[TMP-090] Neural mechanism in human brain activity during weight lifting
Investigation on whether EEG signals can be used for detecting the motion and the variable weights a person is lifting
This micro project investigated whether EEG (electroencephalography) signal can be used for detecting the motion as well as the variable weights a person is lifting. An experimental paradigm has been designed and EEG data have been acquired during performing biceps flexion-extension motions for different weight categories: lifting with no weight (empty), medium, and heavy lifting. The outcomes of the project can be applied in industrial exoskeleton applications as well as physical rehabilitation of stroke patients.
Features in EEG data generating difference for each lifted weight of category have been investigated. EEG data via different two EEG headsets have been collected from various participants while they lift different categories of load, namely empty, medium and heavy, in this project. Then, EEG data have been analyzed to realize if different category of weights result in difference in EEG data by applying different deep learning methods together with different machine learning methods. According to the obtained results, it can be said that EEG signals can be successfully used as a method to predict different loads during dynamic bicep curl motion. Therefore, this result could result in more research to develop rehabilitation systems robust to dynamic changes in weight. Moreover, information regarding weight change could contribute to a better estimation of fatigue conditions to be used in sports and training applications. Finally, it has been evaluated that the approach to predict different categories of lifted weight could be used in further optimizations in industrial applications for which usage of exoskeleton can be given as an example. Results of Micro-Project in which TUBITAK BILGEM and Deutsches Forschungszentrum für Künstliche Intelligenz (DFKI) Kaiserslautern collaborated was presented at the IEEEEMBS International Conference on Biomedical and Health Informatics jointly organised with the IEEE-EMBS International conference on Wearable and Implantable Body Sensor Networks organized in Ioannina, Greece between 27-30 September 2022. Also it was published with the title “Prediction of Lifted Weight Category Using EEG Equipped Headgear” in 2022 IEEE-EMBS International Conference on Biomedical and Health Informatics Conference Proceedings.
Tangible Outcomes
- “Prediction of Lifted Weight Category Using EEG Equipped Headgear”, published in 2022 IEEE-EMBS International Conference on Biomedical and Health Informatics.
https://ieeexplore.ieee.org/document/ - dataset: https://www.ai4europe.eu/research/research-bundles/neural-mechanism-human-brain-activity-during-weight-lifting?category=ai_assets
- Presentation at the IEEE-EMBS International Conference on Biomedical and Health Informatics jointly organised with the IEEE-EMBS International conference on Wearable and Implantable Body Sensor Networks organized in Ioannina, Greece between 27-30 September 2022.
Partners
- TUBITAK BILGEM, Sencer Melih Deniz, sencer.deniz@tubitak.gov.tr
- DFKI Kaiserslautern, Hamraz Javaheri, Hamraz.Javaheri@dfki.de