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Clinical application: Assess gait variability parameters with inertial sensors (IMU)
This project focuses on the development and implementation of new gait analysis algorithms for use with our new inertial measurement units (IMUs), as well as their comparison with existing solutions and validation against motion capture data.
In clinical gait analysis, camera-based motion capture systems are considered to be the gold standard. The nowadays accurate IMU-sensors are not only easier to handle and less expensive than camera based systems, but also provide options for assessing the gait of patients in clinical and home based settings.
The IfB-MotionModule is a nine-axis IMU-based portable measurement device to assess quantitative motion parameters of specific body segments. Up to 14 IfB-MotionModules can be combined to a body area network. The proprietary radio protocol allows synchronous data acquisition with sampling jitter of less than 100 µs and simultaneous data rates of 1k Samples/s for all nine sensor axes within all the modules. The on-chip digital-motion-processor processes raw data directly into orientation data (quaternion representation) and stores them together with accelerometer- and gyroscope-data on a SD-card for further post-processing and analysis.
**Tasks**
10 % Literature review and planning of the study
20 % Integrate existing gait parameter algorithms
20 % Develop a new gait parameter algorithm
20 % Validation study of different algorithms and comparison with motion-capture system (VICON)
20 % Analysis of the results
10 % Preparation of report and presentation
In clinical gait analysis, camera-based motion capture systems are considered to be the gold standard. The nowadays accurate IMU-sensors are not only easier to handle and less expensive than camera based systems, but also provide options for assessing the gait of patients in clinical and home based settings.
The IfB-MotionModule is a nine-axis IMU-based portable measurement device to assess quantitative motion parameters of specific body segments. Up to 14 IfB-MotionModules can be combined to a body area network. The proprietary radio protocol allows synchronous data acquisition with sampling jitter of less than 100 µs and simultaneous data rates of 1k Samples/s for all nine sensor axes within all the modules. The on-chip digital-motion-processor processes raw data directly into orientation data (quaternion representation) and stores them together with accelerometer- and gyroscope-data on a SD-card for further post-processing and analysis.
**Tasks**
10 % Literature review and planning of the study
20 % Integrate existing gait parameter algorithms
20 % Develop a new gait parameter algorithm
20 % Validation study of different algorithms and comparison with motion-capture system (VICON)
20 % Analysis of the results
10 % Preparation of report and presentation
The aim of this project is to develop and implement a new gait parameter algorithm for comparison and validation with existing concepts and motion capture data.
We are therefore searching for a talented Master student with a background in the field of signal processing with a sound knowledge in Matlab and/or LabVIEW to undertake this interesting and challenging task, to begin from Sept 2015 onwards.
The aim of this project is to develop and implement a new gait parameter algorithm for comparison and validation with existing concepts and motion capture data.
We are therefore searching for a talented Master student with a background in the field of signal processing with a sound knowledge in Matlab and/or LabVIEW to undertake this interesting and challenging task, to begin from Sept 2015 onwards.
**Prof. Dr. William R. Taylor**
Institute for Biomechanics, HCI E 357.1
ETH Zurich,
Vladimir-Prelog-Weg 3-4,
8093 Zürich,
Switzerland
**Email:** taylorb@ethz.ch
**Tel:** +41 44 6330595
**Marco Hitz**
Institute for Biomechanics, HCI E 428
ETH Zurich,
Vladimir-Prelog-Weg 4,
8093 Zürich,
Switzerland
**Email:** mhitz@ethz.ch
**Tel:** +41 44 633 63 54