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

Synthetic Biology02:55

Synthetic Biology

Synthetic biology is an interdisciplinary science that involves using principles from disciplines such as engineering, molecular biology, cell biology, and systems biology. It involves remodeling existing organisms from nature or constructing completely new synthetic organisms for applications such as protein or enzyme production, bioremediation, value-added macromolecule production, and the addition of desirable traits to crops, to name a few.
Golden rice
Golden rice is a genetically modified...
Assembly of Signaling Complexes01:30

Assembly of Signaling Complexes

Multiprotein signaling complexes are formed in a dynamic process involving protein-protein interactions at the cytoplasmic domain of transmembrane receptors or enzymatic and non-enzymatic proteins associated with the receptor. These complexes ensure the activation and propagation of intracellular signals that regulate cell functions.
Interaction domains in cell signaling
Interaction domains recognize exposed features of their binding partners containing post-translationally modified sequences,...
Neural Circuits01:25

Neural Circuits

Neural circuits and neuronal pools are two of the main structures found in the nervous system. Neural circuits are networks of neurons that work together to carry out a specific task or process. They consist of interconnected neurons and glial cells, which provide structural and metabolic support.
Neuronal pools are collections of nerve cells with similar functions and interact through chemical and electrical signals. These pools include both interneurons (the central neural circuit nodes that...
Semiconductors01:22

Semiconductors

There is variation in the electrical conductivity of materials - metals, semiconductors, and insulators that are showcased with the help of the energy band diagrams.
Metals such as copper (Cu), zinc (Zn), or lead (Pb) have low resistivity and feature conduction bands that are either not fully occupied or overlap with the valence band, making a bandgap non-existent. This allows electrons in the highest energy levels of the valence band to easily transition to the conduction band upon gaining...
Parallel Processing01:20

Parallel Processing

The brain processes sensory information rapidly due to parallel processing, which involves sending data across multiple neural pathways at the same time. This method allows the brain to manage various sensory qualities, such as shapes, colors, movements, and locations, all concurrently. For instance, when observing a forest landscape, the brain simultaneously processes the movement of leaves, the shapes of trees, the depth between them, and the various shades of green. This enables a quick and...
Synthetic Disvision of Polynomials01:28

Synthetic Disvision of Polynomials

Synthetic division is an efficient algorithmic approach for dividing a polynomial by a linear binomial of the form x - c, where c is a real number. This method is helpful due to its streamlined process, which avoids the more cumbersome steps involved in the traditional long division of polynomials. It simplifies computation and serves as a practical tool for evaluating polynomials and identifying their factors.To perform synthetic division, one begins by listing the coefficients of the...

You might also read

Related Articles

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

Sort by
Same author

Just a little prick: careful cell contacts enabled by ceramic nanostraws.

Pflugers Archiv : European journal of physiology·2026
Same author

Automated Batch Processing of Diurnal Cardiac Activity: Comparison of Fully Automated Batch- to Gold-Standard Manual Processing.

Journal of biological rhythms·2025
Same author

Prediction of impedance characteristic during electrical stimulation with microelectrode arrays.

Journal of neural engineering·2025
Same author

Accuracy Evaluation of 3D Pose Reconstruction Algorithms Through Stereo Camera Information Fusion for Physical Exercises with MediaPipe Pose.

Sensors (Basel, Switzerland)·2024
Same author

Sensing In Exergames for Efficacy and Motion Quality: Scoping Review of Recent Publications.

JMIR serious games·2024
Same author

Technical survey of end-to-end signal processing in BCIs using invasive MEAs.

Journal of neural engineering·2024

Related Experiment Video

Updated: Jun 17, 2026

Scalable Fluidic Injector Arrays for Viral Targeting of Intact 3-D Brain Circuits
13:36

Scalable Fluidic Injector Arrays for Viral Targeting of Intact 3-D Brain Circuits

Published on: January 21, 2010

14.3K

tinyHLS: a novel open source high level synthesis tool targeting hardware accelerators for artificial neural network

Ingo Hoyer1, Alexander Utz1, Christoph Hoog Antink2

  • 1Fraunhofer Institute for Microelectronic Circuits and Systems IMS, Duisburg, Germany.

Physiological Measurement
|January 10, 2025
PubMed
Summary

A new Python package, tinyHLS, enables real-time AI analysis on wearable devices by converting AI models into hardware accelerators. This significantly boosts processing speed and energy efficiency for applications like ECG monitoring.

Keywords:
AIHLSRISC-Vbiosignals

More Related Videos

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks
11:18

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks

Published on: March 2, 2015

10.2K
Construction of an Improved Multi-Tetrode Hyperdrive for Large-Scale Neural Recording in Behaving Rats
10:04

Construction of an Improved Multi-Tetrode Hyperdrive for Large-Scale Neural Recording in Behaving Rats

Published on: May 9, 2018

11.3K

Related Experiment Videos

Last Updated: Jun 17, 2026

Scalable Fluidic Injector Arrays for Viral Targeting of Intact 3-D Brain Circuits
13:36

Scalable Fluidic Injector Arrays for Viral Targeting of Intact 3-D Brain Circuits

Published on: January 21, 2010

14.3K
Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks
11:18

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks

Published on: March 2, 2015

10.2K
Construction of an Improved Multi-Tetrode Hyperdrive for Large-Scale Neural Recording in Behaving Rats
10:04

Construction of an Improved Multi-Tetrode Hyperdrive for Large-Scale Neural Recording in Behaving Rats

Published on: May 9, 2018

11.3K

Area of Science:

  • Artificial Intelligence
  • Hardware Acceleration
  • Wearable Technology

Background:

  • Wearable devices like smartwatches excel at biosignal monitoring (e.g., ECG) but lack power for real-time onboard analysis.
  • Limited power supply restricts the computational capabilities of edge devices for complex AI tasks.

Purpose of the Study:

  • Introduce tinyHLS, a novel Python package for converting AI models into hardware accelerators.
  • Enable efficient, real-time data analysis directly on resource-constrained wearable devices.
  • Facilitate the integration of AI into the development workflow for hardware accelerators.

Main Methods:

  • Developed tinyHLS, a Python package that translates AI models (TensorFlow Keras) into hardware description language code.
  • Utilized a template-based hardware compiler supporting various neural network layers and activation functions.
  • Focused on 1D data, particularly time-series data relevant for biosignal processing.

Main Results:

  • Generated hardware accelerators demonstrated a 62-fold increase in processing speed and a 4.5-fold improvement in energy efficiency.
  • Validated accelerators for detecting atrial fibrillation from ECG data.
  • Ensured code quality and synthesizability using commercial ASIC design tools.

Conclusions:

  • tinyHLS offers an open-source, versatile solution for developing hardware accelerators for AI on edge devices.
  • The package supports seamless integration into existing AI development workflows.
  • Potential applications include edge computing, cloud services, and enhancing wearable biosignal analysis.