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The heart rhythms, controlled by the autonomic nervous system, can fluctuate with varying cognitive loads that can be captured with electrocardiogram (ECG) and heart rate variability (HRV) metrics. In this paper, we report customization of a wireless, ambulatory NeuroMonitor device originally developed for collecting electroencephalogram (EEG) signals as a platform for ECG and HRV data collection...
Wireless and wearable EEG device for home based long-term non intrusive diagnosis for therapy applications like ASD, ADHD, Epilepsy and other neurological disorders is crucial. This work presents the NeuroMonitor (rev. 2.0) platform designed to record EEG signals from two (bipolar or referential montage) channels. The device is lightweight 41.8g (with 900mAh battery and 3 electrodes) and miniature,...
In this paper we present a complete study on the balance between high performance image processing and low power consumption without using expensive components. Our proposal consists in implementing a Discrete Time Cellular Neural Network (DT-CNN) on a low power Actel IGLOO nano Field Programmable Gate Array (FPGA). This is a definitive step further from previous work to obtain an intelligent camera...
This paper introduces two applications of Discrete Time Cellular Non-Linear Networks (DTCNN) in a robot guiding avoiding obstacles algorithm and prove the feasibility of both applications: a high data rate one, using a CMOS camera, and small data rate one, using ultrasonic sensors. The key value of DTCNNs is the locally connections and the parallelism in processing. These characteristics permit a...
This paper presents an implementation of a DTCNN, programmed entirely in LEGO Mindstorms NXT robot to, together with perceptron, guide a robot avoiding obstacles. The map will be processed DTCNN obtained from ultrasonic and infrared sensors. The main objective of this implementation is to demonstrate the feasibility of implementing these and other applications of the CNN with Minstorm LEGO NXT.
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