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Compressed Sensing Based Seizure Detection for an Ultra Low Power Multi-core Architecture
2018
2018 International Conference on High Performance Computing & Simulation (HPCS)
Extracting information from brain signals in advanced Brain Machine Interfaces (BMI) often requires computationally demanding processing. The complexity of the algorithms traditionally employed to process multi-channel neural data, such as Principal Component Analysis (PCA), dramatically increases while scaling-up the number of channels and requires more power-hungry computational platforms. This could hinder the development of low-cost and low-power interfaces which can be used in wearable or
doi:10.1109/hpcs.2018.00083
dblp:conf/ieeehpcs/AghazadehMBRF18
fatcat:sv6u6jm5bbexle2cm6rpxia2gu