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

Discharge Summary Forms01:31

Discharge Summary Forms

1.2K
The discharge summary is crucial as it enables a smooth transition from a healthcare facility to a patient's home or another care setting. This critical document facilitates seamless continuity of care, ensuring patients receive the necessary support and attention.
Here's a detailed look at the key components and guidelines for preparing a discharge summary:
1.2K
Structural Joints: Synovial Joints01:16

Structural Joints: Synovial Joints

6.5K
Synovial joints are the most common type of joint in the body. A key structural characteristic for a synovial joint is the presence of a joint cavity. This fluid-filled space is where the articulating surfaces of the bones contact each other. Also, unlike fibrous or cartilaginous joints, the articulating bone surfaces at a synovial joint are not directly connected to each other with fibrous connective tissue or cartilage. This gives the bones of a synovial joint the ability to move smoothly...
6.5K
Structural Joints: Fibrous Joints01:03

Structural Joints: Fibrous Joints

3.6K
Fibrous joints are a type of joint where the bones are connected by fibrous connective tissue. These joints provide stability and minimal to no movement between the articulating bones. There are three types of fibrous joints.
Suture
All the bones of the skull, except for the mandible, are joined to each other by a fibrous joint called a suture. The fibrous connective tissue found at a suture strongly unites the adjacent skull bones and thus helps to protect the brain and form the face. In...
3.6K
Structural Joints: Cartilaginous Joints01:17

Structural Joints: Cartilaginous Joints

3.9K
As the name indicates, at a cartilaginous joint, the adjacent bones are united by cartilage, a tough but flexible type of connective tissue. Unlike synovial joints, these types of joints lack a joint cavity and involve bones joined together by either hyaline cartilage or fibrocartilage.
There are two types of cartilaginous joints:
Synchondrosis
A synchondrosis ("joined by cartilage") is a cartilaginous joint where bones are connected by hyaline cartilage. Synchondrosis may be temporary...
3.9K
Joints01:26

Joints

35.5K
Joints, also called articulations or articular surfaces, are points at which ligaments or other tissues connect adjacent bones. Joints permit movement and stability, and can be classified based on their structure or function.
Structural joint classifications are based on the material that makes up the joint as well as whether or not the joint contains a space between the bones. Joints are structurally classified as fibrous, cartilaginous, or synovial.
Fibrous Joints Are Immovable
The bones of a...
35.5K
RC Circuits: Discharging A Capacitor01:27

RC Circuits: Discharging A Capacitor

4.4K
One of the applications of an RC circuit is the relaxation oscillator. The relaxation oscillator comprises a voltage source, a capacitor, a resistor, and a neon lamp. The lamp acts like an open circuit (infinite resistance) until the potential difference across the neon lamp reaches a specific voltage. At that voltage, the lamp acts like a short circuit (zero resistance), and the capacitor discharges through the neon lamp and produces light. Once the capacitor is fully discharged through the...
4.4K

You might also read

Related Articles

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

Sort by
Same author

Multisignal Collaborative Detection of Thiram Based on Dual-Functional Iron-Based Metal Organic Frameworks.

Journal of agricultural and food chemistry·2026
Same author

Lanzhou Lily (<i>Lilium davidii var. unicolor</i>) Extract Alleviates Chronic Stress-Induced Mood Disturbances by Suppressing Neuroinflammation and Modulating the Gut-Brain Axis in Mice.

Food science & nutrition·2026
Same author

Machine Learning-Assisted Surface Ligand Engineering Strategy for Enhanced Sensitivity of Immunoassay Platform.

Analytical chemistry·2026
Same author

Dynamic task-related prefrontal functional networks evolved in Stroop Color-Word tasks measured by fNIRS.

Cognitive neurodynamics·2026
Same author

Controlling thermoreversibility and hole conductivity in thermoresponsive ionic biogels using phase morphology for neurohaptics.

Science advances·2026
Same author

Role of nutritional indices (PNI, CONUT, GNRI) in predicting delirium in hospitalised individuals: A systematic review and meta-analysis.

