Jere Joonatan Lavikainen
Doctoral Researcher
My research involves real-time analysis of human motion as well as wearable motion sensors and video-based methods for predicting of the loading of the knee joint. I utilize neural network-based regression models.
Department of Technical Physics, Faculty of Science, Forestry and Technology
jere.lavikainen@uef.fi
Research groups
Publications
6/6 items-
Estimation methods for musculoskeletal movement and loading using biomechanical models and portable modalities: bringing modern musculoskeletal analysis methods outside the motion laboratory
Lavikainen, Jere. 2024. Publications of the University of Eastern Finland. Dissertations in Science, Forestry and Technology -
Gait data from 51 healthy participants with motion capture, inertial measurement units, and computer vision
Lavikainen, Jere; Vartiainen, Paavo; Stenroth, Lauri; Karjalainen, Pasi A; Korhonen, Rami K; Liukkonen, Mimmi K; Mononen, Mika E. 2024. Data in brief. 56: -
Knee-Loading Predictions with Neural Networks Improve Finite Element Modeling Classifications of Knee Osteoarthritis: Data from the Osteoarthritis Initiative
Paz, Alexander; Lavikainen, Jere; Turunen, Mikael J; García, José J; Korhonen, Rami K; Mononen, Mika E. 2024. Annals of biomedical engineering. [Published: 06 June 2024]: 1-15 -
Predicting Knee Joint Contact Force Peaks During Gait Using a Video Camera or Wearable Sensors
Lavikainen, Jere; Stenroth, Lauri; Vartiainen, Paavo; Alkjaer, Tine; Karjalainen, Pasi A; Henriksen, Marius; Korhonen, Rami K; Liukkonen, Mimmi; Mononen, Mika E. 2024. Annals of biomedical engineering. [Epub ahead of print 03 August 2024]: 1-15 -
Open-source software library for real-time inertial measurement unit data-based inverse kinematics using OpenSim
Lavikainen, Jere; Vartiainen, Paavo; Stenroth, Lauri; Karjalainen, Pasi A.. 2023. PeerJ. 11: -
Prediction of Knee Joint Compartmental Loading Maxima Utilizing Simple Subject Characteristics and Neural Networks
Lavikainen, Jere; Stenroth, Lauri; Alkjær, Tine; Karjalainen, Pasi A; Korhonen, Rami K.; Mononen, Mika E. 2023. Annals of biomedical engineering. 51: 2479-2489