluorescein, the experimental cost was greatly reduced. The one-pot reaction process also eliminated tedious preparation steps and suggested feasibility of automation. The limits of detection of miRNA-10b, miRNA-21, and miRNA-210 were 2.19, 2.20, and 2.75 fM, respectively. Notably, this method was successfully applied to multiplex detection of miRNAs in serum samples from breast cancer patients within 30 min.

Wearable Device-Based Intelligent Patrol Inspection System Design and Implementation

The traditional on-site operation of power stations includes inspection and maintenance. However, it heavily relies on experience for maintenance. Most on-site operation and maintenance data are text records. On the one hand, the data processing is tedious for experience to affect the safe on-site operation. On the other hand, we usually cannot give full consideration to the value of maintenance experience, so that the corresponding efficiency is very low. Therefore, this paper proposes a wearable device based remote and intelligent patrol inspection system that uses the cloud video transmission mode of both public and private clouds to realize the video connection between the power stations and the remote diagnosis center and uses the wearable devices for real experience. In this way, the authors can simulate real operation guidance and safety supervision, etc. so as to realize the remote management patrol operations, improve the fault detection efficiency, and improve equipment reliability.

A Review of Commercial and Non-Commercial Wearables Devices for Monitoring Motor Impairments Caused by Neurodegenerative Diseases

Neurodegenerative diseases (NDDs) are among the 10 causes of death worldwide. The effects of NDDs, including irreversible motor impairments, have an impact not only on patients themselves but also on their families and social environments. One strategy to mitigate the pain of NDDs is to early identify and remotely monitor related motor impairments using wearable devices. Technological progress has contributed to reducing the hardware complexity of mobile devices while simultaneously improving their efficiency in terms of data collection and processing and energy consumption. However, perhaps the greatest challenges of current mobile devices are to successfully manage the security and privacy of patient medical data and maintain reasonable costs with respect to the traditional patient consultation scheme. In this work, we conclude: (1) Falls are most monitored for Parkinson's disease, while tremors predominate in epilepsy and Alzheimer's disease. These findings will provide guidance for wearable device manufacturers to strengthen areas of opportunity that need to be addressed, and (2) Of the total universe of commercial wearables devices that are available on the market, only a few have FDA approval, which means that there is a large number of devices that do not safeguard the integrity of the users who use them.

Molecularly Imprinted Ratiometric Fluorescence Nanosensors

Molecularly imprinted ratiometric fluorescence (MIR-FL) nanosensors feature recognition selectivity, detection sensitivity, application universality, visualization accuracy, and device portability, and have gained popularity. However, the fluorescence intensity, nanostructure, color range, and practical application of the sensor still face severe difficulties to be solved. New strategies combined with various technologies have been developed to construct MIR-FL nanosensors for expanded applications. This Perspective highlights current resarch challenges and future prospects involving constructions and applications of MIR-FL nanosensors including dual-emission and triple-emission modes. The postimprinting mixing/modification strategies, microdevices, and multitarget detection are focused, and technology synergy, sensitivity/reproducibility improvement, application diversity/portability, etc. are proposed.