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Reliability Study of Inertial Sensors LIS2DH12 Compared to ActiGraph GT9X: Based on Free Code.

Martín-Martín, J., Jiménez-Partinen, A., De-Torres, I., Escriche-Escuder, A., González-Sánchez, M., Muro-Culebras, A., Roldán-Jiménez, C., Ruiz-Muñoz, M., Mayoral-Cleries, F., Biró, A., Tang, W., Nikolova, B., Salvatore, A. and Cuesta-Vargas, A.I., 2022. Reliability Study of Inertial Sensors LIS2DH12 Compared to ActiGraph GT9X: Based on Free Code. Journal of Personalized Medicine, 12 (5), 749.

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DOI: 10.3390/jpm12050749

Abstract

The study’s purpose was to assess the reliability of the LIS2DH12 in two different positions, using the commercial sensor Actigraph GT9X as a reference instrument. Five participants completed two gait tests on a treadmill. Firstly, both sensors were worn on the wrist and around the thigh. Each test consisted of a 1 min walk for participants to become accustomed to the treadmill, followed by a 2 min trial at ten pre-set speeds. Data from both sensors were collected in real-time. Intraclass correlation coefficient (ICC) was used to evaluate the equality of characteristics obtained by both sensors: maximum peaks, minimum peaks, and the mean of the complete signal (sequence of acceleration values along the time) by each axis and speed were extracted to evaluate the equality of characteristics obtained with LIS2DH12 compared to Actigraph. Intraclass correlation coefficient (ICC) was extracted, and a standard deviation of the mean was obtained from the data. Our results show that LIS2DH12 measurements present more reliability than Actigraph GT9X, ICC > 0.8 at three axes. This study concludes that LIS2DH12 is as reliable and accurate as Actigraph GT9X Link and, therefore, would be a suitable tool for future kinematic studies.

Item Type:Article
ISSN:2075-4426
Additional Information:This article belongs to the Special Issue Digital Health and Telemedicine: Their Contribution to Personalized and Precision Medicine
Uncontrolled Keywords:inertial sensors; R code; open-source code; reliability; functional assessment
Group:Faculty of Science & Technology
ID Code:37024
Deposited By: Symplectic RT2
Deposited On:06 Jun 2022 13:55
Last Modified:06 Jun 2022 13:55

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