The main objective of this study was to determine differences, if any, in three-dimensional (3D) kinematic characteristics of the three principal punches (the jab, hook and uppercut) executed by novice, intermediate and elite level amateur boxers. Specifically, the kinematic variables related to the displacement, linear velocity and acceleration of the upper body segments, translational hand acceleration and vertical ground reaction force generated by boxers were analyzed. The subjects of this study composed of 10 novice, 9 intermediate, and 11 elite level amateur boxers. Ages of the subjects ranged from 18 to 34 years old. All subjects executed their punches toward a head-high target on a standard practice bag. The motions were captured with PhaseSpace real time optical tracking system with 8 high speed cameras at 240 fps. Then, the motions captured were analyzed to quantify the kinematic factors associated with each punch. The results showed that the uppercut punch generated larger linear shoulder, elbow and wrist velocity compared to the jab punch. Similarly, the uppercut punch generated larger linear shoulder, elbow and wrist acceleration compared to the hook and jab punches. Moreover, the uppercut and hook punches generated larger translational hand acceleration compared to the jab punch. As a conclusion, the results for all kinematic variables demonstrated that the type of punch executed was the major determinant of the magnitude of each factor studied. Moreover, the technique employed can significantly affect the resulting displacement, linear velocity and acceleration, and translational hand acceleration of the fist.

In this dissertation, I examine binocular 3D motion processing through a series of psychophysical and neuroimaging experiments aimed at uncovering the neural computations involved and their interaction with the known hierarchy of visual motion processing. Two primary binocular cues could be used to compute 3D motion: one based on changing disparities over time (CD), the other based on interocular velocity differences (IOVD). Under normal viewing conditions, both cues coexist and (potentially) provide the same 3D direction information, yet whether CD, IOVD, or both mechanisms exist has distinct implications for how 3D motion is processed along the visual stream. First, I measured 3D direction discrimination sensitivity is measured for isolated binocular cues under a range of 3D motion speeds and visual eccentricities. Comparison of isolated-cue sensitivity to corresponding combined cue sensitivity (i.e. concurrent IOVD & CD cue stimuli) provided an estimate of relative cue contributions under normal viewing conditions. Second, I conducted a series of motion adaptation experiments to differentiate the neural representation of 2D and 3D directions of motion, and examine the degree to which IOVD or CD mechanisms can account for 3D motion adaptation. Third, I examined the neural locus of 3D motion processing by measuring 3D direction- selectivity throughout a range of visual cortical areas using functional neuroimaging in an event-related paradigm that parallels psychophysical adaptation experiments. Finally, I discuss the broader implications for the neural mechanisms of binocular 3D motion processing and future experimental directions. Together, these results reveal that: (1) the IOVD cue is the dominant cue to 3D motion processing across the majority of natural speeds & eccentricities, (2) neural tuning for 3D motion is distinct from 2D motion and can be fully explained by an IOVD mechanism, and (3) the IOVD cue is computed relatively late in the visual processing stream, in areas MT & MST— cortical areas primarily associated with 2D/retinal motion and thought to be beyond the point of binocular combination. The significance of IOVD —but not CD—cues to 3D motion perception motivates a drastic modification to canonical models of motion processing to include the late-stage comparison of eye- specific motion signals. / text