General hospital psychiatry·2026

Related Experiment Video

Updated: Jan 22, 2026

Tactile Semiautomatic Passive-Finger Angle Stimulator TSPAS
04:40

Tactile Semiautomatic Passive-Finger Angle Stimulator TSPAS

Published on: July 30, 2020

3.3K

Finger Joint Angle Estimation Based on Motoneuron Discharge Activities.

Chenyun Dai, Xiaogang Hu

    IEEE Journal of Biomedical and Health Informatics
    |July 9, 2019
    PubMed
    Summary
    This summary is machine-generated.

    This study demonstrates a novel method for estimating finger joint angles using neural drive derived from motor unit firing. This approach offers a more reliable way to predict finger kinematics for human-machine interfaces.

    More Related Videos

    Preliminary Study on Acupuncture Combined with Grain-sized Moxibustion for Treating Rheumatoid Arthritis with Finger Joint Pain
    04:50

    Preliminary Study on Acupuncture Combined with Grain-sized Moxibustion for Treating Rheumatoid Arthritis with Finger Joint Pain

    Published on: May 16, 2025

    853
    In Vivo Intracellular Recording of Type-Identified Rat Spinal Motoneurons During Trans-Spinal Direct Current Stimulation
    11:07

    In Vivo Intracellular Recording of Type-Identified Rat Spinal Motoneurons During Trans-Spinal Direct Current Stimulation

    Published on: May 11, 2020

    5.7K

    Related Experiment Videos

    Last Updated: Jan 22, 2026

    Tactile Semiautomatic Passive-Finger Angle Stimulator TSPAS
    04:40

    Tactile Semiautomatic Passive-Finger Angle Stimulator TSPAS

    Published on: July 30, 2020

    3.3K
    Preliminary Study on Acupuncture Combined with Grain-sized Moxibustion for Treating Rheumatoid Arthritis with Finger Joint Pain
    04:50

    Preliminary Study on Acupuncture Combined with Grain-sized Moxibustion for Treating Rheumatoid Arthritis with Finger Joint Pain

    Published on: May 16, 2025

    853
    In Vivo Intracellular Recording of Type-Identified Rat Spinal Motoneurons During Trans-Spinal Direct Current Stimulation
    11:07

    In Vivo Intracellular Recording of Type-Identified Rat Spinal Motoneurons During Trans-Spinal Direct Current Stimulation

    Published on: May 11, 2020

    5.7K

    Area of Science:

    • Biomedical Engineering
    • Neuroscience
    • Human-Machine Interaction

    Background:

    • Accurate estimation of joint kinematics is crucial for intuitive human-machine interactions.
    • Continuous and reliable estimation of small joint angles, like those in fingers, remains a significant challenge.
    • Existing methods often struggle with precision, especially during dynamic movements.

    Purpose of the Study:

    • To develop and validate a method for continuous estimation of finger joint angles.
    • To utilize populational motoneuron firing activities as a basis for kinematic prediction.
    • To compare the efficacy of a neural-drive-based approach against traditional electromyography (EMG) methods.

    Main Methods:

    • Acquired multi-channel surface electromyogram (sEMG) signals from extensor digitorum communis muscles during individual finger extension movements.
    • Classified individual finger movements using sEMG signals with high accuracy (>96%).
    • Extracted and pooled individual motor unit discharge timings to derive populational neural drive, then used polynomial regression to predict finger joint angles.

    Main Results:

    • Individual finger movements were classified with over 96% accuracy from sEMG.
    • Finger extension angles were continuously predicted with R² values exceeding 0.8 using the derived neural drive.
    • The neural-drive-based prediction method outperformed the conventional EMG-amplitude-based approach, particularly during rapid movements.

    Conclusions:

    • Populational motoneuron firing activity provides a robust signal for estimating finger joint kinematics.
    • The developed neural-drive-based interface shows significant promise for reliable and intuitive human-machine interactions.
    • This approach offers superior performance compared to traditional EMG amplitude methods for predicting finger movements.