We develop technical systems that functionally support their users and provide them with a positive experience.Our research approach equally considers human factors and technical requirements based on a mixture of methods from engineering and human sciences. We demonstrate our findings on wearable systems such as prostheses or exoskeletons, cognitive systems such as collaborative or humanoid robots, and general applications with tight human-robot interaction.
- Fault diagnosis and tolerance for elastic actuation systems in robotics: physical human-robot interaction
- Active transfer learning with neural networks through human-robot interactions (TRAIN)
- EFFENDI – EFficient and Fast text ENtry for persons with motor disabilities of neuromuscular origin
EFFENDI - EFficient and Fast text ENtry for persons with motor Disabilities of neuromuscular orIgin
(Third Party Funds Single)Term: 1. February 2021 - 30. June 2022
Funding source: DFG-Einzelförderung / Sachbeihilfe (EIN-SBH)The EFFENDI project investigates possibilities to assist persons with neuromuscular diseases in entering text quickly and efficiently. The project was inspired by the search of the applicant for a suitable way to operate a computer and to enter text. The applicant has been diagnosed with the progressive neuromuscular disorder Friedreich Ataxia more than 25 years ago. Being a researcher, he is obliged to use a computer for up to ten hours per day, but due to his disease, he had growing problems with the standard keyboard, making text entry very cumbersome and error prone for him. During his year long search for a suitable alternative, he came across many solutions, some exceeding his abilities by far, others demanding only a fraction of what he was able to deliver. Nothing was JUST RIGHT. To fill this gap, the applicant decided to develop his own alternative. With the idea in mind that what works for him should help others as well, the overall objective was not to concentrate on only one single case, but to consider the thus far neglected group of patients with neuromuscular diseases as a whole. The outcome, OnScreenDualScribe, is a very powerful tool allowing to replace the standard input devices for computer operation, full size keyboard and mouse, with a single device. An extension for the renewal is to search for an optimal input device for persons with neuromuscular diseases. This would also yield a solution suitable for able-bodied users with respect to several applications, e.g., a Travel Companion. The applicant completely switched to the new input method, meaning that he almost uses nothing else to operate a computer. It really has changed his life. For example, the applicant never liked writing emails as that was just effortful work for him. Now he does, since entering longer texts in ambiguous mode is a breeze. OnScreenDualScribe is very suitable for persons who are able to control both hands. Another part of the project aims at emulating this manual interaction with the help of various signals detected by different wearable sensors. Although the sensor platform is already existent regarding the basic hardware architecture, the number of detectable sensor signals is still much too small to allow first user tests. An idea to top up the number of input signals is to develop a limited vocabulary speech recognition tool that works for people with dysarthria. A different idea is to investigate a touch based spin off of OnScreenDualScribe which could open the long closed door to tablets and smartphones for persons with neuromuscular diseases. As the results are really promising, but actually just represent the beginning, the applicant would love to have a chance to go on, in excess to the already approved nine more months, as described in the renewal proposal.
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- Cansev, M.E., Nordheimer, D., Kirchner, E.A., & Beckerle, P. (2021). Feel-Good Requirements: Neurophysiological and Psychological Design Criteria of Affective Touch for (Assistive) Robots. Frontiers in Neurorobotics. https://dx.doi.org/10.3389/fnbot.2021.661207
- Cansev, M.E., Xue, H., Rottmann, N., Bliek, A., Miller, L.E., Rueckert, E., & Beckerle, P. (2021). Interactive Human–Robot Skill Transfer: A Review of Learning Methods and User Experience. Advanced Intelligent Systems. https://dx.doi.org/10.1002/aisy.202000247
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- Del Vecchio, A., Castellini, C., & Beckerle, P. (2021). Peripheral Neuroergonomics – An Elegant Way to Improve Human-Robot Interaction? Frontiers in Neurorobotics, 15. https://dx.doi.org/10.3389/fnbot.2021.691508
- Galljamov, R., Ahmadi, A., Mohseni, O., Seyfarth, A., Beckerle, P., & Sharbafi, M.A. (2021). Adjustable Compliance and Force Feedback as Key Elements for Stable and Efficient Hopping. IEEE Robotics and Automation Letters, 6(4), 6797-6804. https://dx.doi.org/10.1109/LRA.2021.3095024
- Schuermann, T., & Beckerle, P. (2020). Personalizing Human-Agent Interaction Through Cognitive Models. Frontiers in Psychology, 11. https://dx.doi.org/10.3389/fpsyg.2020.561510