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

Upsampling01:22

Upsampling

684
Managing signal sampling rates is essential in digital signal processing to maintain signal integrity. A decimated signal, characterized by a reduced frequency range due to its lower sampling rate, can be upsampled by inserting zeros between each sample. This upsampling process expands the original spectrum and introduces repeated spectral replicas at intervals dictated by the new Nyquist frequency. To refine this zero-inserted sequence, it is passed through a lowpass filter with a cutoff...
684
Downsampling01:20

Downsampling

755
When considering a sampled sequence with zero values between sampling instants, one can replace it by taking every N-th value of the sequence. At these integer multiples of N, the original and sampled sequences coincide. This process, known as decimation, involves extracting every N-th sample from a sequence, thereby creating a more efficient sequence.
The Fourier transform of the decimated sequence reveals a combination of scaled and shifted versions of the original spectrum. This...
755
Reconstruction of Signal using Interpolation01:10

Reconstruction of Signal using Interpolation

822
Signal processing techniques are essential for accurately converting continuous signals to digital formats and vice versa. When a continuous signal is sampled with a period T, the resulting sampled signal exhibits replicas of the original spectrum in the frequency domain, spaced at intervals equal to the sampling frequency. To handle this sampled signal, a zero-order hold method can be applied, which creates a piecewise constant signal by retaining each sample's value until the next...
822

You might also read

Related Articles

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

Sort by
Same author

Efficient lossless compression of nanopore sequencing signals.

Bioinformatics advances·2026
Same author

Ten years of data on small mammal species in Doñana (SW Spain): 2011-2021.

Biodiversity data journal·2025
Same author

Exploring a gene co-expression network throughout the trypanosoma cruzi life cycle.

BMC genomics·2025
Same author

Association of PD-1, LAG-3 and TIM-3 expression on intratumoral CD8 T-cells with response to atezolizumab in a Real-World-Evidence biomarker study for advanced urothelial carcinoma patients.

Oncoimmunology·2025
Same author

Tuning Matters: Comparing Lambda Optimization Approaches for Ridge Regression in Genomic Prediction.

Genes·2025
Same author

Mitochondrial morphology in fertile and infertile men: image processing and morphometric analysis of the sperm midpiece.

Frontiers in cell and developmental biology·2025
Same journal

An Ultra-Lightweight Cross-scale Attention Mamba Network for Accurate Skin Lesion Segmentation.

IEEE journal of biomedical and health informatics·2026
Same journal

Explanation-Guided Reconstruction of Missing Clinical Features for Survival Prediction in Pancreatic Cancer.

IEEE journal of biomedical and health informatics·2026
Same journal

stDGCN: A dual-augmentation graph convolutional network for identifying spatial domains with attention mechanism.

IEEE journal of biomedical and health informatics·2026
Same journal

Patient-specific Biomechanical Investigation of Percutaneous Pulmonary Valves: Towards the Integration of Routinely Acquired Clinical Data and Fluid-structure Interaction Simulations.

IEEE journal of biomedical and health informatics·2026
Same journal

Cross-subject fMRI-to-Image with Visual-cortex 2D Representation and Pre-Training.

IEEE journal of biomedical and health informatics·2026
Same journal

PGCASurv: A Prior-Guided Cross-Attention Framework for Dynamic Survival Model with Longitudinal Data.

IEEE journal of biomedical and health informatics·2026
See all related articles

Related Experiment Video

Updated: Mar 19, 2026

Microfluidic Platform with Multiplexed Electronic Detection for Spatial Tracking of Particles
11:54

Microfluidic Platform with Multiplexed Electronic Detection for Spatial Tracking of Particles

Published on: March 13, 2017

9.9K

Efficient Sequential Compression of Multichannel Biomedical Signals.

Ignacio Capurro, Federico Lecumberry, Alvaro Martin

    IEEE Journal of Biomedical and Health Informatics
    |June 24, 2016
    PubMed
    Summary
    This summary is machine-generated.

    New algorithms offer efficient lossless and near-lossless compression for multichannel biomedical signals. These methods improve data transmission for applications requiring low latency and power, outperforming current standards.

    Related Experiment Videos

    Last Updated: Mar 19, 2026

    Microfluidic Platform with Multiplexed Electronic Detection for Spatial Tracking of Particles
    11:54

    Microfluidic Platform with Multiplexed Electronic Detection for Spatial Tracking of Particles

    Published on: March 13, 2017

    9.9K

    Area of Science:

    • Biomedical Engineering
    • Signal Processing
    • Information Theory

    Background:

    • Multichannel biomedical signals (e.g., electroencephalogram, electrocardiogram) generate large datasets.
    • Efficient compression is crucial for real-time transmission, storage, and low-power applications.

    Purpose of the Study:

    • To develop novel lossless and near-lossless compression algorithms for multichannel biomedical signals.
    • To enhance the efficiency of signal transmission for low-latency and low-power applications.

    Main Methods:

    • Utilized information theory and signal processing tools, including universal coding and prediction.
    • Implemented fast online algorithms for multivariate recursive least squares.
    • Exploited spatial and temporal redundancies inherent in biomedical signals.

    Main Results:

    • Achieved superior compression ratios compared to state-of-the-art methods in both near-lossless and lossless compression.
    • Demonstrated effectiveness on publicly available electroencephalogram (EEG) and electrocardiogram (ECG) datasets.

    Conclusions:

    • The proposed algorithms provide a significant advancement in biomedical signal compression.
    • These methods are suitable for demanding applications like low-latency, low-power biomedical signal transmission.