Previous ankle exoskeleton assistance techniques that were able to demonstrate metabolic reductions can be categorized into those that delivered moment profiles similar to the biological ankle moment throughout the stance phase, and others that deliv...
Traditional laboratory experiments, rehabilitation clinics, and wearable sensors offer biomechanists a wealth of data on healthy and pathological movement. To harness the power of these data and make research more efficient, modern machine learning t...
The aim of this study was to use Recurrent Neural Network (RNN) to predict the orientation and amplitude of the applied force during the push phase of manual wheelchair propulsion. Trunk and the right-upper limb kinematics data were assessed with an ...
Wearable technology has been viewed as one of the plausible alternatives to capture human motion in an unconstrained environment, especially during running. However, existing methods require kinematic and kinetic measurements of human body segments a...
The purpose of this study was to develop and train a Neural Network (NN) that uses barbell mass and motions to predict hip, knee, and ankle Net Joint Moments (NJM) during a weightlifting exercise. Seven weightlifters performed two cleans at 85% of th...
The measurement of wrist passive ranges of motion (ROMs) can provide insight into improvements and allow for effective monitoring during a rehabilitation program. Compared with conventional methods, this study proposed a new robotic assessment techni...
The aim of this study was to investigate if a machine learning algorithm utilizing triaxial accelerometer, gyroscope, and magnetometer data from an inertial motion unit (IMU) could detect surface- and age-related differences in walking. Seventeen old...
Description of the patterns of ground reaction force is a standard method in areas such as medicine, biomechanics and robotics. The fundamental parameter is the time course of the force, which is classified visually in particular in the field of clin...
This study examines the ability of commonly used supervised learning techniques to classify the execution of a maximum effort change of direction task into predefined movement pattern as well as the influence of fuzzy executions and the impact of sel...
We present a novel biorobotic framework comprised of a biological muscle-tendon unit (MTU) mechanically coupled to a feedback controlled robotic environment simulation that mimics in vivo inertial/gravitational loading and mechanical assistance from ...