Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 3 of 3
Full-Text Articles in Biomechanics
Novel Approach For Non-Invasive Prediction Of Body Shape And Habitus, Emma Young
Novel Approach For Non-Invasive Prediction Of Body Shape And Habitus, Emma Young
Electronic Theses and Dissertations
While marker-based motion capture remains the gold standard in measuring human movement, accuracy is influenced by soft-tissue artifacts, particularly for subjects with high body mass index (BMI) where markers are not placed close to the underlying bone. Obesity influences joint loads and motion patterns, and BMI may not be sufficient to capture the distribution of a subject’s weight or to differentiate differences between subjects. Subjects in need of a joint replacement are more likely to have mobility issues or pain, which prevents exercise. Obesity also increases the likelihood of needing a total joint replacement. Accurate movement data for subjects with …
Development Of A Novel Haptic Feedback System For Gait Training Applications, Mohsen Alizadeh Noghani
Development Of A Novel Haptic Feedback System For Gait Training Applications, Mohsen Alizadeh Noghani
Electronic Theses and Dissertations
Until recently, study and correction of motor or gait functions required costly sensors and measurement setups (e.g., optical motion capture systems) which were only available in laboratories or clinical environments. However, due to (1) the growing availability and affordability of inertial measurement units (IMUs) with high accuracy, and (2) progress in wireless, high bandwidth, and energy-efficient networking technologies such as Bluetooth Low Energy (BLE), it is now possible to measure and provide feedback in real-time for biomechanical parameters outside of those specialized settings. To enable gait training without an expert who can provide verbal feedback, augmented feedback, which is divided …
Longitudinal Tracking Of Physiological State With Electromyographic Signals., Robert Warren Stallard
Longitudinal Tracking Of Physiological State With Electromyographic Signals., Robert Warren Stallard
Electronic Theses and Dissertations
Electrophysiological measurements have been used in recent history to classify instantaneous physiological configurations, e.g., hand gestures. This work investigates the feasibility of working with changes in physiological configurations over time (i.e., longitudinally) using a variety of algorithms from the machine learning domain. We demonstrate a high degree of classification accuracy for a binary classification problem derived from electromyography measurements before and after a 35-day bedrest. The problem difficulty is increased with a more dynamic experiment testing for changes in astronaut sensorimotor performance by taking electromyography and force plate measurements before, during, and after a jump from a small platform. A …