A New Quantitative Analysis for Prostheses Research and Evaluation

A New Quantitative Analysis for Prostheses Research and Evaluation: A Sensor Fusion Approach

Remmerswaal, Evan (TU Delft Mechanical, Maritime and Materials Engineering)

Kok, M. (mentor)
Smit, G. (graduation committee)
van Wingerden, J.W. (graduation committee)

Delft University of Technology

Mechanical Engineering | Systems and Control

2020-09-14

Problem: Due to high rejection rates regarding prostheses’ use, the assessment of the amputee’s use of the prosthesis has become more critical. Today’s prosthesis research is limited to assessing a users’ performance to perform tasks in a controlled environment. Therefore, these studies cannot wholly assess how the prosthesis is used in the daily lives of amputees. Purpose: The purpose of this thesis project is to create, test, and examine the performance of methods that can be used to enhance prostheses' research and evaluation. Results: We have created several enhancements and extensions regarding prosthesis research and evaluation for three sensor scenarios. In the first scenario, we only use an accelerometer, which allowed us to create a new method for creating a vector magnitude (VM) that can show us what type of arm movement is made; additionally, we created a novel scoring system to determine the intensity of movements that are performed. In our second scenario, we used an additional gyroscope, which opened up possibilities for using more advanced Sensor Fusion (SF) techniques. We created an accurate tilt estimation algorithm that remains robust against high levels of gyroscope noise, accelerometer outliers, and measurement model violations. With the gyroscope, we were also able to create a VM from rotational velocity, which displays information about the arms’ rotational movement. Additionally, we created a novel scoring system that also shows the intensity of the performed movements. Our last scenario considers the use of two Inertial Measurement Units (IMUs); we present a novel algorithm for estimating the relative sensor orientation. This algorithm uses a joint kinematic estimation method that incorporates the connection between adjacent segments within a SF algorithm that remains accurate in the vicinity of common real-world disturbances, among which are; high levels of gyroscope noise, accelerometer outliers, and Soft-Tissue-Artifacts (STA). Conclusion: The best way to enhance the analysis for prostheses research and evaluation is to start incorporating gyroscopes into the research process. This can either be in the form of the single sensor case or the double sensor system. The additional gyroscope(s) will enable the use the SF techniques and methods as discussed in this report.

Prostheses
Relative sensor orientation estimation
Joint kinematics
Tilt estimation
Movement Visualization
Accelerometer
Gyroscope
Inertial Measurement Unit
Sensor Fusion
Sensor
Fusion
Soft-Tissue-Artifacts
STA
disturbance
Magnetometer-free
Orientation Estimation
Orientation

http://resolver.tudelft.nl/uuid:063a483b-26e0-4da3-a297-1d38a013cae3

2022-09-01

Student theses

master thesis

© 2020 Evan Remmerswaal