This study examined the acute effects of whole-body corrective exercise on postural alignment in a sample of 50 male participants (18-30 y) displaying asymmetrical postural deviations. All participants were randomly assigned to either a non-exercise control (n = 25) or corrective exercise treatment (n = 25) group. A three-dimensional motion analysis Vicon system was employed to quantify standing postural alignment at the beginning and end of a 6 d study. Postural misalignments were determined in degrees of symmetry (tilt) and rotation using horizontal and vertical virtual plumb lines for the following locations: hip (ASIS), leg (greater trochanter), shoulder (acromion process), and head (ear). The treatment group completed five corrective exercise sessions on separate days which included 11 exercises (requiring about 60 min per session to complete). The control group performed no intervention and maintained a normal lifestyle. At the commencement of the study there were no significant differences in the degree of postural misalignment between the control and treatment groups at any of the postural measurements. At the conclusion of the treatment period (following the five sessions of corrective exercise), there were no significant differences in any of the postural alignments of any of the postural measurements between the treatment and control groups. For example, all of the following postural measurements were not significantly different (critical F ≥ 4.24;df = 1,25) between groups: hip (ASIS) tilt (F = 0.05), hip (ASIS) rotation (F = 0.15), greater trochanter tilt (F = 1.58), greater trochanter rotation (F = 0.33), shoulder tilt (F = 2.63), shoulder rotation (F = 0.07), head tilt (F = 2.39), and head rotation (F = 2.79). The results of this study suggest that five sessions of corrective exercise were insufficient to significantly improve standing postural alignment. In addition, this study appears to be the first to document whole-body postural alignment using 3D video analysis.

Starting a few decades ago, the unmanned wheeled vehicle research has drawn lately more attention, especially for off-road environment. As the demand to use electric vehicles increased, the need to conceptualize the use of electrically driven vehicles in autonomous operations became a target. That is because in addition to the fact that they are more environmentally friendly, they are also easier to control. This also gives another reason to enhance further the energy economy of those unmanned electric vehicles. Off-road vehicles research was always challenging, but in the present work the nature of the off-road land is utilized to benefit from in order to enhance the energy consumption of those vehicles. An algorithm for energy consumption optimization for electrically driven unmanned wheeled vehicles is presented. The algorithm idea is based on the fact that in off-road conditions, when the vehicle passes a ditch or a hole, the kinetic energy gained while moving downhill could be utilized to reduce the energy consumption for moving uphill if the dimensions of the ditch/hole were known a distance ahead. Two manipulated variables are evaluated: the wheels DC motors supply voltage and the DC armature current. The developed algorithm is analysed and compared to the PID speed iii controller and to the open-loop control of DC motors. The developed predictive controller achieved encouraging results compared to the PID speed control and also compared to the open-loop control. Also, the use of the DC armature current as a manipulated variable showed more noticeable improvement over using the DC input voltage. Experimental work was carried out to validate the predictive control algorithm. A mobile robot with two DC motor driven wheels was deployed to overcome a ditch-like hindrance. The experimental results verified the simulation results. A parametric study for the predictive control is conducted. The effect of changing the downhill angle and the uphill angle as well as the size of the prediction horizon on the consumed electric energy by the DC motors is addressed. The simulation results showed that, when using the proposed approach, the larger the prediction horizon, the lower the energy consumption is.

The Niagara Foot (NF) is a relatively new prosthetic design, primarily intended for use in developing countries. It combines low cost and durability with high performance energy return features. The design has been successfully tested mechanically and in field trials, but to date there has been little quantitative gait data describing the performance of the foot. Biomechanical gait analysis techniques will be used to extract quantitative gait measures. The current study is designed to characterize the effect of heel section stiffness parameter differences between a NF normal heel and a NF with a reduced material heel section., on gait characteristics in persons with unilateral trans-tibial amputations (TTA). Standardized biomechanical gait analysis techniques, adapted for this population, were used to extract quantitative gait measures. Five persons with TTA performed walking tasks while 3D ground reaction forces were recorded via an embedded force platform. A motion capture system also recorded the 3D segmental motion of the lower limbs and torso of each subject. These were combined to calculate net joint moments and mechanical power at the hip and knee of both limbs. These data were compared between a normal NF and a NF with a modified heel. Each participant had a period of two-week adaptation prior to any testing. An EMG system and a prosthesis evaluation questionnaire were used to help analyze the condition. The overall hypothesis of this study was that modification of the heel section stiffness would change several aspects of gait. Although the gait pattern differences between participants and the low participant number produced no significant differences between the conditions for all variables, trends were observed in multiple outcomes. These results report preliminary evidence that for some participants the heel material reduction does impact their gait by showing a different loading phase during the transition between the heel strike and the full contact with the ground. The NF2 may move the gait toward a more flexed knee position. Furthermore, despite a reduction in the material of the heel section results showed that the overall foot stiffness increased. This may be the result of the one-piece design and mechanics of the NF. Further investigations with a bigger cohort of people with TTA are required to look at the importance of the impact of the prosthetic foot heel stiffness.

