Self-powered pressure detection using smart wearable devices is the subject of intense research attention, which is intended to address the critical need for prolonged and uninterrupted operations. Current piezoelectric and triboelectric sensors well respond to dynamic stimuli while overlooking static stimuli. This study proposes a dual-response potentiometric pressure sensor that responds to both dynamic and static stimuli. The proposed sensor utilizes interdigital electrodes with MnO/carbon/polyvinyl alcohol (PVA) as the cathode and conductive silver paste as the anode. The electrolyte layer incorporates a mixed hydrogel of PVA and phosphoric acid. The optimized interdigital electrodes and sandpaper-like microstructured surface of the hydrogel electrolyte contribute to enhanced performance by facilitating an increased contact area between the electrolyte and electrodes. The sensor features an open-circuit voltage of 0.927 V, a short-circuit current of 6 µA, a higher sensitivity of 14 mV/kPa, and outstanding cycling performance (>5000 cycles). It can accurately recognize letter writing and enable capacitor charging and LED lighting. Additionally, a data acquisition and display system employing the proposed sensor, which facilitates the monitoring of athletes' rehabilitation training, and machine learning algorithms that effectively guide rehabilitation actions are presented. This study offers novel solutions for the future development of smart wearable devices.
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http://dx.doi.org/10.1002/advs.202401515 | DOI Listing |
Nanomaterials (Basel)
January 2025
Department of Physics and Engineering, Moldova State University, MD-2009 Chisinau, Moldova.
This article analyzes the prospects for the appearance of paper-based sensors on the sensor market. It is concluded that paper-based sensors are not a fantasy but a reality. It is shown that paper has properties that make it possible to develop a wide variety of paper-based sensors, such as SERS, colorimetric, fluorescent, conductometric, capacitive, fiber-optic, electrochemical, microfluidic, shape-deformation, microwave, and various physical sensors.
View Article and Find Full Text PDFJ Cardiovasc Dev Dis
January 2025
Department of Cardiology, University Hospital Galway, Saolta University Healthcare Group, Newcastle Road, H91YR71 Galway, Ireland.
Hospitalisation for acute decompensated heart failure (HF) portends a poor prognosis. Fluid retention manifesting in dyspnoea and oedema are important clinical features of decompensated heart failure and drive hospital admissions. Intracardiac and pulmonary artery pressure (PAP) monitoring can help predict heart failure decompensation, as changes in these haemodynamics occur before clinical congestion manifests.
View Article and Find Full Text PDFBiosensors (Basel)
December 2024
Department of Biomechatronics Engineering, National Taiwan University, Taipei 10617, Taiwan.
An origami-based tactile sensory ring utilizing multilayered conductive paper substrates presents an innovative approach to wearable health applications. By harnessing paper's flexibility and employing origami folding, the sensors integrate structural stability and self-packaging without added encapsulation layers. Knot-shaped designs create loop-based systems that secure conductive paper strips and protect sensing layers.
View Article and Find Full Text PDFBiosensors (Basel)
December 2024
Department of Materials Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China.
The early monitoring of cardiovascular biomarkers is essential for the prevention and management of some cardiovascular diseases. Here, we present a novel, compact, and highly integrated skin electrode as a mechanical-electrochemical dual-model E-skin, designed for the real-time monitoring of heart rate and sweat ion concentration, two critical parameters for assessing cardiovascular health. As a pressure sensor, this E-skin is suitable for accurate heart rate monitoring, as it exhibits high sensitivity (25.
View Article and Find Full Text PDFBiomimetics (Basel)
January 2025
Key Laboratory of Mechanism Theory and Equipment Design, Ministry of Education, Tianjin University, Tianjin 300072, China.
This paper presents a novel soft crawling robot controlled by gesture recognition, aimed at enhancing the operability and adaptability of soft robots through natural human-computer interactions. The Leap Motion sensor is employed to capture hand gesture data, and Unreal Engine is used for gesture recognition. Using the UE4Duino, gesture semantics are transmitted to an Arduino control system, enabling direct control over the robot's movements.
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