Fitts' index of difficulty predicts the 1/f structure of movement amplitude time series.

Studies using a variety of experimental tasks have established that when humans repeatedly produce an action, fluctuations in action output are highest at the lowest frequencies and fluctuation magnitude (power) systematically declines as frequency increases. Such time series structure is termed pink noise. However, the appearance of pink noise seems to be limited to tasks where action is executed in the absence of task-related feedback. A few studies have demonstrated that when action was executed in the presence of task-related feedback, power was evenly distributed across all spectral frequencies--i.e., white noise was revealed. Here, participants produced cyclical aiming movements under visual feedback conditions and we sought to determine whether variations of both the movement amplitude requirement (A) and the target width (W)--in the form of the index of difficulty [ID = log2(2A/W)]--would predict the structure of movement amplitude (MA) time series. There were two ID levels, and there was a small- and large-scale version of each ID: The A and W values of the large-scale version were twice those used for the small-scale version. Given that increases in ID are known to induce increased reliance on the available visual feedback, we predicted an ID-induced shift in MA time series structure from pink to white noise. Indeed, that is what we found. Further, there were no changes in MA structure when scale level changed within each ID level. Such scale invariance of MA time series structure reinforces the notion that MA structure depends on the combined influence of A and W.

Visual feedback modulates the 1/f structure of movement amplitude time series.

In our prior studies, human participants were required to generate long sequences of targeted hand movement when task difficulty varied between conditions, and where full vision of the hand and target was always available. The movement amplitude-that is, the actual distance travelled-for each movement was measured; consecutive movement amplitude values were formed into time series; then, the time series were submitted to spectral analysis. As task difficulty increased, there was a pink-to-white-noise shift in movement amplitude time-series structure. Those changes could be attributed to a difficulty-induced increase in the need to engage visual feedback processes, which maintain accurate guidance of the hand to the target. The current study was designed to provide a more direct test of the hypothesis that difficulty-induced increases in visual feedback processing modulate movement amplitude time-series structure. To that end, we examined cyclical aiming performance under four unique conditions created from the crossing of two index of difficulty (2 and 5 bits) and two visual feedback (visual feedback and no-visual feedback) conditions. That allowed us to examine how variations in visual feedback quality might influence difficulty-induced changes in time-series structure. In the visual feedback condition, we predicted that the increase in difficulty should result in a pink-to-white-noise shift in time-series structure. If that expected shift resulted from increased engagement of visual feedback processing, then in the no-visual feedback condition-where visual feedback processing was disabled-we should observe a strengthened pink-noise time-series structure that does not change with the increase in difficulty. The current results confirmed those predictions. That provides further support for the hypothesis that engagement of closed-loop visual feedback processing modulates movement amplitude time-series structure.

Amplitude requirements, visual information, and the spatial structure of movement.

Studies using a variety of experimental tasks have established that when humans repeatedly produce an action, the amount of variability in system output is distributed across a range of time scales or frequencies. A finding of particular interest is that fluctuations in the output of cognitive systems are the highest at the lowest frequencies with fluctuation magnitude (power) systematically declining as frequency increases. Such time-series structure--captured by spectral analysis--is termed pink noise. However, the appearance of pink noise seems to be limited to tasks where action is executed in the absence of external, task-related feedback. In contrast, a few studies have demonstrated that when action was executed in the presence of external, task-related feedback, power was evenly distributed across all spectral frequencies--that is, a white-noise time-series structure was revealed. Here, we sought to determine if the time-series structure of movement amplitude values would change when movement amplitude requirements increased (6.35, 12.70, 25.40, 50.80, and 101.60 mm) under conditions of full visual feedback. Given that increases in movement amplitude requirements are known to induce increased reliance on the available visual feedback, we predicted an amplitude-requirement-induced shift in time-series structure from pink to white noise. Indeed, those results were revealed. Last, the main findings were captured by a computer simulation that was based on established principles of motor control.

