Development of Smart Aid for innovative Rehabilitation and Physiotherapy Procedures Using Artificial intelligence MethodsSupervisor: prof. Ing. Pavol Tanuška, PhD.
This page shows details on the project. The primary projects are displayed together with a list of sub-projects.
|Project description:||The aim of the project is the design and experimental verification of a set of smart devices represented by intelligent physioterapeutic aids. Depending on the nature of the physiotherapeutic aid, the device is adapted for specific use with regard to patient disability and patient rehabilitation. In practice, this means that a different mode may be set for the same disability (fracture, post-operative condition), depending on the patient's ability to use the device. The aid will be able, according to therapist's instructions, learning the correct movement patterns individually tailored to the patient, and will guide the patient using the aid correctly. The aid will also collect information about its use for a long time period, which will be primarily intended for the specialist. Thanks to its extended functionality – a set of sensors collecting information about the external conditions, its status and patient status, implementation of machine learning principles, data processing, communication with the wired/wireless system, power independent device – can be labeled as smart. Currently used rehabilitation aids have built-in sensors, but they provide only information on the current status enabling monitoring of the selected parameters during rehabilitation exercises. For these reasons, design and a pilot implementation of artificial intelligence principles (situation recognition, machine learning, classification) into the selected physioterapeutic aid is considered highly topical and necessary. Thanks to artificial intelligence, the aid can learn movement patterns tailored to the patient under the supervision of a physiotherapist. The benefits of the projects lie in eliminating painful conditions, shortening the rehabilitation process and sooner return to active life. This will increase the quality of the patient’s life and decrease financial loss of the patient during their sick leave. The state's treatment and rehabilitation costs will also be reduced.|
|Kind of project:||APVV - Všeobecná výzva ()|
|Department:||Institute of Applied Informatics, Automation and Mechatronics (MTF)|
|Project status:||Not approved|
|Project start date :||01. 07. 2018|
|Project close date:||30. 06. 2021|
|Number of workers in the project:||9|
|Number of official workers in the project:||9|
The following table shows the researcher workers who have been assigned official roles in a project.
|Mária Rešetková, MBA||administratíva|
|prof. Ing. Pavol Tanuška, PhD.||zodpovedný riešiteľ|
|Ing. Jela Abasová||spoluriešiteľ|
|doc. Ing. Michal Kebísek, PhD.||spoluriešiteľ|
|doc. Ing. Peter Schreiber, CSc.||spoluriešiteľ|
|Ing. Veronika Grígelová||spoluriešiteľ|
|Ing. Lukáš Špendla, PhD.||spoluriešiteľ|
|prof. Ing. Pavel Važan, PhD.||spoluriešiteľ|
|doc. Mgr. Róbert Vrábeľ, PhD.||spoluriešiteľ|