A Minimally Invasive Low-Power Platform for Real-Time Brain Computer Interaction Based on Canonical Correlation Analysis

• Published in: IEEE internet of things journal Vol. 6; no. 1; pp. 967 - 977
• Main Authors: Salvaro, Mattia, Benatti, Simone, Kartsch, Victor J., Guermandi, Marco, Benini, Luca
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.02.2019; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Batteries; Biomedical signal processing; brain-computer interfaces (BCIs); Correlation; Correlation analysis; Data acquisition; Decoding; Electrodes; Electroencephalography; embedded software; Feature extraction; Human computer interaction; Human-computer interface; Internet of Things; low-power electronics; Microcontrollers; Power consumption; real-time systems; Training; Visualization; Wearable technology

A growing trend in human-computer interaction is to integrate computational capabilities into wearable devices, to enable sophisticated and natural interaction modalities. Acting directly by decoding neural activity is a very natural way of interaction and one of the fundamental paradigms of brain c...