The Niagara Foot (NF) is a relatively new prosthetic design, primarily intended for use in developing countries. It combines low cost and durability with high performance energy return features. The design has been successfully tested mechanically and in field trials, but to date there has been little quantitative gait data describing the performance of the foot. Biomechanical gait analysis techniques will be used to extract quantitative gait measures. The current study is designed to characterize the effect of heel section stiffness parameter differences between a NF normal heel and a NF with a reduced material heel section., on gait characteristics in persons with unilateral trans-tibial amputations (TTA). Standardized biomechanical gait analysis techniques, adapted for this population, were used to extract quantitative gait measures. Five persons with TTA performed walking tasks while 3D ground reaction forces were recorded via an embedded force platform. A motion capture system also recorded the 3D segmental motion of the lower limbs and torso of each subject. These were combined to calculate net joint moments and mechanical power at the hip and knee of both limbs. These data were compared between a normal NF and a NF with a modified heel. Each participant had a period of two-week adaptation prior to any testing. An EMG system and a prosthesis evaluation questionnaire were used to help analyze the condition. The overall hypothesis of this study was that modification of the heel section stiffness would change several aspects of gait. Although the gait pattern differences between participants and the low participant number produced no significant differences between the conditions for all variables, trends were observed in multiple outcomes. These results report preliminary evidence that for some participants the heel material reduction does impact their gait by showing a different loading phase during the transition between the heel strike and the full contact with the ground. The NF2 may move the gait toward a more flexed knee position. Furthermore, despite a reduction in the material of the heel section results showed that the overall foot stiffness increased. This may be the result of the one-piece design and mechanics of the NF. Further investigations with a bigger cohort of people with TTA are required to look at the importance of the impact of the prosthetic foot heel stiffness.

Starting a few decades ago, the unmanned wheeled vehicle research has drawn lately more attention, especially for off-road environment. As the demand to use electric vehicles increased, the need to conceptualize the use of electrically driven vehicles in autonomous operations became a target. That is because in addition to the fact that they are more environmentally friendly, they are also easier to control. This also gives another reason to enhance further the energy economy of those unmanned electric vehicles. Off-road vehicles research was always challenging, but in the present work the nature of the off-road land is utilized to benefit from in order to enhance the energy consumption of those vehicles. An algorithm for energy consumption optimization for electrically driven unmanned wheeled vehicles is presented. The algorithm idea is based on the fact that in off-road conditions, when the vehicle passes a ditch or a hole, the kinetic energy gained while moving downhill could be utilized to reduce the energy consumption for moving uphill if the dimensions of the ditch/hole were known a distance ahead. Two manipulated variables are evaluated: the wheels DC motors supply voltage and the DC armature current. The developed algorithm is analysed and compared to the PID speed iii controller and to the open-loop control of DC motors. The developed predictive controller achieved encouraging results compared to the PID speed control and also compared to the open-loop control. Also, the use of the DC armature current as a manipulated variable showed more noticeable improvement over using the DC input voltage. Experimental work was carried out to validate the predictive control algorithm. A mobile robot with two DC motor driven wheels was deployed to overcome a ditch-like hindrance. The experimental results verified the simulation results. A parametric study for the predictive control is conducted. The effect of changing the downhill angle and the uphill angle as well as the size of the prediction horizon on the consumed electric energy by the DC motors is addressed. The simulation results showed that, when using the proposed approach, the larger the prediction horizon, the lower the energy consumption is.

