Objective: Adherence is a prerequisite for the effectiveness of orthopaedic footwear. The aim of this study is to assess the validity of a new temperature sensor for objective assessment of footwear use and non-use.
Design: Observational study.
Methods: The validity of a temperature sensor (Orthotimer, Balingen, Germany) to discriminate between time periods of use and non-use of footwear over a period of 48 h was assessed using 3 algorithms, in 10 healthy participants (mean age 32.8 years (standard deviation (SD) 14.1 years)). Footwear use measured with the sensor was compared with a reference standard, footwear use measured with a time-lapse sports camera secured to the shoe.
Main Outcome Measure: Hours of footwear use.
Results: Mean footwear use measured with the camera was 8.10 (SD 2.46) h per day. Mean footwear uses measured with the sensor and calculated with the 3 algorithms were 8.16 (SD 2.37), 8.86 (SD 2.48) and 4.91 (SD 3.17) h per day for the Groningen algorithm, algorithm-25, and algorithm-29, respectively. The correlation between footwear use assessed with the camera and with the sensor was: rGroningen = 0.995, ralg25 = 0.919 and ralg29 = 0.680).
Conclusion: The temperature sensor is a valid instrument to measure footwear use and non-use when using the Groningen algorithm.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.2340/16501977-2494 | DOI Listing |
ACS Appl Mater Interfaces
January 2025
Key Laboratory of MEMS of the Ministry of Education, Southeast University, Nanjing 210096, China.
As one of the core parts of the Internet-of-things (IOTs), multimodal sensors have exhibited great advantages in fields such as human-machine interaction, electronic skin, and environmental monitoring. However, current multimodal sensors substantially introduce a bloated equipment architecture and a complicated decoupling mechanism. In this work we propose a multimodal fusion sensing platform based on a power-dependent piecewise linear decoupling mechanism, allowing four parameters to be perceived and decoded from the passive wireless single component, which greatly broadens the configurable freedom of a sensor in the IOT.
View Article and Find Full Text PDFACS Sens
January 2025
Department of Chemistry, Wayne State University, 5101 Cass Ave, Detroit, Michigan 48202, United States.
Bioanalytical sensors are adept at quantifying target analytes from complex sample matrices with high sensitivity, but their multiplexing capacity is limited. Conversely, analytical separations afford great multiplexing capacity but typically require analyte labeling to increase sensitivity. Here, we report the development of a separation-based sensor to sensitively quantify unlabeled polysaccharides using particle motion tracking within a microfluidic electrophoresis platform.
View Article and Find Full Text PDFBMC Biomed Eng
January 2025
William B. Burnsed Jr. Department of Mechanical, Aerospace, and Biomedical Engineering, University of South Alabama, 150 Student Services Drive, Mobile, AL, 36688, USA.
Background: The ST response to high frequency EM heating may give an indication of rate of BF in underlying tissue. This novel method, which we have termed REFLO (Rapid Electromagnetic Flow) has potential for applications such as detection of PAD. The method utilizes the relationship between blood flow rate and tissue temperature increase during exposure to radio frequency (RF) energy.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Chemical Engineering, University of Mohaghegh Ardabili, Ardabil, Iran.
In this paper, we propose and theoretically investigate a novel multimode refractive index (MMRI) plasmonic optical sensor for detecting various brain cancer cells, leveraging the unique capabilities of split ring resonators (SRRs). The sensor, simulated using the finite-difference time-domain (FDTD) method, exhibits dual resonance modes in its reflection spectrum within the 1500 nm to 3500 nm wavelength range, marking a significant advancement in multimode plasmonic biosensing. Through detailed parametric analysis, we optimize critical dimensional parameters to achieve superior performance.
View Article and Find Full Text PDFPhysiol Meas
January 2025
Emory University School of Medicine, 101 Woodruff Circle, Atlanta, Atlanta, Georgia, 30322, UNITED STATES.
Objective: This study aims to evaluate the efficacy of wearable physiology and movement sensors in identifying a spectrum of challenging behaviors, including self-injurious behavior (SIB), in children and teenagers with autism spectrum disorder (ASD) in real-world settings.
Approach: We utilized a long-short-term memory (LSTM) network with features derived using the wavelet scatter transform to analyze physiological biosignals, including electrodermal activity and skin temperature, alongside three-dimensional movement data captured via accelerometers. The study was conducted in naturalistic environments, focusing on participants' daily activities.
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!