Results 121 to 130 of about 2,295 (204)

Markerless Motion Analysis Using New Digital Technology. [PDF]

Phys Ther Res
Ota M.
europepmc   +1 more source

Commercial vision sensors and AI-based pose estimation frameworks for markerless motion analysis in sports and exercises: a mini review. [PDF]

Front Physiol
Edriss S, Romagnoli C, Caprioli L, Bonaiuto V, Padua E, Annino G.   +5 more
europepmc   +1 more source

Quantitative Evaluation and Optimization of Museum Fatigue Using Computer Vision Human Pose Estimation. [PDF]

Sensors (Basel)
Cheng Z, Zhang Y, Zhang L.
europepmc   +1 more source

Fitness exercise evaluation system based on improved DTW algorithm. [PDF]

Sci Rep
Guo T, Yin Q, Liu X, Sun Y, Qin Z, Han Y, Lu G.   +6 more
europepmc   +1 more source

The Application of Deep Learning Human Pose Estimation in Sport: A Systematic Review. [PDF]

Sports Med Open
Aulton C, Wakili L, Strafford BW, Davids K, Chiu CY.   +4 more
europepmc   +1 more source

Generating synthetic images of human skeletal motion for pose and kinematics estimation tasks. [PDF]

Sci Data
Lavikainen J, Pagnon D, Liukkonen MK, Korhonen RK, Turunen MJ, Stenroth L, Mononen ME.   +6 more
europepmc   +1 more source

Diffusion models enable zero-shot pose estimation for lower-limb prosthetic users. [PDF]

PLOS Digit Health
Zhou T, Iskandar MNS, Chiam KH.
europepmc   +1 more source

T²W-CogLoadNet: a framework for cognitive load assessment of dance movements based on deep learning-powered human pose estimation. [PDF]

Front Psychol
Zhao F.
europepmc   +1 more source

A PILOT STUDY TO EVALUATE SAGITTAL KINEMATIC VARIABLES IN ACCELERATED RUN USING OPENPOSE MARKERLESS MOTION CAPTURE SYSTEM

This study evaluated the agreement between OpenPose markerless and marker-based methods in analyzing sprint start performance. Four male students performed ten sprint starts. The Bland-Altman test for average center of mass (COM) horizontal velocity from
Kitamura, Mizuki, Otsuka, Mitsuo
core  

A machine learning study highlighting the challenges of fidgety movement recognition using vision and inertial sensors. [PDF]

Sci Rep
Lentzsch F, Li F, Pagel F, Lau M, Kock A, Röhling HM, Stein A, Baranowski M, Maass M, Hölzl H, Glende S, Mansow-Model S, Thyen U, Grzegorzek M.   +13 more
europepmc   +1 more source