Validation of a model-based inverse kinematics approach based on wearable inertial sensors.

Wearable inertial measurement units (IMUs) are a promising solution to human motion estimation. Using IMUs 3D orientations, a model-driven inverse kinematics methodology to estimate joint angles is presented. Estimated joint angles were validated against encoder-measured kinematics (robot) and against marker-based kinematics (passive mechanism).

Biofeedback for Gait Retraining Based on Real-Time Estimation of Tibiofemoral Joint Contact Forces.

Biofeedback assisted rehabilitation and intervention technologies have the potential to modify clinically relevant biomechanics. Gait retraining has been used to reduce the knee adduction moment, a surrogate of medial tibiofemoral joint loading often used in knee osteoarthritis research. In this paper, we present an electromyogram-driven neuromusculoskeletal model of the lower-limb to estimate, in real-time, the tibiofemoral joint loads.

Estimation of musculotendon parameters for scaled and subject specific musculoskeletal models using an optimization technique.

A challenging aspect of subject specific musculoskeletal modeling is the estimation of muscle parameters, especially optimal fiber length and tendon slack length. In this study, the method for scaling musculotendon parameters published by Winby et al. (2008), J.

CEINMS: A toolbox to investigate the influence of different neural control solutions on the prediction of muscle excitation and joint moments during dynamic motor tasks.

Personalized neuromusculoskeletal (NMS) models can represent the neurological, physiological, and anatomical characteristics of an individual and can be used to estimate the forces generated inside the human body. Currently, publicly available software to calculate muscle forces are restricted to static and dynamic optimisation methods, or limited to isometric tasks only. We have created and made freely available for the research community the Calibrated EMG-Informed NMS Modelling Toolbox (CEINMS), an OpenSim plug-in that enables investigators to predict different neural control solutions for the same musculoskeletal geometry and measured movements.

Comparison of markerless and marker-based motion capture technologies through simultaneous data collection during gait: proof of concept.

During the last decade markerless motion capture techniques have gained an increasing interest in the biomechanics community. In the clinical field, however, the application of markerless techniques is still debated. This is mainly due to a limited number of papers dedicated to the comparison with the state of the art of marker based motion capture, in term of repeatability of the three dimensional joints' kinematics.

Motion analysis of front crawl swimming applying CAST technique by means of automatic tracking.

Kinematic analysis of swimming is of interest to improve swimming performances. Although the video recordings of underwater swimmers are commonly used, the available methodologies are rarely precise enough to adequately estimate the three dimensional (3D) joint kinematics. This is mainly due to difficulties in obtaining the required kinematic parameters (anatomical landmarks, joint centres and reference frames) in the swimming environment.