Ultrasensitive Textile Strain Sensors Redefine Wearable Silent Speech Interfaces with High Machine Learning Efficiency

Our research presents a wearable Silent Speech Interface (SSI) technology that excels in device comfort, time-energy efficiency, and speech decoding accuracy for real-world use. We developed a biocompatible, durable textile choker with an embedded graphene-based strain sensor, capable of accurately detecting subtle throat movements. This sensor, surpassing other strain sensors in sensitivity by 420%, simplifies signal processing compared to traditional voice recognition methods. Our system uses a computationally efficient neural network, specifically a one-dimensional convolutional neural network with residual structures, to decode speech signals. This network is energy and time-efficient, reducing computational load by 90% while achieving 95.25% accuracy for a 20-word lexicon and swiftly adapting to new users and words with minimal samples. This innovation demonstrates a practical, sensitive, and precise wearable SSI suitable for daily communication applications.Comment: 5 figures in the article; 11 figures and 4 tables in supplementary informatio

SHP2 regulates osteoclastogenesis by promoting preosteoclast fusion

Genes that regulate osteoclast (OC) development and function in both physiologic and disease conditions remain incompletely understood. Shp2 (the Src homology-2 domain containing protein tyrosine phosphatase 2), a ubiquitously expressed cytoplasmic protein tyrosine phosphatase, is implicated in regulating M-CSF and receptor activator of nuclear factor-κB ligand (RANKL)-evoked signaling; its role in osteoclastogenesis and bone homeostasis, however, remains unknown. Using a tissue-specific gene knockout approach, we inactivated Shp2 expression in murine OCs. Shp2 mutant mice are phenotypically osteopetrotic, featuring a marked increase of bone volume (BV)/total volume (TV) (+42.8%), trabeculae number (Tb.N) (+84.1%), structure model index (+119%), and a decrease of trabecular thickness (Tb.Th) (-34.1%) and trabecular spacing (Tb.Sp) (-41.0%). Biochemical analyses demonstrate that Shp2 is required for RANKL-induced formation of giant multinucleated OCs by up-regulating the expression of nuclear factor of activated T cells, cytoplasmic 1 (Nfatc1), a master transcription factor that is indispensable for terminal OC differentiation. Shp2 deletion, however, has minimal effect on M-CSF-dependent survival and proliferation of OC precursors. Instead, its deficiency aborts the fusion of OC precursors and formation of multinucleated OCs and decreases bone matrix resorption. Moreover, pharmacological intervention of Shp2 is sufficient to prevent preosteoclast fusion in vitro. These findings uncover a novel mechanism through which Shp2 regulates osteoclastogenesis by promoting preosteoclast fusion. Shp2 or its signaling partner(s) could potentially serve as pharmacological target(s) to regulate the population of OCs locally and/or systematically, and thus treat OC-related diseases, such as periprosthetic osteolysis and osteoporosis

Roadmap on printable electronic materials for next-generation sensors

The dissemination of sensors is key to realizing a sustainable, ‘intelligent’ world, where everyday objects and environments are equipped with sensing capabilities to advance the sustainability and quality of our lives—e.g., via smart homes, smart cities, smart healthcare, smart logistics, Industry 4.0, and precision agriculture. The realization of the full potential of these applications critically depends on the availability of easy-to-make, low-cost sensor technologies. Sensors based on printable electronic materials offer the ideal platform: they can be fabricated through simple methods (e.g., printing and coating) and are compatible with high-throughput roll-to-roll processing. Moreover, printable electronic materials often allow the fabrication of sensors on flexible/stretchable/biodegradable substrates, thereby enabling the deployment of sensors in unconventional settings. Fulfilling the promise of printable electronic materials for sensing will require materials and device innovations to enhance their ability to transduce external stimuli—light, ionizing radiation, pressure, strain, force, temperature, gas, vapours, humidity, and other chemical and biological analytes. This Roadmap brings together the viewpoints of experts in various printable sensing materials—and devices thereof—to provide insights into the status and outlook of the field. Alongside recent materials and device innovations, the roadmap discusses the key outstanding challenges pertaining to each printable sensing technology. Finally, the Roadmap points to promising directions to overcome these challenges and thus enable ubiquitous sensing for a sustainable, ‘intelligent’ world

An empirical study on the correlation of self-efficacy and autonomous learningability of undergraduate nursing students and its influencing factors

