Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same journal

Microwave-assisted thermal profiling of blood: a potential biomarker for differentiating cancer and non-cancer states.

Journal of medical engineering & technology·2026
Same journal

News and Product Update.

Journal of medical engineering & technology·2026
Same journal

PMMA based ultra miniaturized implantable antenna for biotelemetry applications.

Journal of medical engineering & technology·2026
Same journal

Comparative machine learning for accurate EEG-based epileptic seizure state classification using sub-band analysis.

Journal of medical engineering & technology·2026
Same journal

Genetic algorithm-optimized machine learning approaches for EEG-based silent speech decoding.

Journal of medical engineering & technology·2026
Same journal

Power transition signatures of vibroarthrographic spectrograms for diagnosing knee joint pathologies.

Journal of medical engineering & technology·2026

Related Experiment Video

Updated: Feb 22, 2026

Standardized Measurement of Nasal Membrane Transepithelial Potential Difference NPD
09:47

Standardized Measurement of Nasal Membrane Transepithelial Potential Difference NPD

Published on: September 13, 2018

17.3K

A simple encoding method for Sigma-Delta ADC based biopotential acquisition systems.

Federico N Guerrero1, Enrique M Spinelli1

  • 1a Instituto de Investigaciones en Electrónica, Control, y Procesamiento de Señales LEICI (CONICET-UNLP) , La Plata , Argentina.

Journal of Medical Engineering & Technology
|September 29, 2017
PubMed
Summary
This summary is machine-generated.

A novel encoding method reduces data size for Sigma-Delta analogue-to-digital converters, crucial for biomedical signal acquisition. This lossless compression enhances efficiency in high-channel count systems and low-power platforms.

Keywords:
ECGEMGSigma Delta converterbiomedical signalbiopotentialdynamic rangeencodinglossless compression

More Related Videos

Simultaneous Application of Transcranial Direct Current Stimulation during Virtual Reality Exposure
08:20

Simultaneous Application of Transcranial Direct Current Stimulation during Virtual Reality Exposure

Published on: January 18, 2021

4.5K
A Procedure for Implanting Organized Arrays of Microwires for Single-unit Recordings in Awake, Behaving Animals
10:58

A Procedure for Implanting Organized Arrays of Microwires for Single-unit Recordings in Awake, Behaving Animals

Published on: February 14, 2014

13.7K

Related Experiment Videos

Last Updated: Feb 22, 2026

Standardized Measurement of Nasal Membrane Transepithelial Potential Difference NPD
09:47

Standardized Measurement of Nasal Membrane Transepithelial Potential Difference NPD

Published on: September 13, 2018

17.3K
Simultaneous Application of Transcranial Direct Current Stimulation during Virtual Reality Exposure
08:20

Simultaneous Application of Transcranial Direct Current Stimulation during Virtual Reality Exposure

Published on: January 18, 2021

4.5K
A Procedure for Implanting Organized Arrays of Microwires for Single-unit Recordings in Awake, Behaving Animals
10:58

A Procedure for Implanting Organized Arrays of Microwires for Single-unit Recordings in Awake, Behaving Animals

Published on: February 14, 2014

13.7K

Area of Science:

  • Biomedical Engineering
  • Signal Processing
  • Embedded Systems

Background:

  • Sigma-Delta analogue-to-digital converters offer high dynamic range for biomedical signals but generate large data volumes.
  • High-channel count biopotential systems (128-256 electrodes) face data transmission challenges, often requiring optic fiber links.
  • Low-power acquisition platforms struggle with data transmission over wireless links due to large sample sizes.

Purpose of the Study:

  • To present a low-complexity, lossless encoding method to decrease data size from Sigma-Delta converters.
  • To preserve the full DC-coupled signal integrity during data compression.
  • To reduce power consumption and improve data transmission efficiency in biomedical acquisition systems.

Main Methods:

  • Developed a low-complexity encoding algorithm for reducing sample data size.
  • Implemented the encoding method in C for an 8-bit microcontroller.
  • Evaluated the compression ratio using ECG and EMG signal datasets.

Main Results:

  • Achieved an average compression ratio of 2.3 over ECG and EMG signals.
  • The encoding method is lossless, preserving the full DC-coupled signal.
  • The C implementation required only 110 clock cycles on average for an 8-bit microcontroller, indicating low processing load.

Conclusions:

  • The proposed encoding method effectively reduces data size from Sigma-Delta converters without data loss.
  • This technique is suitable for high-channel count and low-power biomedical acquisition systems, improving data transmission efficiency.
  • The low computational requirement makes it ideal for implementation on resource-constrained microcontrollers.