Version 1
: Received: 8 January 2024 / Approved: 9 January 2024 / Online: 9 January 2024 (06:49:36 CET)
Version 2
: Received: 9 April 2024 / Approved: 9 April 2024 / Online: 10 April 2024 (13:21:50 CEST)
David, J.P.; Schick, D.; Rapp, L.; Schick, J.; Glaser, M. SensAA—Design and Verification of a Cloud-Based Wearable Biomechanical Data Acquisition System. Sensors2024, 24, 2405.
David, J.P.; Schick, D.; Rapp, L.; Schick, J.; Glaser, M. SensAA—Design and Verification of a Cloud-Based Wearable Biomechanical Data Acquisition System. Sensors 2024, 24, 2405.
David, J.P.; Schick, D.; Rapp, L.; Schick, J.; Glaser, M. SensAA—Design and Verification of a Cloud-Based Wearable Biomechanical Data Acquisition System. Sensors2024, 24, 2405.
David, J.P.; Schick, D.; Rapp, L.; Schick, J.; Glaser, M. SensAA—Design and Verification of a Cloud-Based Wearable Biomechanical Data Acquisition System. Sensors 2024, 24, 2405.
Abstract
Exoskeletons designed to assist patients with activities of daily living are becoming increasingly popular, but still are subject to research. In order to gather requirements for the design of such systems, long-term gait observation of the patients over the course of multiple days in an environment of daily living are required. In this paper a wearable all-in-one data acquisition system for collecting and storing biomechanical data in everyday life is proposed. The system is designed to be cost efficient and easy to use, using off-the-shelf components and a cloud server system for centralized data storage. The measurement accuracy of the system was verified, by measuring the angle of the human knee joint at walking speeds between 3 and 12 km/h in reference to an optical motion analysis system. The acquired data was uploaded to a cloud database via a smartphone application. Verification results showed that the proposed toolchain works as desired. The system reached an RMSE from 2.9° to 8°, which is below most of the comparable system. The system provides a powerful, scalable platform for collecting and processing biomechanical data, which can help to automize the generation of an extensive database for human kinematics.
Keywords
Medical Engineering, biomechanics; exoskeleton; active knee orthosis; motion analysis; sensor technologies; human activity recognition
Subject
Engineering, Bioengineering
Copyright:
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.
