Robot-Based Training for People With Mild Cognitive Impairment
| Autor: | Oliver Armbruster, Michael Mende, Björn Hein, Xingbo Wang, Patric Meyer, Denis Stogl |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
0209 industrial biotechnology
medicine.medical_specialty Control and Optimization Computer science Controller (computing) Biomedical Engineering Physical activity 02 engineering and technology Postural control 020901 industrial engineering & automation Physical medicine and rehabilitation User experience design Artificial Intelligence 0202 electrical engineering electronic engineering information engineering medicine Cognitive impairment Motor skill business.industry Mechanical Engineering 020208 electrical & electronic engineering Work (physics) Neuropsychology Training (meteorology) Mobile robot Computer Science Applications Human-Computer Interaction Control and Systems Engineering Robot Computer Vision and Pattern Recognition business |
| Zdroj: | IEEE Robotics and Automation Letters. 4:1916-1923 |
| ISSN: | 2377-3774 |
| DOI: | 10.1109/lra.2019.2898470 |
| Popis: | Current research suggests that physical activity has positive effects on the overall state of people with mild cognitive impairment (MCI) and that the use of new technologies could help those people to keep and improve their postural control and motor skills. In a pilot study, we investigated the use of a device based on a mobile robot for the motor activation of people with MCI, with the goal of investigating the possible influence of such an activity on the cognitive level. The device is an omnidirectional robot platform with handlebars and an integrated force-torque sensor to enable direct interaction with a user. A passive interaction controller with high-level interaction modes for training scenarios is developed. The device and the training are evaluated with ten participants (eight males and two females) from 66 to 78 years of age with MCI in five 1-h sessions. Here, we present the data gathered with the device and the evaluation of the user experience. The results for the precision of controlling the device and the time performance show that the users got better during the training week for most tasks. The participants felt safe during the training and managed to adapt to changes in the device's high-level behavior. Overall, the current results suggest that the proposed training is feasible and the device is suitable for the training. Future work will evaluate pre- and post-training MRI data and data from neuropsychological and memory testing to investigate impacts of the training with the robotic device on the cognitive level of a user. |
| Databáze: | OpenAIRE |
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