Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Measuring Acceleration Due to Gravity01:12

Measuring Acceleration Due to Gravity

544
Consider a coffee mug hanging on a hook in a pantry. If the mug gets knocked, it oscillates back and forth like a pendulum until the oscillations die out.
A simple pendulum can be described as a point mass and a string. Meanwhile, a physical pendulum is any object whose oscillations are similar to a simple pendulum, but cannot be modeled as a point mass on a string because its mass is distributed over a larger area. The behavior of a physical pendulum can be modeled using the principles of...
544
Static and Kinetic Frictional Force01:05

Static and Kinetic Frictional Force

15.6K
One of the simpler characteristics of sliding friction is that it is parallel to the contact surfaces between systems, and is always in a direction that opposes the motion or attempted motion of the systems relative to each other. If two systems are in contact and moving relative to one another, then the friction between them is called kinetic friction. For example, kinetic friction slows a hockey puck sliding on ice.
However, if two systems are in contact and are stationary relative to one...
15.6K
Equation of Motion: General Plane motion - Problem Solving01:16

Equation of Motion: General Plane motion - Problem Solving

173
Consider a lawn roller with a mass of 100 kg, a radius of 0.2 meters, and a radius of gyration of 0.15 meters. A force of 200 N is applied to this roller, angled at 60 degrees from the horizontal plane. What will be the angular acceleration of the lawn roller?
The friction between the roller and the ground is characterized by two coefficients. The static friction coefficient is 0.15, while the kinetic friction coefficient is 0.1. These values are crucial in understanding the interaction between...
173
Non-inertial Frames of Reference01:27

Non-inertial Frames of Reference

5.8K
A reference frame accelerating or decelerating relative to an inertial frame is a non-inertial frame. To help understand this, consider what taking off in an airplane, turning a corner in a car, riding a merry-go-round, and the circular motion of a tropical cyclone all have in common. All these systems are accelerating, decelerating, or rotating relative to the Earth; hence, they all are non-inertial frames. All these systems exhibit inertial forces, which merely seem to arise from motion,...
5.8K

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

[Distribution of potential suitable habitats for <i>Haemaphysalis longicornis</i> in Nanjing City based on the maximum entropy model].

Zhongguo xue xi chong bing fang zhi za zhi = Chinese journal of schistosomiasis control·2026
Same author

Differentiation of benign and malignant complex cystic lesions of the breast: The diagnostic value of MRI.

Radiography (London, England : 1995)·2025
Same author

Selection of human embryo for IVF treatment using ensemble machine learning technique.

Morphologie : bulletin de l'Association des anatomistes·2025
Same author

Neoadjuvant Chemotherapy and Low Dose Immunotherapy in Resectable Non-small Cell Lung Cancer: A Multi-center Retrospective Cohort Analysis.

Clinical oncology (Royal College of Radiologists (Great Britain))·2025
Same author

Ascorbic acid is involved in melatonin-induced salinity tolerance of maize (<i>Zea mays</i> L.) by regulating antioxidant and photosynthetic capacities.

Photosynthetica·2025
Same author

Expression patterns of interleukin-6 and microRNA-146A during orthodontic relapse in a rat model.

Journal of physiology and pharmacology : an official journal of the Polish Physiological Society·2024
Same journal

Enhancing Volumetric Imaging in Linear-Array Photoacoustic Tomography: multiview fusion with deep learning.

IEEE transactions on bio-medical engineering·2026
Same journal

Robust Rule-based Heuristic Assistance Strategy for a Semi-Active Shoulder Exoskeleton Used in Overhead Work.

IEEE transactions on bio-medical engineering·2026
Same journal

Highly Accelerated 1-mm Isotropic 3D Chemical Exchange Saturation Transfer MRI Using Wave-Co-CAIPI at 5 Tesla.

IEEE transactions on bio-medical engineering·2026
Same journal

Systematic Evaluation of Hip Exoskeleton Assistance Parameters for Enhancing Gait Stability During Ground Slip Perturbations.

IEEE transactions on bio-medical engineering·2026
Same journal

SleepConFormer: A Single-Channel EEG Framework for Sleep Staging and Consciousness Assessment in Patients with Disorders of Consciousness.

