This thesis sought to: 1) examine the effect of a number of organism and task constraints on the control of two forms of physiological tremor, namely postural and finger-pinch force tremor; and 2) determine if the expected constraint-related changes in tremor output were associated with alterations in the control strategy utilised by the performer. The organism constraints were age and resistance-training (for both forms of tremor), while the task constraints were visual feedback, target size and limb preference (postural tremor) and mean force, target shape and limb preference (force tremor). The postural (index finger) tremor amplitude of young adults was significantly greater in the augmented vision (AV) than normal vision (NV) conditions and when using the non-preferred than preferred limb. Even greater differences/changes in postural tremor amplitude were observed as a function of aging and training. Older adults had significantly more index finger tremor amplitude than young adults. Regardless, the older adults who completed a six weeks program of unilateral strength- or coordination-training were able to significantly reduce their tremor amplitude. Although the training-related reductions in tremor amplitude were of a greater magnitude for the trained than untrained limb, a significant reduction in the tremor amplitude of the untrained limb was also observed for the coordination-training group. All of these significant differences/changes in tremor amplitude were associated with significant changes in a number of other dependent variables. For example, the task- and age-related increases in tremor amplitude were primarily a result of greater 8-12 Hz tremor power and were associated with increased EMG activity/co-activation of the extensor digitorum (ED) and flexor digitorum superficialis (FDS) muscles and a significant reduction in intra-limb (index finger-hand and forearm-upper arm) coupling. The significant reductions in tremor amplitude observed for the resistance-trained older adults was a result of a significant decline in 8-12 Hz power and were associated with a significant reduction in ED and FDS co-activation. However, no significant change in intra-limb coupling was observed. The overall trends observed in the results for the finger-pinch force tremor experiments were similar to those for postural tremor. Older adults had significantly more finger-pinch force tremor (i.e. force variability and targeting error) than young adults, although older adults who performed six weeks of unilateral strength-training were able to significantly reduce the force variability and targeting error of the trained limb. No significant training-related reduction in force tremor was however observed for the untrained limb. The significant age-related increase in force tremor was a result of greater low frequency (less than 2 Hz) power and was associated with a significant loss of inter-digit force sharing and coupling as well as tactile sensitivity. Interestingly, the training-related decreases in force tremor were not associated with significant changes in any of the frequency, sharing or coupling measures. Collectively, the results of the five experiments contained in this thesis add much to our understanding of postural and force tremor. Results indicated that numerous task and organism constraints can have a substantial effect on the resulting tremor output. Furthermore, the task- and age-related differences in the power spectral, muscle activity and coupling measures suggested that the changes in tremor output were the result of the use of an altered (sub-optimal) control strategy. The age-related increase in postural and force tremor amplitude may therefore reflect not only an overall decline in neuromuscular system function, but also the relative inability of older adults to effectively coordinate the output of numerous degrees of freedom (limb segments). The effect of the aging process on tremor output was somewhat reversible, with the older adults who performed resistance-training significantly improving their control of both postural and force tremor. There was some evidence that resistance-training could produce cross-education effects in older adults, although these were only statistically significant for postural tremor amplitude in the coordination-training group and for wrist flexion strength in the strength-training group. The relative brevity of the training program (6 weeks) and the observable cross-education effects suggest that the reduction in tremor amplitude and increases in strength were primarily a result of neural adaptations. Such findings further support the prescription of resistance-training for improving physical function in older individuals.

