Thesis Project Form
Title (tentative): Test of an assistive and rehabilitative a myoelectric computer interfaceThesis advisor(s): Casadio Maura, Camilla Pierella Giorgia Marchesi | E-mail: |
Address: Via Opera Pia 13, 16145 Genova (ITALY) | Phone: (+39) 010 33 52749 |
Description
Motivation and application domain
Human-Machine Interfaces are technological solutions for helping people with disabilities to interact with external devices or overcome limitations due to their condition but are also used for rehabilitation purposes. These systems usually take as input one bio-signal (or more) and transform it in a control signal for an external device, e.g. cursor of a computer. One possible bio-signal is the electromyographic (EMG) signal, and in this case, we will have a Myoelectric Computer Interface (MCI). The control of the external device can be of different nature, for example with the EMG one can control the position of the cursor or its velocity. In this work, we want to test a Myoelectric Computer Interface that allows a simple and intuitive interaction between the user and the computer. More precisely, we want to characterize the effect of age in the learning process happening when using the MCI.
General objectives and main activities
The proposed thesis has the two main goals:
- Test how old adults learn how to use a myoelectric interface
- Study whether the learning depends on age.
- Experiment planning, data collection,data analysis
- Test how old adults learn how to use a myoelectric interface
- Study whether the learning depends on age.
- Experiment planning, data collection,data analysis
Training Objectives (technical/analytical tools, experimental methodologies)
The student will learn to:
1. Running experiments with human participants
2. Developing a study according to the ethical guidelines
3. Study how to assess learning in motor control
4. Study the most informative parameters to be used by clinicians in order to keep track of the state of wealth of the subject
5. Improve the knowledge of data analysis algorithms and statistical analysis.
1. Running experiments with human participants
2. Developing a study according to the ethical guidelines
3. Study how to assess learning in motor control
4. Study the most informative parameters to be used by clinicians in order to keep track of the state of wealth of the subject
5. Improve the knowledge of data analysis algorithms and statistical analysis.
Place(s) where the thesis work will be carried out: DIBRIS & joints labs
Additional information
Maximum number of students: 1