How We Found Our IMU: Guidelines to IMU Selection and a Comparison of Seven IMUs for Pervasive Healthcare Applications
by
Lin Zhou 1,*
, Eric Fischer 1, Can Tunca 2, Clemens Markus Brahms 3, Cem Ersoy 2, Urs Granacher 3 and Bert Arnrich 1,*
Lin Zhou 1,*, Eric Fischer 1, Can Tunca 2, Clemens Markus Brahms 3, Cem Ersoy 2, Urs Granacher 3 and Bert Arnrich 1,*
1
Digital Health Center, Hasso Plattner Institute, University of Potsdam, 14482 Potsdam, Germany
2
NETLAB, Department of Computer Engineering, Bogazici University, 34342 Istanbul, Turkey
3
Division of Training and Movement Sciences, University of Potsdam, 14469 Potsdam, Germany
*
Authors to whom correspondence should be addressed.
Sensors 2020, 20(15), 4090; https://doi.org/10.3390/s20154090
Received: 9 June 2020 / Revised: 12 July 2020 / Accepted: 16 July 2020 / Published: 22 July 2020
(This article belongs to the Special Issue Mobile Sensors for Healthcare)
Inertial measurement units (IMUs) are commonly used for localization or movement tracking in pervasive healthcare-related studies, and gait analysis is one of the most often studied topics using IMUs. The increasing variety of commercially available IMU devices offers convenience by combining the sensor modalities and simplifies the data collection procedures. However, selecting the most suitable IMU device for a certain use case is increasingly challenging. In this study, guidelines for IMU selection are proposed. In particular, seven IMUs were compared in terms of their specifications, data collection procedures, and raw data quality. Data collected from the IMUs were then analyzed by a gait analysis algorithm. The difference in accuracy of the calculated gait parameters between the IMUs could be used to retrace the issues in raw data, such as acceleration range or sensor calibration. Based on our algorithm, we were able to identify the best-suited IMUs for our needs. This study provides an overview of how to select the IMUs based on the area of study with concrete examples, and gives insights into the features of seven commercial IMUs using real data.
View Full-Text
▼
Show Figures
Figure 1
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited
MDPI and ACS Style
Zhou, L.; Fischer, E.; Tunca, C.; Brahms, C.M.; Ersoy, C.; Granacher, U.; Arnrich, B. How We Found Our IMU: Guidelines to IMU Selection and a Comparison of Seven IMUs for Pervasive Healthcare Applications. Sensors 2020, 20, 4090.
Show more citation formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.
Search more from Scilit