Parkinson's disease (PD) is a neuro-degenerative chronic disorder with cardinal signs of bradykinesia, resting tremor, rigidity, and postural abnormality/instability. Tremor, which is a manifestation of both normal and abnormal activities in the nervous system, can be described as an involuntary and periodic oscillation of any limb. Such an oscillation with a small amplitude, which is barely visible to the naked eye, is present in healthy people. This is called a physiological tremor and is asymptomatic. This tremor is believed to be the result of at least two distinct oscillations. A passive mechanical oscillation that is produced by the irregularities of motor unit firing, and by blood ejection during cardiac systole. The frequency and amplitude of these oscillations are dependent on the mechanical properties of the limb including joint stiffness and limb inertia. There is another component of oscillation that does not respond to elastic or inertial loading, which is called the central component, and is believed to arise from an unknown oscillating neuronal network within the central nervous system. Unlike physiological tremor, pathological tremors are symptomatic and can impair motor performance. Parkinson's disease (PD) tremor is generally manifested at rest, but also occurs during posture or motion. Classical PD rest tremor is known to be a central tremor of 4-6 Hz and peripheral origins have only a minimal role. However, whether or not the same central mechanism remains active during action tremor (including posture and movement) should yet be answered. Contrary to PD rest tremor, reported results on action tremor in the literature are diverse; and the reason for the changes in tremor characteristics in situations other than rest, or generally during muscle activation, is not fully understood. The lack of generality in the results of studies on action tremor, makes the efforts of treatment difficult, and is a barrier for mechanical/engineering approaches of suppressing this tremor. To investigate the role of mechanisms other than classic rest tremor, and possible sub-categories of tremulous PD in yielding diverse results, this study was conducted on twenty PD patients and fourteen healthy age-matched (on average) controls. To evaluate the possible contribution of (enhanced) physiological tremor, the study considered the effect of loading on postural hand tremor in a complete range of 0-100% MVC (Maximum Voluntary Contraction). The study looked at two measures of tremor amplitude and one measure of tremor frequency, and focused on two frequency bands of classic-rest (3.5-6.5 Hz) and physiological (7.5-16.5 Hz) tremors. The study revealed that PD tremor was not uniformly distributed in the three dimensional space, and then focused on the investigation of tremor in the dominant axis, which was the same as direction of loading. It also revealed that dopaminergic medication could significantly affect tremor components only in PD band, compared to the components in the physiological band. The study was an extension to previous studies and yielded similar results for the previously reported range of loading. However, with the extended range of loading, it revealed novel results particularly after separating PD patients into sub-groups. It was hypothesized that the coexistence of physiological mechanism, and considerable difference between sub-types of tremulous PD patients, are responsible for most of the diversity in the previously reported studies. This study showed that for clearer results the sub-groups are inevitable, and that automatic classification (clustering) provided the most separable sub-groups. These sub-groups had distinct trends of load effect on tremor amplitude and frequency. No matter which categorization method was used, at least one sub-group exhibited significantly higher tremor energy compared to the healthy participants not only in the PD band, but also in the physiological band. This meant that, for some sub-groups of PD, the physiological tremor is a very important mechanism and not the same as that of healthy people. The coexistence hypothesis was also affirmed by examining tremor spectrums' peak frequency and magnitude in the two separate bands. The necessity of the separation of tremulous PD patients into sub-groups, and the coexistence of physiological and classic PD tremor mechanisms for some of them are the factor that should be considered in the design of a suppressing device and also in the proposed treatment of action tremor in this population.

Parkinson's disease (PD) is a neuro-degenerative chronic disorder with cardinal signs of bradykinesia, resting tremor, rigidity, and postural abnormality/instability. Tremor, which is a manifestation of both normal and abnormal activities in the nervous system, can be described as an involuntary and periodic oscillation of any limb. Such an oscillation with a small amplitude, which is barely visible to the naked eye, is present in healthy people. This is called a physiological tremor and is asymptomatic. This tremor is believed to be the result of at least two distinct oscillations. A passive mechanical oscillation that is produced by the irregularities of motor unit firing, and by blood ejection during cardiac systole. The frequency and amplitude of these oscillations are dependent on the mechanical properties of the limb including joint stiffness and limb inertia. There is another component of oscillation that does not respond to elastic or inertial loading, which is called the central component, and is believed to arise from an unknown oscillating neuronal network within the central nervous system. Unlike physiological tremor, pathological tremors are symptomatic and can impair motor performance. Parkinson's disease (PD) tremor is generally manifested at rest, but also occurs during posture or motion. Classical PD rest tremor is known to be a central tremor of 4-6 Hz and peripheral origins have only a minimal role. However, whether or not the same central mechanism remains active during action tremor (including posture and movement) should yet be answered. Contrary to PD rest tremor, reported results on action tremor in the literature are diverse; and the reason for the changes in tremor characteristics in situations other than rest, or generally during muscle activation, is not fully understood. The lack of generality in the results of studies on action tremor, makes the efforts of treatment difficult, and is a barrier for mechanical/engineering approaches of suppressing this tremor. To investigate the role of mechanisms other than classic rest tremor, and possible sub-categories of tremulous PD in yielding diverse results, this study was conducted on twenty PD patients and fourteen healthy age-matched (on average) controls. To evaluate the possible contribution of (enhanced) physiological tremor, the study considered the effect of loading on postural hand tremor in a complete range of 0-100% MVC (Maximum Voluntary Contraction). The study looked at two measures of tremor amplitude and one measure of tremor frequency, and focused on two frequency bands of classic-rest (3.5-6.5 Hz) and physiological (7.5-16.5 Hz) tremors. The study revealed that PD tremor was not uniformly distributed in the three dimensional space, and then focused on the investigation of tremor in the dominant axis, which was the same as direction of loading. It also revealed that dopaminergic medication could significantly affect tremor components only in PD band, compared to the components in the physiological band. The study was an extension to previous studies and yielded similar results for the previously reported range of loading. However, with the extended range of loading, it revealed novel results particularly after separating PD patients into sub-groups. It was hypothesized that the coexistence of physiological mechanism, and considerable difference between sub-types of tremulous PD patients, are responsible for most of the diversity in the previously reported studies. This study showed that for clearer results the sub-groups are inevitable, and that automatic classification (clustering) provided the most separable sub-groups. These sub-groups had distinct trends of load effect on tremor amplitude and frequency. No matter which categorization method was used, at least one sub-group exhibited significantly higher tremor energy compared to the healthy participants not only in the PD band, but also in the physiological band. This meant that, for some sub-groups of PD, the physiological tremor is a very important mechanism and not the same as that of healthy people. The coexistence hypothesis was also affirmed by examining tremor spectrums' peak frequency and magnitude in the two separate bands. The necessity of the separation of tremulous PD patients into sub-groups, and the coexistence of physiological and classic PD tremor mechanisms for some of them are the factor that should be considered in the design of a suppressing device and also in the proposed treatment of action tremor in this population.

