TFG: Assistance exoskeletons in rehabilitation and pose IA models
Verónica Tornero has successfully presented her final degree project named “Sistema de control para la rehabilitación motora con un exoesqueleto y evaluación de redes posnet como ayuda a terapias”.
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| Git Repository | Link |
| Tutor | Roberto Calvo Palomino |
Robotics and Artificial Intelligence (AI) are areas in continuous expansion that covers many different fields. One of the sectors that has benefited the most of the development of this industry is medicine. People who present any injury, disability, who need help to walk or who have suffered an accident cerebrovascular disease, require assistance to accelerate their recovery and improve their quality of life. Exoskeletons play a fundamental role by allowing them to perform rehabilitation exercises quickly and efficiently, relieving the physical load of the therapists involved. Due to this, designing and developing new programs of rehabilitation that are integrated into these devices is absolutely necessary, with the purpose of addressing the different problems that patients face in your recovery process.
In collaboration with the company Marsi Bionics, a new exercise has been designed rehabilitation for an exoskeleton. After a study of pre-existing information on the device, the necessary content was extracted and a new control system based on the movement of the squats. Thanks to this system, patients will be able to perform exercises of this type, which is important considering note that it is not a common movement in current devices. Besides, am evaluation has been made with pose neural network models, in order to provide additional assistance in situations where the exoskeleton is not available.
Finally, in this project it has been possible to develop a solid and stable solution of the proposed exercise, as well as a comparison of two neural network models verifying that, indeed, although the results are more accurate using the exoskeleton, could be used for support and additional help.
In collaboration with the company Marsi Bionics, a new exercise has been designed rehabilitation for an exoskeleton. After a study of pre-existing information on the device, the necessary content was extracted and a new control system based on the movement of the squats. Thanks to this system, patients will be able to perform exercises of this type, which is important considering note that it is not a common movement in current devices. Besides, am evaluation has been made with pose neural network models, in order to provide additional assistance in situations where the exoskeleton is not available.
Finally, in this project it has been possible to develop a solid and stable solution of the proposed exercise, as well as a comparison of two neural network models verifying that, indeed, although the results are more accurate using the exoskeleton, could be used for support and additional help.