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Related Experiment Video

Updated: Jun 18, 2026

Simultaneous Scalp Electroencephalography (EEG), Electromyography (EMG), and Whole-body Segmental Inertial Recording for Multi-modal Neural Decoding
11:25

Simultaneous Scalp Electroencephalography (EEG), Electromyography (EMG), and Whole-body Segmental Inertial Recording for Multi-modal Neural Decoding

Published on: July 26, 2013

An accuracy aware low power wireless EEG unit with information content based adaptive data compression.

Jeremy R Tolbert1, Pratik Kabali, Simeranjit Brar

  • 1Georgia Institute of Technology, Atlanta, GA 30332, USA. jeremy.r.tolbert@gatech.edu

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
|December 8, 2009
PubMed
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This study introduces an adaptive data compression system for low-power wireless Electroencephalography (EEG) transmission. The system optimizes energy use and data accuracy for efficient wireless EEG monitoring.

Area of Science:

  • Biomedical Engineering
  • Signal Processing
  • Wireless Communication

Background:

  • Wireless transmission of Electroencephalography (EEG) data faces challenges in power consumption and data volume.
  • Existing systems often require a trade-off between signal accuracy and energy efficiency.

Purpose of the Study:

  • To develop a digital system for adaptive data compression for low-power wireless EEG transmission.
  • To enable real-time accuracy-energy trade-offs in multi-channel EEG signal transmission.

Main Methods:

  • A digital system designed as a base-band processor between the EEG analog-to-digital front-end and RF transceiver.
  • Implementation of a multi-core digital signal processor for on-chip EEG signal processing.
  • Real-time adaptive compression algorithms to control transmitted data volume based on signal information.

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Recording Human Electrocorticographic (ECoG) Signals for Neuroscientific Research and Real-time Functional Cortical Mapping
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Recording Human Electrocorticographic (ECoG) Signals for Neuroscientific Research and Real-time Functional Cortical Mapping

Published on: June 26, 2012

Related Experiment Videos

Last Updated: Jun 18, 2026

Simultaneous Scalp Electroencephalography (EEG), Electromyography (EMG), and Whole-body Segmental Inertial Recording for Multi-modal Neural Decoding
11:25

Simultaneous Scalp Electroencephalography (EEG), Electromyography (EMG), and Whole-body Segmental Inertial Recording for Multi-modal Neural Decoding

Published on: July 26, 2013

Recording Human Electrocorticographic (ECoG) Signals for Neuroscientific Research and Real-time Functional Cortical Mapping
13:32

Recording Human Electrocorticographic (ECoG) Signals for Neuroscientific Research and Real-time Functional Cortical Mapping

Published on: June 26, 2012

Main Results:

  • The proposed system effectively manages the accuracy-energy trade-off for EEG signal transmission.
  • Significant savings in transmitter power were achieved through adaptive data compression.
  • Minimal impact on the overall signal accuracy was observed.

Conclusions:

  • The developed digital system offers an efficient solution for low-power wireless EEG data transmission.
  • On-chip adaptive compression using multi-core processors enhances power efficiency without compromising signal integrity.
  • This approach is promising for improving the feasibility of wireless EEG monitoring systems.