Background: It is the focus of current nursing education to improve the independent learningability of nursing students and the post competence of registered nurses. The general selfefficacy of nursing students has a certain predictive value on their academic achievement,which is worthy of further study by nursing educators.Aim: This study aimed to describe the level of nursing students' self-efficacy and autonomouslearning ability, explore the relationship between self-efficacy and autonomous learningability, and explore the influencing factors of autonomous learning ability.Methods: Totally 247 undergraduate nursing students were investigated with the GeneralInformation Questionnaire,General Self- Efficacy Scale(GSES) and Self-directed LearningAbility Questionnaire．Results: First, the general self-efficacy score of nursing students was (27.081 ± 3.108), lowerthan the international norm, at the middle level, with an increasing trend from the first year tothe fourth year. Second, the overall average score of self-study ability of nursingundergraduate students was (77.63 ± 13.14) with a downward trend among four grades. Afterstandardization, the scores of each dimension were from high to low in order of learningcooperation, self-management, learning motivation and information quality. Third, the totalscore of nursing students' autonomous learning ability and its four dimensions werenegatively correlated with general self-efficacy; The self-study ability and all dimensions ofnursing students were negatively correlated with general self-efficacy. Fourth, the reasons forstudying nursing, serving as a student cadre and learning motivation are the influencingfactors or predictive factors of general self-efficacy.Conclusion: Firstly, the general self-efficacy of undergraduate nursing students at LishuiCollege is at an intermediate level, and the independent learning ability is high.Then as thegrade level increases, the general self-efficacy score gradually increases and the independentlearning ability score gradually decreases. The reasons for this are worthy of further study.Lastly, in order to improve students' academic performance and overall quality, undergraduatenursing teaching should pay more attention to the positive impact of self-directed learningreadiness and general self-efficacy on students' education. One of the ways in which selfdirected learning readiness can be addressed is in terms of motivation and quality ofinformation.Key words: Autonomous learning ability, Baccalaureate, Education, Nursing student, Selfefficac

An empirical study on the correlation of self-efficacy and autonomous learningability of undergraduate nursing students and its influencing factors

Background: It is the focus of current nursing education to improve the independent learningability of nursing students and the post competence of registered nurses. The general selfefficacy of nursing students has a certain predictive value on their academic achievement,which is worthy of further study by nursing educators.Aim: This study aimed to describe the level of nursing students' self-efficacy and autonomouslearning ability, explore the relationship between self-efficacy and autonomous learningability, and explore the influencing factors of autonomous learning ability.Methods: Totally 247 undergraduate nursing students were investigated with the GeneralInformation Questionnaire,General Self- Efficacy Scale(GSES) and Self-directed LearningAbility Questionnaire．Results: First, the general self-efficacy score of nursing students was (27.081 ± 3.108), lowerthan the international norm, at the middle level, with an increasing trend from the first year tothe fourth year. Second, the overall average score of self-study ability of nursingundergraduate students was (77.63 ± 13.14) with a downward trend among four grades. Afterstandardization, the scores of each dimension were from high to low in order of learningcooperation, self-management, learning motivation and information quality. Third, the totalscore of nursing students' autonomous learning ability and its four dimensions werenegatively correlated with general self-efficacy; The self-study ability and all dimensions ofnursing students were negatively correlated with general self-efficacy. Fourth, the reasons forstudying nursing, serving as a student cadre and learning motivation are the influencingfactors or predictive factors of general self-efficacy.Conclusion: Firstly, the general self-efficacy of undergraduate nursing students at LishuiCollege is at an intermediate level, and the independent learning ability is high.Then as thegrade level increases, the general self-efficacy score gradually increases and the independentlearning ability score gradually decreases. The reasons for this are worthy of further study.Lastly, in order to improve students' academic performance and overall quality, undergraduatenursing teaching should pay more attention to the positive impact of self-directed learningreadiness and general self-efficacy on students' education. One of the ways in which selfdirected learning readiness can be addressed is in terms of motivation and quality ofinformation.Key words: Autonomous learning ability, Baccalaureate, Education, Nursing student, Selfefficac

Research data supporting [Ultrasensitive Textile Strain Sensors Redefine Wearable Silent Speech Interfaces with High Machine Learning Efficiency]

