Thesis Project Form
Title (tentative): Development and test of a passive sitting platform for training and testing core stability| Thesis advisor(s): Casadio Maura, C. Pierella, G. Marchesi, G.Carlini, A. Canessa, M. Pagano | E-mail: |
| Address: Via Opera Pia 13, 16145 Genova (ITALY) | Phone: (+39) 010 33 52749 |
Description
Motivation and application domain
Core stability training is beneficial for strengthening both core and inner muscles, which are fundamental in everyday life for balance and movement initiation. The inability to properly decouple trunk muscles involved in such core stability is a common symptom of many neurological disorders such as Stroke, Multiple Sclerosis, and Spinal Cord Injury, resulting in incorrect behaviors that may additionally hamper an already unstable condition. Nevertheless, previous studies highlighted the beneficial effects of core stability training in lower back pain and in the sportive fields, while its role in people with neurological disorders is less well studied.
Moreover, the clinical environment is still lacking assessment tools for a complete evaluation targeting both muscles activations and trunk movements. Since it is well known that people with neurological disorders have problems in correctly selecting the right muscles needed for a specific movement, it may be useful to develop a low-cost tool that can be used both for assessment and training. For the latter, biofeedback may be used for teaching participants to re-learn correct muscle activation patterns and to decouple muscles that are not intended to be activated simultaneously. In such scenario, this project aims to develop a low-cost assessment tool able to integrate both electromyographic and inertial measurements extracted during the execution of rehabilitation and training exercises with a passive balance board to provide real-time biofeedback to improve the core stability in patients with neurological disorders
Moreover, the clinical environment is still lacking assessment tools for a complete evaluation targeting both muscles activations and trunk movements. Since it is well known that people with neurological disorders have problems in correctly selecting the right muscles needed for a specific movement, it may be useful to develop a low-cost tool that can be used both for assessment and training. For the latter, biofeedback may be used for teaching participants to re-learn correct muscle activation patterns and to decouple muscles that are not intended to be activated simultaneously. In such scenario, this project aims to develop a low-cost assessment tool able to integrate both electromyographic and inertial measurements extracted during the execution of rehabilitation and training exercises with a passive balance board to provide real-time biofeedback to improve the core stability in patients with neurological disorders
General objectives and main activities
The proposed thesis has 2 main aims:
Aim 1: Integrate and process electromyographic and inertial signals to develop core stability exercises and provide biofeedback to the users.
Aim 2: Testing the system with healthy and spinal cord injured subjects. A first evaluation will be carried out on healthy participants to assess its safety and effectiveness, subsequently test on spinal cord injury survivors will be carried out.
Aim 1: Integrate and process electromyographic and inertial signals to develop core stability exercises and provide biofeedback to the users.
Aim 2: Testing the system with healthy and spinal cord injured subjects. A first evaluation will be carried out on healthy participants to assess its safety and effectiveness, subsequently test on spinal cord injury survivors will be carried out.
Training Objectives (technical/analytical tools, experimental methodologies)
The student will learn to:
1. Program a Microcontroller for signals acquisition
2. Process and Analyze EMG signals
3. Improve the knowledge of Python/C#/MATLAB and statistical analysis
1. Program a Microcontroller for signals acquisition
2. Process and Analyze EMG signals
3. Improve the knowledge of Python/C#/MATLAB and statistical analysis
Place(s) where the thesis work will be carried out: Dibris & Laboratorio congiunto unita' spinale.
Additional information
Maximum number of students: 1