Starting a few decades ago, the unmanned wheeled vehicle research has drawn lately more attention, especially for off-road environment. As the demand to use electric vehicles increased, the need to conceptualize the use of electrically driven vehicles in autonomous operations became a target. That is because in addition to the fact that they are more environmentally friendly, they are also easier to control. This also gives another reason to enhance further the energy economy of those unmanned electric vehicles. Off-road vehicles research was always challenging, but in the present work the nature of the off-road land is utilized to benefit from in order to enhance the energy consumption of those vehicles. An algorithm for energy consumption optimization for electrically driven unmanned wheeled vehicles is presented. The algorithm idea is based on the fact that in off-road conditions, when the vehicle passes a ditch or a hole, the kinetic energy gained while moving downhill could be utilized to reduce the energy consumption for moving uphill if the dimensions of the ditch/hole were known a distance ahead. Two manipulated variables are evaluated: the wheels DC motors supply voltage and the DC armature current. The developed algorithm is analysed and compared to the PID speed iii controller and to the open-loop control of DC motors. The developed predictive controller achieved encouraging results compared to the PID speed control and also compared to the open-loop control. Also, the use of the DC armature current as a manipulated variable showed more noticeable improvement over using the DC input voltage. Experimental work was carried out to validate the predictive control algorithm. A mobile robot with two DC motor driven wheels was deployed to overcome a ditch-like hindrance. The experimental results verified the simulation results. A parametric study for the predictive control is conducted. The effect of changing the downhill angle and the uphill angle as well as the size of the prediction horizon on the consumed electric energy by the DC motors is addressed. The simulation results showed that, when using the proposed approach, the larger the prediction horizon, the lower the energy consumption is.

Yes / Motion-in-depth can be detected by using two different types of binocular cues: change of disparity (CD) and inter-ocular velocity differences (IOVD). To investigate the underlying detection mechanisms, stimuli can be constructed that isolate these cues or contain both (FULL cue). Two different methods to isolate the IOVD cue can be employed: anti-correlated (aIOVD) and de-correlated (dIOVD) motion signals. While both types of stimuli have been used in studies investigating the perception of motion-in-depth, for the first time, we explore whether both stimuli isolate the same mechanism and how they differ in their relative efficacy. Here, we set out to directly compare aIOVD and dIOVD sensitivity by measuring motion coherence thresholds. In accordance with previous results by Czuba et al. (2010), we found that motion coherence thresholds were similar for aIOVD and FULL cue stimuli for most participants. Thresholds for dIOVD stimuli, however, differed consistently from thresholds for the two other cues, suggesting that aIOVD and dIOVD stimuli could be driving different visual mechanisms.

Yes / Motion in depth (MID) can be cued by high-resolution changes in binocular disparity over time (CD), and low-resolution interocular velocity differences (IOVD). Computational differences between these two mechanisms suggest that they may be implemented in visual pathways with different spatial and temporal resolutions. Here, we used fMRI to examine how achromatic and S-cone signals contribute to human MID perception. Both CD and IOVD stimuli evoked responses in a widespread network that included early visual areas, parts of the dorsal and ventral streams, and motion-selective area hMT+. Crucially, however, we measured an interaction between MID type and chromaticity. fMRI CD responses were largely driven by achromatic stimuli, but IOVD responses were better driven by isoluminant S-cone inputs. In our psychophysical experiments, when S-cone and achromatic stimuli were matched for perceived contrast, participants were equally sensitive to the MID in achromatic and S-cone IOVD stimuli. In comparison, they were relatively insensitive to S-cone CD. These findings provide evidence that MID mechanisms asymmetrically draw on information in precortical pathways. An early opponent motion signal optimally conveyed by the S-cone pathway may provide a substantial contribution to the IOVD mechanism. / Supported by the Biotechnology and Biological Sciences Research Council Grants BB/M002543/1 (to A.R.W.), BB/M001660/1 (to J.M.H.), and BB/M001210/1 (to M.B.). / Research Development Fund Publication Prize Award winner, May 2019.