Speed-accuracy tradeoffs, velocity profiles, and physiological tremor are fundamental characteristics of human movement. The principles underlying these phenomena have long attracted major interest and controversy. Each is well established experimentally but as yet they have no common theoretical basis. It is proposed that these three phenomena occur as the direct consequence of a movement response planning system that acts as an intermittent optimal controller operating at discrete intervals of ~100 ms. The BUMP model of response planning describes such a system. It forms the kernel of adaptive model theory which defines, in computational terms, a basic unit of motor production or BUMP. Each BUMP consists of three processes: (i) analysing sensory information, (ii) planning a desired optimal response, and (iii) executing that response. These processes operate in parallel across successive sequential BUMPs. The response planning process requires a discrete time interval in which to generate a minimum acceleration trajectory of variable duration, or horizon, to connect the actual response with the predicted future state of the target and compensate for executional error. BUMP model simulation studies show that intermittent adaptive optimal control employing two extremes of variable horizon predictive control reproduces almost exactly findings from several authoritative human experiments. On the one extreme, simulating spatially-constrained movements, a receding horizon strategy results in a logarithmic speed-accuracy tradeoff and accompanying asymmetrical velocity profiles. On the other extreme, simulating temporally-constrained movements, a fixed horizon strategy results in a linear speed-accuracy tradeoff and accompanying symmetrical velocity profiles. Furthermore, simulating ramp movements, a receding horizon strategy closely reproduces experimental observations of 10 Hz physiological tremor. A 100 ms planning interval yields waveforms and power spectra equivalent to those of joint-angle, angular velocity and electromyogram signals recorded for several speeds, directions, and skill levels of finger movement. While other models of response planning account for one or other set of experimentally observed features of speed-accuracy tradeoffs, velocity profiles, and physiological tremor, none accounts for all three. The BUMP model succeeds in explaining these disparate movement phenomena within a single framework, strengthening this approach as the foundation for a unified theory of motor control and planning.

Speed-accuracy tradeoffs, velocity profiles, and physiological tremor are fundamental characteristics of human movement. The principles underlying these phenomena have long attracted major interest and controversy. Each is well established experimentally but as yet they have no common theoretical basis. It is proposed that these three phenomena occur as the direct consequence of a movement response planning system that acts as an intermittent optimal controller operating at discrete intervals of ~100 ms. The BUMP model of response planning describes such a system. It forms the kernel of adaptive model theory which defines, in computational terms, a basic unit of motor production or BUMP. Each BUMP consists of three processes: (i) analysing sensory information, (ii) planning a desired optimal response, and (iii) executing that response. These processes operate in parallel across successive sequential BUMPs. The response planning process requires a discrete time interval in which to generate a minimum acceleration trajectory of variable duration, or horizon, to connect the actual response with the predicted future state of the target and compensate for executional error. BUMP model simulation studies show that intermittent adaptive optimal control employing two extremes of variable horizon predictive control reproduces almost exactly findings from several authoritative human experiments. On the one extreme, simulating spatially-constrained movements, a receding horizon strategy results in a logarithmic speed-accuracy tradeoff and accompanying asymmetrical velocity profiles. On the other extreme, simulating temporally-constrained movements, a fixed horizon strategy results in a linear speed-accuracy tradeoff and accompanying symmetrical velocity profiles. Furthermore, simulating ramp movements, a receding horizon strategy closely reproduces experimental observations of 10 Hz physiological tremor. A 100 ms planning interval yields waveforms and power spectra equivalent to those of joint-angle, angular velocity and electromyogram signals recorded for several speeds, directions, and skill levels of finger movement. While other models of response planning account for one or other set of experimentally observed features of speed-accuracy tradeoffs, velocity profiles, and physiological tremor, none accounts for all three. The BUMP model succeeds in explaining these disparate movement phenomena within a single framework, strengthening this approach as the foundation for a unified theory of motor control and planning.