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Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229
ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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  4/2022 - 10
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A Comparative Analysis of Two Approaches for Estimation of Upper Limb Orientation Using Inertial and Kinect Sensors

ACHARYA, A. See more information about ACHARYA, A. on SCOPUS See more information about ACHARYA, A. on IEEExplore See more information about ACHARYA, A. on Web of Science, BHAT, S. See more information about  BHAT, S. on SCOPUS See more information about  BHAT, S. on SCOPUS See more information about BHAT, S. on Web of Science, KANTHI, M. See more information about KANTHI, M. on SCOPUS See more information about KANTHI, M. on SCOPUS See more information about KANTHI, M. on Web of Science
 
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Download PDF pdficon (1,433 KB) | Citation | Downloads: 820 | Views: 956

Author keywords
inertial sensor, Kalman filter, upper limb, occupational medicine, sensor fusion

References keywords
upper(16), sensors(16), limb(13), kinect(13), inertial(12), sensor(9), assessment(8), stroke(7), motion(7), orientation(6)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2022-11-30
Volume 22, Issue 4, Year 2022, On page(s): 83 - 90
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2022.04010
Web of Science Accession Number: 000920289700010
SCOPUS ID: 85149751892

Abstract
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In Neuropsychology and Occupational medicine, the clinical environment uses upper limb assessment activity, which involves performing a few daily living activities. The main objective of this work is to develop a non-wearable, automated version of upper limb assessment, which allows free movement of the hand and records the trajectory information using inertial and Kinect sensor modules. The upper limb orientation is measured using an object attached to an MPU6050 inertial sensor. The assessment involves the measurement of quantitative parameters such as time, orientation, and trajectory with which the given task is completed. A similar task is performed using the Kinect sensor. The correlation between these two sensors is recorded. The Wilcoxon signed-rank test is performed to quantify the comparison between the stopwatch with the inertial sensor and Kinect sensor-based timing measurements.


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Cited-By CrossRef

[1] Pedal Speed and Orientation Estimation of a Virtual Reality Indoor Bicycle, Mollasaraei, Reyhaneh Hadipour, Motaharifar, Mohammad, Taghirad, Hamid D., 2023 11th RSI International Conference on Robotics and Mechatronics (ICRoM), ISBN 979-8-3503-0810-5, 2023.
Digital Object Identifier: 10.1109/ICRoM60803.2023.10412533
[CrossRef]

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