Controlling an effector with eye movements: The effect of entangled sensory and motor responsibilities.

Restoring arm and hand function has been indicated by individuals with tetraplegia as one of the most important factors for regaining independence. The overall goal of our research is to develop assistive technologies that allow individuals with tetraplegia to control functional reaching movements. This study served as an initial step toward our overall goal by assessing the feasibility of using eye movements to control the motion of an effector in an experimental environment. We aimed to understand how additional motor requirements placed on the eyes affected eye-hand coordination during functional reaching. We were particularly interested in how eye fixation error was affected when the sensory and motor functions of the eyes were entangled due to the additional motor responsibility. We recorded participants' eye and hand movements while they reached for targets on a monitor. We presented a cursor at the participant's point of gaze position which can be thought of as being similar to the control of an assistive robot arm. To measure eye fixation error, we used an offline filter to extract eye fixations from the raw eye movement data. We compared the fixations to the locations of the targets presented on the monitor. The results show that not only are humans able to use eye movements to direct the cursor to a desired location (1.04 ± 0.15 cm), but they can do so with error similar to that of the hand (0.84 ± 0.05 cm). In other words, despite the additional motor responsibility placed on the eyes during direct eye-movement control of an effector, the ability to coordinate functional reaching movements was unaffected. The outcomes of this study support the efficacy of using the eyes as a direct command input for controlling movement.

Proof-of-Concept: A Hands-Free Interface for Robot-Assisted Self-Feeding.

Eating and drinking is an essential part of every-day life. And yet, there are many people in the world today who rely on others to feed them. In this work, we present a prototype robot-assisted self-feeding system for individuals with movement disorders. The system is capable of perceiving, localizing, grasping, and delivering non-compliant food items to an individual. We trained an object recognition network to detect specific food items, and we compute the grasp pose for each item. Human input is obtained through an interface consisting of an eye-tracker and a display screen. The human selects options on the monitor with their eye and head movements and triggers responses with mouth movements. We performed a pilot study with four able-bodied participants and one participant with a spinal cord injury (SCI) to evaluate the performance of our prototype system. Participants selected food items with their eye movements, which were then delivered by the robot. We observed an average overall feeding success rate of 89.1% and an average overall task time of $31.4 \pm 2.4$ seconds per food item. The SCI participant gave scores of 90.0 and 8.3 on the System Usability Scale and NASA Task Load Index, respectively. We also conducted a custom, post-study interview to gather participant feedback to drive future design decisions. The quantitative results and qualitative user feedback demonstrate the feasibility of robot-assisted self-feeding and justify continued research into mealtime-related assistive devices.

Trajectory evolution and changes in the structure of movement amplitude time series.

With increases in the index of difficulty [ID = log2(2A/W)], the time-series structure of movement amplitude values shift from pink to white noise. The appearance of pink noise at low-ID levels may be attributed to the dominance of feedforward control processes, while the appearance of white noise at high-ID levels may be attributed to increased reliance on visuomotor feedback processes needed to guide movement into the target region. Such within-movement corrections may disrupt the pink-noise time-series correlations that exist in the absence of feedback processing. In our prior work, movement amplitude was defined as the distance moved from movement start until its end. In contrast, in the current study we examined the time-series structure of movement amplitude values at each of 10 different percentages of time into the movement trajectory-ranging between 10 and 100% of the movement time (%MT)-at a low (2 bits) and a high (5 bits) ID level. We hypothesized that at both ID levels a pink-noise time-series structure would be seen during the early portions of the movement trajectory when feedforward control should dominate, but during later portions of the trajectory, increased whitening of time-series structure would emerge only under ID 5 as there would be an increased need to engage visuomotor feedback processes. Under ID 2, the same level of pink noise should be maintained across all %MT levels as movement should be under the same level of feedforward control throughout the trajectory. The only unpredicted result occurred at ID 2 where the pink-noise level increased with increases in %MT. We hypothesize that such strengthening of pink noise as a function of %MT reflects the engagement of early trajectory corrections superimposed on the initial feedforward signal, but, once such initial adjustments were made, feedforward processes increasingly took over as the trajectory neared its goal.

