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

Anatomical Positions01:11

Anatomical Positions

In anatomy, several standard anatomical positions are used as references for describing the position and orientation of different body parts. These positions help provide a common frame of reference when discussing anatomical structures. The anatomical position is the standard reference point for describing the body's position and orientation. In this position:
The body is upright, facing forward, and standing erect.
The feet are parallel and flat on the floor.
The arms are hanging by the...
Muscles that Move the Head01:19

Muscles that Move the Head

The muscles that move the head are a dynamic and complex group of structures that work together to facilitate a wide range of head movements, including rotation, flexion, extension, and lateral bending.
The bilateral sternocleidomastoid, or SCM, and the suprahyoid and infrahyoid muscles are significant head flexors. The SCM muscles originate at the sternum and clavicle and attach to the mastoid process of the temporal bone. The SCM contracts bilaterally to bend the head forward, whereas...

You might also read

Related Articles

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

Sort by
Same author

Sleep Apnea and Paroxysmal Atrial Fibrillation: Diurnal Patterning of Autonomic Dysfunction and Influence of CPAP Therapy.

Journal of arrhythmia·2026
Same author

Regularity in occurrence of respiratory-related events in sleep predicts cardiovascular disease and mortality.

medRxiv : the preprint server for health sciences·2026
Same author

A Push-Pull Network Mechanism Revealed by Describing Function Analysis for Alzheimer's Pathological Oscillations.

IEEE transactions on neural networks and learning systems·2026
Same author

Spectral analysis of ECG and SpO₂ for machine learning classification of Sleep-Disordered breathing.

Sleep & breathing = Schlaf & Atmung·2026
Same author

Exercise-Induced Modulation of Subthalamic Activity and Intra-Nuclear Connectivity.

The European journal of neuroscience·2026
Same author

Actigraphy-based sleep disruption and diurnal biomarkers of autonomic function in paroxysmal atrial fibrillation.

Sleep & breathing = Schlaf & Atmung·2025

Related Experiment Video

Updated: Jun 6, 2026

Resting-State Connectivity and Neuroimaging of Prefrontal Cortex Activity During a Block-Design Yoga Asana Practice Using fNIRS
07:56

Resting-State Connectivity and Neuroimaging of Prefrontal Cortex Activity During a Block-Design Yoga Asana Practice Using fNIRS

Published on: June 24, 2025

A headband for classifying human postures.

Mohammed Aloqlah1, Rosa R Lahiji, Kenneth A Loparo

  • 1Department of Electrical Engineering and Computer Science, Case Western Reserve University, Cleveland, OH 44106, USA.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
|November 25, 2010
PubMed
Summary

This study introduces a real-time human posture classification system using accelerometer data. The method accurately identifies sitting, standing, and lying positions, along with transitions between them.

More Related Videos

Assessment of Static Graviceptive Perception in the Roll-Plane using the Subjective Visual Vertical Paradigm
06:30

Assessment of Static Graviceptive Perception in the Roll-Plane using the Subjective Visual Vertical Paradigm

Published on: April 28, 2020

Computerized Dynamic Posturography for Postural Control Assessment in Patients with Intermittent Claudication
14:52

Computerized Dynamic Posturography for Postural Control Assessment in Patients with Intermittent Claudication

Published on: December 11, 2013

Related Experiment Videos

Last Updated: Jun 6, 2026

Resting-State Connectivity and Neuroimaging of Prefrontal Cortex Activity During a Block-Design Yoga Asana Practice Using fNIRS
07:56

Resting-State Connectivity and Neuroimaging of Prefrontal Cortex Activity During a Block-Design Yoga Asana Practice Using fNIRS

Published on: June 24, 2025

Assessment of Static Graviceptive Perception in the Roll-Plane using the Subjective Visual Vertical Paradigm
06:30

Assessment of Static Graviceptive Perception in the Roll-Plane using the Subjective Visual Vertical Paradigm

Published on: April 28, 2020

Computerized Dynamic Posturography for Postural Control Assessment in Patients with Intermittent Claudication
14:52

Computerized Dynamic Posturography for Postural Control Assessment in Patients with Intermittent Claudication

Published on: December 11, 2013

Area of Science:

  • Biomedical Engineering
  • Signal Processing
  • Human-Computer Interaction

Background:

  • Accurate human posture detection is crucial for health monitoring and assistive technologies.
  • Existing methods often require multiple sensors or complex setups.
  • A real-time, single-sensor approach is needed for practical applications.

Purpose of the Study:

  • To develop a real-time method for classifying static human postures (sitting, standing, lying) and dynamic transitions.
  • To utilize a single three-axis accelerometer for posture recognition.
  • To integrate discrete wavelet transform (DWT) and fuzzy logic inference system (FIS) for enhanced classification.

Main Methods:

  • A single three-axis accelerometer in a wearable headband collected data.
  • Data was wirelessly transmitted and analyzed in real-time on a laptop.
  • Discrete Wavelet Transform (DWT) decomposed signals to extract dynamic features.
  • A Fuzzy Logic Inference System (FIS) used DWT features and transition data for classification.

Main Results:

  • The developed algorithm successfully classifies basic human static postures in real-time.
  • Dynamic transitions between postures were accurately identified.
  • The combination of DWT and FIS proved effective for posture classification using accelerometer data.

Conclusions:

  • A novel, real-time human posture classification system using only accelerometer data has been developed.
  • The DWT-FIS approach offers a robust and efficient method for wearable-based activity recognition.
  • This technology has potential applications in healthcare, sports science, and human-computer interaction.