Epileptic Seizure Detection on an Ultra-Low-Power Embedded RISC-V Processor Using a Convolutional Neural Network

The treatment of refractory epilepsy via closed-loop implantable devices that act on seizures either by drug release or electrostimulation is a highly attractive option. For such implantable medical devices, efficient and low energy consumption, small size, and efficient processing architectures are essential. To meet these requirements, epileptic seizure detection by analysis and classification of brain signals with a convolutional neural network (CNN) is an attractive approach. This work presents a CNN for epileptic seizure detection capable of running on an ultra-low-power microprocessor. The CNN is implemented and optimized in MATLAB. In addition, the CNN is also implemented on a GAP8 microprocessor with RISC-V architecture. The training, optimization, and evaluation of the proposed CNN are based on the CHB-MIT dataset. The CNN reaches a median sensitivity of 90% and a very high specificity over 99% corresponding to a median false positive rate of 6.8 s per hour. After implementation of the CNN on the microcontroller, a sensitivity of 85% is reached. The classification of 1 s of EEG data takes t=35 ms and consumes an average power of P≈140 μW. The proposed detector outperforms related approaches in terms of power consumption by a factor of 6. The universal applicability of the proposed CNN based detector is verified with recording of epileptic rats. This results enable the design of future medical devices for epilepsy treatment

PKA-dependent potentiation of glucose-stimulated insulin secretion by Epac activator 8-pCPT-2′-O-Me-cAMP-AM in human islets of Langerhans

Potential insulin secretagogue properties of an acetoxymethyl ester of a cAMP analog (8-pCPT-2′-O-Me-cAMP-AM) that activates the guanine nucleotide exchange factors Epac1 and Epac2 were assessed using isolated human islets of Langerhans. RT-QPCR demonstrated that the predominant variant of Epac expressed in human islets was Epac2, although Epac1 was detectable. Under conditions of islet perifusion, 8-pCPT-2′-O-Me-cAMP-AM (10 μM) potentiated first- and second-phase 10 mM glucose-stimulated insulin secretion (GSIS) while failing to influence insulin secretion measured in the presence of 3 mM glucose. The insulin secretagogue action of 8-pCPT-2′-O-Me-cAMP-AM was associated with depolarization and an increase of [Ca2+]i that reflected both Ca2+ influx and intracellular Ca2+ mobilization in islet β-cells. As expected for an Epac-selective cAMP analog, 8-pCPT-2′-O-Me-cAMP-AM (10 μM) failed to stimulate phosphorylation of PKA substrates CREB and Kemptide in human islets. Furthermore, 8-pCPT-2′-O-Me-cAMP-AM (10 μM) had no significant ability to activate AKAR3, a PKA-regulated biosensor expressed in human islet cells by viral transduction. Unexpectedly, treatment of human islets with an inhibitor of PKA activity (H-89) or treatment with a cAMP antagonist that blocks PKA activation (Rp-8-CPT-cAMPS) nearly abolished the action of 8-pCPT-2′-O-Me-cAMP-AM to potentiate GSIS. It is concluded that there exists a permissive role for PKA activity in support of human islet insulin secretion that is both glucose dependent and Epac regulated. This permissive action of PKA may be operative at the insulin secretory granule recruitment, priming, and/or postpriming steps of Ca2+-dependent exocytosis