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Early Seizure Detection with an Energy-Efficient Convolutional Neural Network on an Implantable Microcontroller
- M. Hügle, S. Heller, J. Boedecker
- Computer ScienceInternational Joint Conference on Neural Networks…
- 12 June 2018
This paper presents a convolutional neural network for the early detection of seizures from in- tracranial EEG signals, designed specifically for this purpose and is the only approach suited to be realized on a low power microcontroller due to its parsimonious use of computational and memory resources.
A Comparison of Machine Learning Classifiers for Energy-Efficient Implementation of Seizure Detection
- F. Manzouri, S. Heller, M. Dümpelmann, P. Woias, A. Schulze-Bonhage
- Computer ScienceFront. Syst. Neurosci.
- 20 September 2018
The feature set in combination with Random Forest classifier is an energy efficient hardware implementation that shows an improvement of detection sensitivity and specificity compared to the presently available closed-loop intervention in epilepsy while preserving a low detection delay.
Hardware Implementation of a Performance and Energy-optimized Convolutional Neural Network for Seizure Detection
- S. Heller, M. Hügle, P. Woias
- Computer Science40th Annual International Conference of the IEEE…
- 1 July 2018
This work presents for the first time a μW-power convolutional neural network for seizure detection running on a low-power microcontroller that is suitable for the application in an implantable closed-loop device.
A water-powered Energy Harvesting system with Bluetooth Low Energy interface
This paper reports the design, and testing of a water turbine generator system for typical flow rates in domestic applications, with an integrated power management and a Bluetooth low energy (BLE)…
Self-sufficient electronic control for nonlinear, frequency tunable, piezoelectric vibration harvesters
Research in vibration energy harvesting focuses increasingly on nonlinear harvesters. In comparison to linear harvesters they show an inherent larger bandwidth through hardening or softening effects…
A low-voltage boost converter using a forward converter with integrated Meissner oscillator
This paper describes a novel boost converter to be used with energy harvesters that provide only low output voltages. The device is self-supplied from electric power delivered to its input. With peak…
A highly sensitive and ultra-low-power wake-up receiver for energy-autonomous embedded systems
This article presents the design, optimization and characterization of an ultra-low-power wake-up receiver for embedded wireless sensor nodes, based on an optimized diode detector for an amplitude-modulated 315 MHz RF carrier, followed by anUltra-low power low-frequency (LF) amplifier for the demodulated signal.
Optimized detector for closed-loop devices for neurostimulation
- F. Manzouri, A. Schulze-Bonhage, M. Dümpelmann, S. Heller, P. Woias
- Computer ScienceIEEE International Conference on Systems, Man…
- 1 October 2017
Results of this optimization process indicate a decrease of detection delay, which is crucial to successful seizure suppression, and increased sensitivity; while preserving the false positive detections low compared to presently available closed-loop intervention in epilepsy.
A narrow-band and ultra-low-power 433 MHz wake-up receiver
This work presents the design and characterization of an ultra-low-power wake-up receiver, based on an optimized modulation/demodulation concept, to achieve a high RF sensitivity and narrow-band operation at the same time.
Three channel high dynamic current measurement system for low power systems
- S. Heller, I. Nematollahi, S. Koeble, P. Woias
- Computer ScienceJournal of Physics: Conference Series
- 1 July 2018
A measurement system is presented that allows the simultaneous measurement of three current ranges from 1 µA to 30 mA at a sample rate of 1 MHz with a selectable supply voltage in the range of 1.8 V to 3.3 V.