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Comparison of inertial measurement units for capturing human movement
Wearable sensors, such as inertial measurement units (IMUs), have become a viable tool in neurological rehabilitation and can be utilized in various ways. They can be used to assess motor impairments, guide motor recovery, and evaluate the effectiveness of interventions. Since IMUs are lightweight and easy to wear, they are particularly useful for measuring upper limb movement and can provide a wide range of kinematic and kinetic information, including movement smoothness, speed or range of motion.
However, as there are various commercially available sensors with varying characteristics, deciding which one to choose becomes challenging. This study will assess each IMU's accuracy, precision, temporal characteristics and ease of use regarding wearability, data accessibility, streaming capabilities and configurability. This can provide valuable information for researchers and clinicians to select the appropriate IMU for their specific application, according to the research aim. To do so, an overview of the sensor characteristics and an assessment battery to compare the sensors are necessary.
Keywords: Inertial Measurement Unit, Neurological rehabilitation, Human movement capture, Wearable sensor
This project aims to prepare and conduct a systematic comparison of different types of IMUs, to determine their suitability for measuring human movement in patients with neurological impairments. The tasks will involve a literature search as well as developing and implementing a test bench and protocol to systematically and efficiently compare the IMUs, analyzing their data output and comparing the results. For this purpose, several commercial sensors and the ZurichMOVE system are available at the lab.
This project aims to prepare and conduct a systematic comparison of different types of IMUs, to determine their suitability for measuring human movement in patients with neurological impairments. The tasks will involve a literature search as well as developing and implementing a test bench and protocol to systematically and efficiently compare the IMUs, analyzing their data output and comparing the results. For this purpose, several commercial sensors and the ZurichMOVE system are available at the lab.
The project aims to identify the most suitable IMU for measuring and streaming human movement in patients with neurological impairments.
The project aims to identify the most suitable IMU for measuring and streaming human movement in patients with neurological impairments.
- Literature research
- Development of a test bench and protocol
- Systematically compare different IMUs
- Presentations and final report
- Literature research - Development of a test bench and protocol - Systematically compare different IMUs - Presentations and final report
The ideal candidate for this project should have a background in Mechanical Engineering/ Health Sciences and Technology/ Electrical Engineering/ Biomedical Engineering. You are highly motivated and interested in biomechanics, IMUs, and their applications. Additionally, you are excited to apply your analytical and problem-solving skills and can work independently and in a team environment. Experience with IMUs, as well as proficiency in programming and data analysis, are a plus.
The ideal candidate for this project should have a background in Mechanical Engineering/ Health Sciences and Technology/ Electrical Engineering/ Biomedical Engineering. You are highly motivated and interested in biomechanics, IMUs, and their applications. Additionally, you are excited to apply your analytical and problem-solving skills and can work independently and in a team environment. Experience with IMUs, as well as proficiency in programming and data analysis, are a plus.
If you are interested or have further questions, please get in touch with Laura Mayrhuber (laura.mayrhuber@hest.ethz.ch).
Please include your CV and transcript of records in your application.
If you are interested or have further questions, please get in touch with Laura Mayrhuber (laura.mayrhuber@hest.ethz.ch). Please include your CV and transcript of records in your application.
20230124_ReLAB_Project-Announcement_IMU.pdf
