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On the Impact of Biceps Muscle Fatigue in Human Activity Recognition.

Author(s): Elshafei M, Costa DE, Shihab E

Nowadays, Human Activity Recognition (HAR) systems, which use wearables and smart systems, are a part of our daily life. Despite the abundance of literature in the area, little is known about the impact of muscle fatigue on these systems' performance. I...

Article GUID: 33557239
Towards Detecting Biceps Muscle Fatigue in Gym Activity Using Wearables.

Author(s): Elshafei M, Shihab E

Fatigue is a naturally occurring phenomenon during human activities, but it poses a bigger risk for injuries during physically demanding activities, such as gym activities and athletics. Several studies show that bicep muscle fatigue can lead to various inj...

Article GUID: 33498702
Finite Element Modelling of Bandgap Engineered Graphene FET with the Application in Sensing Methanethiol Biomarker.

Author(s): Singh P, Abedini Sohi P, Kahrizi M

In this work, we have designed and simulated a graphene field effect transistor (GFET) with the purpose of developing a sensitive biosensor for methanethiol, a biomarker for bacterial infections. The surface of a graphene layer is functionalized by manipula...

Article GUID: 33467459
A Benchmark of Data Stream Classification for Human Activity Recognition on Connected Objects.

Author(s): Khannouz M; Glatard T;

This paper evaluates data stream classifiers from the perspective of connected devices, focusing on the use case of Human Activity Recognition. We measure both the classification performance and resource consumption (runtime, memory, and power) of five usua...

Article GUID: 33202905
Contactless Capacitive Electrocardiography Using Hybrid Flexible Printed Electrodes.

Author(s): Lessard-Tremblay M, Weeks J, Morelli L, Cowan G, Gagnon G, Zednik RJ

Traditional capacitive electrocardiogram (cECG) electrodes suffer from limited patient comfort, difficulty of disinfection and low signal-to-noise ratio in addition to the challenge of integrating them in wearables. A novel hybrid flexible cECG electrode wa...

Article GUID: 32927651
Determining the Optimal Restricted Driving Zone Using Genetic Algorithm in a Smart City.

Author(s): Azami P, Jan T, Iranmanesh S, Ameri Sianaki O, Hajiebrahimi S

Sensors (Basel). 2020 Apr 16;20(8): Authors: Azami P, Jan T, Iranmanesh S, Ameri Sianaki O, Hajiebrahimi S

Article GUID: 32316356
A Quantitative Comparison of Overlapping and Non-Overlapping Sliding Windows for Human Activity Recognition Using Inertial Sensors.

Author(s): Dehghani A, Sarbishei O, Glatard T, Shihab E

Sensors (Basel). 2019 Nov 18;19(22): Authors: Dehghani A, Sarbishei O, Glatard T, Shihab E

Article GUID: 31752158
Characterization and Efficient Management of Big Data in IoT-Driven Smart City Development.

Author(s): Alsaig A, Alagar V, Chammaa Z, Shiri N

Sensors (Basel). 2019 May 28;19(11): Authors: Alsaig A, Alagar V, Chammaa Z, Shiri N

Article GUID: 31141899
A Crowdsensing Based Analytical Framework for Perceptional Degradation of OTT Web Browsing.

Author(s): Li K, Wang H, Xu X, Du Y, Liu Y, Ahmad MO

Sensors (Basel). 2018 May 15;18(5): Authors: Li K, Wang H, Xu X, Du Y, Liu Y, Ahmad MO

Article GUID: 29762493
Fast Feature-Preserving Approach to Carpal Bone Surface Denoising.

Author(s): Salim I, Hamza AB

Sensors (Basel). 2018 Jul 21;18(7): Authors: Salim I, Hamza AB

Article GUID: 30037109
Big Data-Driven Cellular Information Detection and Coverage Identification.

Author(s): Wang H, Xie S, Li K, Ahmad MO

Sensors (Basel). 2019 Feb 22;19(4): Authors: Wang H, Xie S, Li K, Ahmad MO

Article GUID: 30813353
Surface Profiling and Core Evaluation of Aluminum Honeycomb Sandwich Aircraft Panels Using Multi-Frequency Eddy Current Testing.

Author(s): Reyno T, Underhill PR, Krause TW, Marsden C, Wowk D

Sensors (Basel). 2017 Sep 14;17(9): Authors: Reyno T, Underhill PR, Krause TW, Marsden C, Wowk D

Article GUID: 28906434
Title:Surface Profiling and Core Evaluation of Aluminum Honeycomb Sandwich Aircraft Panels Using Multi-Frequency Eddy Current Testing.
Authors:Reyno T,  Underhill PR,  Krause TW,  Marsden C,  Wowk D
Link:https://www.ncbi.nlm.nih.gov/pubmed/28906434?dopt=Abstract
Category:Sensors (Basel)
PMID:28906434
Dept Affiliation: PHYSICS
1 Department of Mechanical and Aerospace Engineering, Royal Military College of Canada, Kingston, ON K7K 7B4, Canada. tylerreyno@gmail.com.
2 Department of Physics, Royal Military College of Canada, Kingston, ON K7K 7B4, Canada. ross.underhill@rmc.ca.
3 Department of Physics, Royal Military College of Canada, Kingston, ON K7K 7B4, Canada. thomas.krause@rmc.ca.
4 Faculty of Engineering and Computer Science, Concordia University, Montreal, QC H3G 1M8, Canada. c.marsden@concordia.ca.
5 Department of Mechanical and Aerospace Engineering, Royal Military College of Canada, Kingston, ON K7K 7B4, Canada. diane.wowk@rmc.ca.

Description:

Surface Profiling and Core Evaluation of Aluminum Honeycomb Sandwich Aircraft Panels Using Multi-Frequency Eddy Current Testing.

Sensors (Basel). 2017 Sep 14;17(9):

Authors: Reyno T, Underhill PR, Krause TW, Marsden C, Wowk D

Abstract

Surface damage on honeycomb aircraft panels is often measured manually, and is therefore subject to variation based on inspection personnel. Eddy current testing (ECT) is sensitive to variations in probe-to-specimen spacing, or lift-off, and is thus promising for high-resolution profiling of surface damage on aluminum panels. Lower frequency testing also allows inspection through the face sheet, an advantage over optical 3D scanning methods. This paper presents results from the ECT inspection of surface damage on an approximately flat aluminum honeycomb aircraft panel, and compares the measurements to those taken using optical 3D scanning technology. An ECT C-Scan of the dented panel surface was obtained by attaching the probe to a robotic scanning apparatus. Data was taken simultaneously at four frequencies of 25, 100, 400 and 1600 kHz. A reference surface was then defined that approximated the original, undamaged panel surface, which also compensated for the effects of specimen tilt and thermal drift within the ECT instrument. Data was converted to lift-off using height calibration curves developed for each probe frequency. A damage region of 22,550 mm² area with dents ranging in depth from 0.13-1.01 mm was analyzed. The method was accurate at 1600 kHz to within 0.05 mm (2s) when compared with 231 measurements taken via optical 3D scanning. Testing at 25 kHz revealed a 3.2 mm cell size within the honeycomb core, which was confirmed via destructive evaluation. As a result, ECT demonstrates potential for implementation as a method for rapid in-field aircraft panel surface damage assessment.

PMID: 28906434 [PubMed]