This work encompasses five related datasets, accessible via an open-source link provided at the end of the manuscript: 1. Dataset1_20 Frequently Used Words: This dataset contains signals of the 20 most frequently used words (10 nouns and 10 verbs) collected from participants, with 100 samples per class. Each sample of a word is represented in a row, with the last number in each row indicating the class label for that word (the same applies to the following datasets). 2. Dataset2_Confusing Words: This dataset includes 5 pairs of 10 words with similar pronunciations that are easily confused, with 100 samples per class. 3. Dataset3_Different Reading Speeds: This dataset comprises signals of 5 long words read at three different speeds: fast, medium, and slow, with approximately 33 samples for each word at each reading speed. 4. New User Generalization Test: This dataset contains signals of 5 commonly used words (included in Dataset1) collected from three new users, with 50 samples per class. 5. Noise Injection Data: This dataset includes around five minutes of silent noise signals (containing physiological noises such as breathing and swallowing) recorded in the absence of speech

EMG-Based Human Motion Analysis: A Novel Approach Using Towel Electrodes and Transfer Learning

This paper presents an innovative solution for electromyography (EMG)-based human motion analysis systems, addressing challenges of sensor comfort, inter-individual variations, and labor-intensive labeling processes. The solution combines textile towel-based electrodes with transfer learning techniques. The textile towel-based graphene/PEDOT:PSS composite electrode offers biocompatibility, low skin impedance, and user comfort, while transfer learning reduces the need for extensive new data labeling and enhances the generalisation ability of the motion analysis system. The proposed methodology achieves accurate classification of hand gestures with a minimal number of samples and epochs. This demonstrates the potential of transfer learning for efficient EMG-based human motion analysis

A Roadmap for the Development of Human Body Digital Twins

A human body digital twin (DT) is a virtual representation of an individual's physiological state, created using real-time data from sensors and medical test devices, with the purpose of simulating, predicting, and optimizing health outcomes through advanced analysis and modeling. The human body DT has the potential to revolutionize healthcare and wellness, but its responsible and effective implementation requires consideration of multiple intertwined engineering aspects. This perspective presents a comprehensive overview of the status and prospects of the human body DT and proposes a five-level roadmap to guide its development, from the sensing components, in the form of wearable devices, to the data collection, analysis, and decision-making systems. The article also highlights the necessary support, security, cost, and ethical considerations that must be addressed to ensure responsible and effective implementation of the human body DT. In the end, we provide a framework for the development and offer a unique perspective on the future of the human body DT, facilitating new interdisciplinary research and innovative solutions in this rapidly evolving field

A Pressure Sensing System for Heart Rate Monitoring with Polymer-Based Pressure Sensors and An Anti-Interference Post Processing Circuit

Heart rate measurement is a basic and important issue for either medical diagnosis or daily health monitoring. In this work great efforts have been focused on realizing a portable, comfortable and low cost solution for long-term domestic heart rate monitoring. A tiny but efficient measurement system composed of a polymer-based flexible pressure sensor and an analog anti-interference readout circuit is proposed; manufactured and tested. The proposed polymer-based pressure sensor has a linear response and high sensitivity of 13.4 kPa−1. With the circuit’s outstanding capability in removing interference caused by body movement and the highly sensitive flexible sensor device, comfortable long-term heart rate monitoring becomes more realistic. Comparative tests prove that the proposed system has equivalent capability (accuracy: <3%) in heart rate measurement to the commercial product

Transformation of Soil Accumulated Phosphorus and Its Driving Factors across Chinese Cropping Systems

Understanding the transformation of accumulated phosphorus (P) is vital for P management. However, previous studies are limited to a few sites in Chinese agroecosystems. In this study, to investigate the temporal-spatial differences of transformation from accumulated P to available P (determined by the Olsen method), a dataset was assembled based on 91 national long-term experimental sites across China in the recent 31 years (1988–2018). A boosted regression tree (BRT) and a structural equation model (SEM) were used to analyze the factors influencing the transformation. The results showed that the transformation from accumulated P to available P in South China (1.97 mg kg−1) was significantly higher than that in other regions (0.69–1.22 mg kg−1). Soil properties were the main driving factors with a relative contribution of 81.8%, while climate and management practices explained 7.8% and 10.4% of the variations, respectively. Furthermore, SEM analysis revealed that the soil organic matter (SOM) could positively and directly affect the transformation, whereas the soil pH, soil silt content, and P fertilizer had negative and direct effects on it. For the first time, this study analyzed the transformation from soil accumulated P to available P at a national scale and at multiple sites and quantified the contribution of the main influencing factors. These results help to predict the soil available P content across different agroecosystems based on the input amount of P fertilizer, contributing to the regional precise management of P fertilizer application