IEEE transactions on bio-medical engineering·2026
Same journal

Modeling Partial and Total Support of Left Ventricular Assist Device for Discrete Hemodynamic Control Framework.

IEEE transactions on bio-medical engineering·2026
查看所有相关文章

相关实验视频

Updated: Jun 12, 2025

Oscillation and Reaction Board Techniques for Estimating Inertial Properties of a Below-knee Prosthesis
08:08

Oscillation and Reaction Board Techniques for Estimating Inertial Properties of a Below-knee Prosthesis

Published on: May 8, 2014

16.8K

从惯性传感器估计地面反应力

B Song, M Paolieri, H E Stewart

    IEEE transactions on bio-medical engineering
    |September 20, 2024
    PubMed
    概括
    此摘要是机器生成的。

    使用惯性测量单位 (IMU) 的轻量级机器学习模型可以准确地估计运行的地面反应力 (GRF) 和生物力学变量. 这些方法为损伤风险评估提供了复杂的深度学习模型的可行,高效的替代方案.

    更多相关视频

    An Inertial Measurement Unit Based Method to Estimate Hip and Knee Joint Kinematics in Team Sport Athletes on the Field
    06:52

    An Inertial Measurement Unit Based Method to Estimate Hip and Knee Joint Kinematics in Team Sport Athletes on the Field

    Published on: May 26, 2020

    7.9K
    Simulation of Human-induced Vibrations Based on the Characterized In-field Pedestrian Behavior
    10:52

    Simulation of Human-induced Vibrations Based on the Characterized In-field Pedestrian Behavior

    Published on: April 13, 2016

    8.8K

    相关实验视频

    Last Updated: Jun 12, 2025

    Oscillation and Reaction Board Techniques for Estimating Inertial Properties of a Below-knee Prosthesis
    08:08

    Oscillation and Reaction Board Techniques for Estimating Inertial Properties of a Below-knee Prosthesis

    Published on: May 8, 2014

    16.8K
    An Inertial Measurement Unit Based Method to Estimate Hip and Knee Joint Kinematics in Team Sport Athletes on the Field
    06:52

    An Inertial Measurement Unit Based Method to Estimate Hip and Knee Joint Kinematics in Team Sport Athletes on the Field

    Published on: May 26, 2020

    7.9K
    Simulation of Human-induced Vibrations Based on the Characterized In-field Pedestrian Behavior
    10:52

    Simulation of Human-induced Vibrations Based on the Characterized In-field Pedestrian Behavior

    Published on: April 13, 2016

    8.8K

    科学领域:

    • 生物力学 生物力学
    • 运动科学 运动科学 运动科学
    • 机器学习 机器学习

    背景情况:

    • 地面反应力 (GRF) 描述了跑步过程中的机械负荷,对于识别受伤风险至关重要.
    • 目前使用LSTM进行GRF估计的最先进的方法是计算密集的,缺乏透明度.
    • 惯性测量单元 (IMU) 为收集运行数据提供了一个便携式解决方案.

    研究的目的:

    • 评估轻量级机器学习方法,从IMU数据中估计GRF和生物力学变量.
    • 将新型轻量级方法的准确性和效率与传统的深度学习模型进行比较.
    • 评估个性化数据对估计准确性的影响.

    主要方法:

    • 拟议的SVD嵌入回归 (SER),一种新的轻量级方法.
    • 与LSTMs相比,SER和k-最近邻居 (KNN) 回归的比较.
    • 在各种实验场景中利用了来自骨架和腿部的IMU数据 (加速,角速度).

    主要成果:

    • 轻量级方法 (SER,KNN) 在GRF和生物力学变量估计方面表现出与LSTM可比或更高的准确性.
    • 个性化训练数据显著减少了估计误差,特别是在使用轻量级方法的生物力学变量.
    • 探索传感器位置和数据组合,以获得最佳性能.

    结论:

    • 轻量级机器学习模型是有效的估计运行生物力学从IMU数据.
    • SER和KNN为复杂的深度学习模型提供了高效和准确的替代方案.
    • 个性化数据提高了轻量级模型的性能,用于体育科学和伤害预防的实际应用.