High loads induce differences between actual and imagined movement duration.

Actual and imagined action may be governed by common information and neural processes. This hypothesis has found strong support from a range of chronometric studies showing that it takes the same amount of time to actually move and to imagine moving. However, exceptions have been observed when actual and imagined movements were made under conditions of inertial loading: sometimes the equivalency of actual and imagined movement durations (MDs) has been preserved, and other times it has been disrupted. The purpose of the current study was to test the hypothesis that the appearance and magnitude of actual-imagined MD differences in those studies was dependent on the level of load relative to the maximum loading capacity of the involved effector system [the maximum voluntary load (MVL)]. The experiment required 12 young, healthy humans to actually produce, and to imagine producing, single degree of freedom index finger movements under a range of loads (0, 5, 10, 20, 40, and 80% MVL). As predicted, statistically significant actual-imagined MD differences were absent at lower loads (0-20% MVL), but differences appeared and increased in magnitude with further increases in %MVL (40 and 80% MVL). That pattern of results may relate to the common, everyday experience individuals have in interacting with loads. Participants are likely to have extensive experience interacting with very low loads, but not high loads. It follows that the control of low inertial loads should be governed by complete central representations of action, while representations should be less complete for high loads. A consequence may be increases in the uncertainty of predicting motor output with increases in load. Compensation for the increased uncertainty may appear as increases in the MD values selected during both the preparation and imagery of action--according to a speed-uncertainty trade-off. Then, during actual action, MD may be reduced if movement-related feedback indicates that a faster movement would succeed.

Fitts' Law in the Control of Isometric Grip Force With Naturalistic Targets.

Fitts' law models the relationship between amplitude, precision, and speed of rapid movements. It is widely used to quantify performance in pointing tasks, study human-computer interaction, and generally to understand perceptual-motor information processes, including research to model performance in isometric force production tasks. Applying Fitts' law to an isometric grip force task would allow for quantifying grasp performance in rehabilitative medicine and may aid research on prosthetic control and design. We examined whether Fitts' law would hold when participants attempted to accurately produce their intended force output while grasping a manipulandum when presented with images of various everyday objects (we termed this the implicit task). Although our main interest was the implicit task, to benchmark it and establish validity, we examined performance against a more standard visual feedback condition via a digital force-feedback meter on a video monitor (explicit task). Next, we progressed from visual force feedback with force meter targets to the same targets without visual force feedback (operating largely on feedforward control with tactile feedback). This provided an opportunity to see if Fitts' law would hold without vision, and allowed us to progress toward the more naturalistic implicit task (which does not include visual feedback). Finally, we changed the nature of the targets from requiring explicit force values presented as arrows on a force-feedback meter (explicit targets) to the more naturalistic and intuitive target forces implied by images of objects (implicit targets). With visual force feedback the relation between task difficulty and the time to produce the target grip force was predicted by Fitts' law (average r2 = 0.82). Without vision, average grip force scaled accurately although force variability was insensitive to the target presented. In contrast, images of everyday objects generated more reliable grip forces without the visualized force meter. In sum, population means were well-described by Fitts' law for explicit targets with vision (r2 = 0.96) and implicit targets (r2 = 0.89), but not as well-described for explicit targets without vision (r2 = 0.54). Implicit targets should provide a realistic see-object-squeeze-object test using Fitts' law to quantify the relative speed-accuracy relationship of any given grasper.

Degree of target utilization influences the location of movement endpoint distributions.

