Characterizing Accuracy Trade-offs of EEG Applications on Embedded HMPs

arXiv:2402.09867v1 Announce Type: cross
Abstract: Electroencephalography (EEG) recordings are analyzed using battery-powered wearable devices to monitor brain activities and neurological disorders. These applications require long and continuous processing to generate feasible results. However, wearable devices are constrained with limited energy and computation resources, owing to their small sizes for practical use cases. Embedded heterogeneous multi-core platforms (HMPs) can provide better performance within limited energy budgets for EEG applications. Error resilience of the EEG application pipeline can be exploited further to …

abstract accuracy applications arxiv battery brain computation continuous cs.ai cs.cv cs.lg cs.pf devices eeg eess.sp embedded energy generate practical processing resources small trade type wearable wearable devices