Moment arms are important in many contexts. Various methods have been used to estimate moment arms. It has been shown that a moment arm changes as a function of joint angle and contraction state. However, besides the influence of these anatomical factors, results from recent studies suggest that the estimation of moment arm is also dependent on the methods employed. The overall goal of this thesis was to explore the interaction between the methodological and anatomical influences on moment arm and their effect on estimates of muscle-tendon forces during biomechanical modelling. The first experiment was a direct comparison between two different moment arm methods that have been previously used for the estimation of Achilles tendon moment arm. The results of this experiment revealed a significant difference in Achilles tendon moment arm length dependent on the moment arm method employed. However, besides the differences found, results from both methods were well correlated. Based on these results, methodological differences between these two methods were compared across different joint angles and contraction states in study two. Results of experiment two revealed that Achilles tendon moment arms obtained using both methods change in a similar way as a function of joint angle and contraction state. In the third experiment, results from the first two experiments were used to determine how methodological and anatomical influences on Achilles tendon moment arm would change muscle-tendon forces during the task of submaximal cycling. Results of the third experiment showed the importance of taking the method, ankle angle and contraction state dependence of Achilles tendon moment arm into account when using biomechanical modelling techniques. Together, these findings emphasis the importance of carefully considering methodological and anatomical modifiers when estimating Achilles tendon moment arm.

Current bio-robotic assistive devices have developed into intelligent and dexterous machines. However, the sophistication of these wearable devices still remains limited by the inherent difficulty in controlling them by sensing user-intention. Even the most commonly used sensing method, which detects the electrical activity of skeletal muscles, offer limited information for multi-function control. An alternative bio-sensing strategy is needed to allow for the assistive device to bear more complex functionalities. In this thesis, a different sensing approach is introduced using Pulsed-Wave Doppler ultrasound in order to non-invasively detect small tendon displacements in the hand. The returning Doppler shifted signals from the moving tendon are obtained with a new processing technique. This processing technique involves a unique way to acquire raw data access from a commercial clinical ultrasound machine and to process the signal with Fourier analysis in order to determine the tendon displacements. The feasibility of the proposed sensing method and processing technique is tested with three experiments involving a moving string, a moving biological beef tendon and a moving human hand tendon. Although the proposed signal processing technique will be useful in many clinical applications involving displacement monitoring of biological tendons, its uses are demonstrated in this thesis for ultrasound-based user intention analysis for the ultimate goal of controlling assistive exoskeletal robotic hands.