Development of a Low-Cost Open-Source Measurement System for Joint Angle Estimation

The use of inertial measurement units (IMUs) is a low-cost alternative for measuring joint angles. This study aims to present a low-cost open-source measurement system for joint angle estimation. The system is modular and has hardware and software. The hardware was developed using a low-cost IMU and...

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Bibliographic Details
Published in:Sensors (Basel, Switzerland) Switzerland), 2021-09, Vol.21 (19), p.6477
Main Authors: de Almeida, Túlio Fernandes, Morya, Edgard, Rodrigues, Abner Cardoso, de Azevedo Dantas, André Felipe Oliveira
Format: Article
Language:English
Subjects:
Accelerometers
Algorithms
Communication
Data acquisition systems
Data processing
Data transmission
Evaluation
Gait
Inertial platforms
Internet Protocol
Joints (anatomy)
Kalman filters
Knee
Laboratories
Libraries
Literature reviews
Low cost
Modular systems
Open source software
sensor fusion
Sensors
sensors in healthcare
Servers
Wireless access points
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Summary:The use of inertial measurement units (IMUs) is a low-cost alternative for measuring joint angles. This study aims to present a low-cost open-source measurement system for joint angle estimation. The system is modular and has hardware and software. The hardware was developed using a low-cost IMU and microcontroller. The IMU data analysis software was developed in Python and has three fusion filters: Complementary Filter, Kalman Filter, and Madgwick Filter. Three experiments were performed for the proof of concept of the system. First, we evaluated the knee joint of Lokomat, with a predefined average range of motion (ROM) of 60∘. In the second, we evaluated our system in a real scenario, evaluating the knee of a healthy adult individual during gait. In the third experiment, we evaluated the software using data from gold standard devices, comparing the results of our software with Ground Truth. In the evaluation of the Lokomat, our system achieved an average ROM of 58.28∘, and during evaluation in a real scenario it achieved an average ROM of 44.62∘. In comparing our software with Ground Truth, we achieved a root-mean-square error of 0.04 and a mean average percentage error of 2.95%. These results encourage the use of this system in other scenarios.
ISSN:1424-8220
1424-8220
DOI:10.3390/s21196477