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- Title
A brain machine interface framework for exploring proactive control of smart environments.
- Authors
Braun, Jan-Matthias; Fauth, Michael; Berger, Michael; Huang, Nan-Sheng; Simeoni, Ezequiel; Gaeta, Eugenio; Rodrigues do Carmo, Ricardo; García-Betances, Rebeca I.; Arredondo Waldmeyer, María Teresa; Gail, Alexander; Larsen, Jørgen C.; Manoonpong, Poramate; Tetzlaff, Christian; Wörgötter, Florentin
- Abstract
Brain machine interfaces (BMIs) can substantially improve the quality of life of elderly or disabled people. However, performing complex action sequences with a BMI system is onerous because it requires issuing commands sequentially. Fundamentally different from this, we have designed a BMI system that reads out mental planning activity and issues commands in a proactive manner. To demonstrate this, we recorded brain activity from freely-moving monkeys performing an instructed task and decoded it with an energy-efficient, small and mobile field-programmable gate array hardware decoder triggering real-time action execution on smart devices. Core of this is an adaptive decoding algorithm that can compensate for the day-by-day neuronal signal fluctuations with minimal re-calibration effort. We show that open-loop planning-ahead control is possible using signals from primary and pre-motor areas leading to significant time-gain in the execution of action sequences. This novel approach provides, thus, a stepping stone towards improved and more humane control of different smart environments with mobile brain machine interfaces.
- Subjects
SMART devices; DECODING algorithms; GATE array circuits; SCHEDULING; MACHINERY; MACAQUES
- Publication
Scientific Reports, 2024, Vol 14, Issue 1, p1
- ISSN
2045-2322
- Publication type
Article
- DOI
10.1038/s41598-024-60280-7