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 author

Clinical Validation of Pupil Response During Walking in Parkinson's Disease.

Sensors (Basel, Switzerland)·2026
Same author

Medical Image Segmentation Methods: A Decision-Guided Survey Covering 2D/3D CNNs, Transformers, VLMs, SAM-Based Models and Diffusion Approaches.

Bioengineering (Basel, Switzerland)·2026
Same author

Retraining gait in Parkinson's Disease via a personalised app: A study protocol.

PloS one·2026
Same author

Extreme-Aware Time-Series Forecasting via Weak-Label-Guided Mixture of Experts.

Sensors (Basel, Switzerland)·2026
Same author

A prospective analysis of falls in Parkinson's disease: Does physical capacity moderate the relationship between walking amount and falls rates?

Journal of Parkinson's disease·2026
Same author

Co-designing the future: End-user involvement in digital interventions.

NPJ digital medicine·2026

Related Experiment Video

Updated: Aug 16, 2025

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

43.5K

Improving Inertial Sensor-Based Activity Recognition in Neurological Populations.

Yunus Celik1, M Fatih Aslan2, Kadir Sabanci2

  • 1Department of Computer and Information Sciences, Northumbria University, Newcastle upon Tyne NE1 8ST, UK.

Sensors (Basel, Switzerland)
|December 23, 2022
PubMed
Summary

This study introduces a new framework using image conversion and data augmentation for human activity recognition (HAR) in neurological populations. The method significantly improves HAR accuracy with limited datasets, aiding healthcare applications.

Failed At:

2026-06-19T13:39:53.515933+00:00

Keywords:
convolutional neural networksdata augmentationhuman activity recognitioninertial measurement units

More Related Videos

Home-Based Monitor for Gait and Activity Analysis
07:24

Home-Based Monitor for Gait and Activity Analysis

Published on: August 8, 2019

6.8K
Functional Near Infrared Spectroscopy of the Sensory and Motor Brain Regions with Simultaneous Kinematic and EMG Monitoring During Motor Tasks
11:31

Functional Near Infrared Spectroscopy of the Sensory and Motor Brain Regions with Simultaneous Kinematic and EMG Monitoring During Motor Tasks

Published on: December 5, 2014

15.2K

Related Experiment Videos

Last Updated: Aug 16, 2025

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

43.5K
Home-Based Monitor for Gait and Activity Analysis
07:24

Home-Based Monitor for Gait and Activity Analysis

Published on: August 8, 2019

6.8K
Functional Near Infrared Spectroscopy of the Sensory and Motor Brain Regions with Simultaneous Kinematic and EMG Monitoring During Motor Tasks
11:31

Functional Near Infrared Spectroscopy of the Sensory and Motor Brain Regions with Simultaneous Kinematic and EMG Monitoring During Motor Tasks

Published on: December 5, 2014

15.2K