This paper briefly overviews and discusses the existing techniques using antennas for passive sensing, starting from the antenna operating principle and antenna structural design to different antenna-based sensing mechanisms. The effects of different electrical properties of the material used to design an antenna, such as conductivity, loss tangent, and resistivity, are discussed to illustrate the fundamental sensing mechanisms. Furthermore, the key parameters, such as operating frequency and antenna impedance, along with the factors affecting the sensing performance, are discussed. Overall, passive sensing using an antenna is mainly achieved by altering the reflected wave characteristics in terms of center frequency, return loss, phase, and received/reflected signal strength. The advantages and drawbacks of each technique are also discussed briefly. Given the increasing relevance, millimeter-wave antenna sensors and resonator sensors are also discussed with their applications and recent advancements. This paper primarily focuses on microstrip-based radiating structures and insights for further sensing performance improvement using passive antennas, which are outlined in this study. In addition, suggestions are made for the current scientific and technical challenges, and future directions are discussed.
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http://dx.doi.org/10.3390/s24196355 | DOI Listing |
JMIR Mhealth Uhealth
January 2025
IWK Health Centre Department of Psychiatry & Specific Care Clinics, Department of Psychiatry, Dalhousie University, 5850/5980 University Ave, Halifax, NS, B3K 6R8, Canada, 1 902-470-7720.
Background: Gratitude interventions are used to cultivate a sense of gratitude for life and others. There have been mixed results of the efficacy of gratitude interventions' effect on psychological well-being with a variety of populations and methodologies.
Objectives: The objective of our study was to test the effectiveness of a gratitude intervention smartphone app on university students' psychological well-being.
J Strength Cond Res
December 2024
School of Psychology, Faculty of Life and Health Sciences, Ulster University, Coleraine, Northern Ireland.
Edwards, AM, Coleman, D, Fuller, J, Kesisoglou, A, and Menting, SGP. Time perception and enjoyment of professional soccer players in different training sessions: Implications for assessment of session-RPE and training load. J Strength Cond Res 38(12): e754-e760, 2024-The purpose of this study was to investigate whether the perception of time and enjoyment levels among professional soccer players varied according to the type of training undertaken and whether this influenced the training load (TL) assessment method of session-rating of perceived exertion (sRPE).
View Article and Find Full Text PDFAdv Mater
January 2025
Division of Intelligent and Biomechanical Systems, State Key Laboratory of Tribology in Advanced Equipment, Department of Mechanical Engineering, Tsinghua University, Haidian, Beijing, 100084, China.
Quantitative assessment for post-stroke spasticity remains a significant challenge due to the encountered variable resistance during passive stretching, which can lead to the widely used modified Ashworth scale (MAS) for spasticity assessment depending heavily on rehabilitation physicians. To address these challenges, a high-force-output triboelectric soft pneumatic actuator (TENG-SPA) inspired by a lobster tail is developed. The bioinspired TENG-SPA can generate approximately 20 N at 0.
View Article and Find Full Text PDFSensors (Basel)
December 2024
School of Electrical and Computer Engineering, National Technical University of Athens, 15772 Athens, Greece.
Innov Aging
December 2024
Human Centered Design Department, Cornell University, Ithaca, New York, USA.
Background And Objectives: This study evaluates the feasibility of virtual reality (VR) wayfinding training with aging adults and assesses the impact of the training on wayfinding performance.
Research Design And Methods: 49 participants were recruited using a convenience sample approach. Wayfinding tasks were conducted by 3 participant groups: active VR training, passive video training, and no training, assigned randomly.
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