According to dominant theories of motor control, speed and accuracy are optimized when, on the average, movement endpoints are located at the target center and when the variability of the movement endpoint distributions is matched to the width of the target (viz., Meyer, Abrams, Kornblum, Wright, & Smith, 1988). The current study tested those predictions. According to the speed-accuracy trade-off, expanding the range of variability to the amount permitted by the limits of the target boundaries allows for maximization of movement speed while centering the distribution on the target center prevents movement errors that would have occurred had the distribution been off center. Here, participants (N=20) were required to generate 100 consecutive targeted hand movements under each of 15 unique conditions: There were three movement amplitude requirements (80, 160, 320mm) and within each there were five target widths (5, 10, 20, 40, 80mm). According to the results, it was only at the smaller target widths (5, 10mm) that movement endpoint distributions were centered on the target center and the range of movement endpoint variability matched the range specified by the target boundaries. As target width increased (20, 40, 80mm), participants increasingly undershot the target center and the range of movement endpoint variability increasingly underestimated the variability permitted by the target region. The degree of target center undershooting was strongly predicted by the difference between the size of the target and the amount of movement endpoint variability, i.e., the amount of unused space in the target. The results suggest that participants have precise knowledge of their variability relative to that permitted by the target, and they use that knowledge to systematically reduce the travel distance to targets. The reduction in travel distance across the larger target widths might have resulted in greater cost savings than those associated with increases in speed.

Task goals and change in dynamical degrees of freedom with motor learning.

In this article, the authors examined the hypothesis that the direction of the change (increase or decrease) in the dynamical degrees of freedom (dimension) regulated as a function of motor learning is task-dependent. Adult participants learned 1 of 2 isometric force-production tasks (Experiment 1: constant force output; Experiment 2: sinusoidal force output) over 5 days of practice and a 6th day with augmented information withdrawal. The results showed that over practice, the task goal induced either an increase (Experiment 1) or a decrease (Experiment 2) in the dimension of force output as performance error was reduced. These findings support the proposition that the observed increase or decrease in dimension with learning is dependent on both the intrinsic dynamics of the system and the short-term change required to realize the task goal.

Aiming for the future: prospective action difficulty, prescribed difficulty, and Fitts' law.

A main purpose of the current investigation was to determine if Fitts' index of difficulty [log(2)(2A/W)] could be taken as an index of subjective difficulty in prospective action. In two experiments, participants viewed 12 target displays with values of log(2)(2A/W) (prescribed difficulty) ranging between 1.0 and 6.5 bits. Following each 15 s trial, participants provided magnitude estimates reflecting the difficulty that someone else would experience if they actually had to make targeted movements during the trial. The prospective difficulty estimates were always made in the absence of movement. In Experiment 1, target displays were presented to participants on their own video monitor, while in Experiment 2, all participants concurrently viewed scaled-up target displays projected onto a large screen. There were three main findings: First, in both experiments, the prospective-prescribed relation was strong and positive. This finding warrants two conclusions: Fitts' index of difficulty can be taken as an index of subjective difficulty in prospective action, and subjective estimates of performance difficulty result from the monitoring of feedforward control signals generated in the absence of movement-related feedback. Second, even with the large differences in the target display scale of Experiments 1 and 2, difficulty estimates were equivalent at common prescribed difficulty levels. In other words, the results of Experiment 1 were successfully replicated in Experiment 2. This finding demonstrates the generality of the prospective-prescribed relation. Third, nonlinearities in the prospective-prescribed relation resembled those seen in functions describing the increases in movement time that accompany increases in prescribed difficulty (Fitts' law). This observation suggests that the prospective difficulty estimates were based on the value of a temporal parameter in an implicit mental simulation of the action.

Inter-digit individuation and force variability in the precision grip of young, elderly, and Parkinson's disease participants.

We examine the force fluctuations in the control of grip force to determine if force variability increases or decreases in relation to the degree of inter-digit individuation. This relation was examined in young (n = 7) and elderly (n = 7) participants, and in participants diagnosed with Parkinson's disease (n = 7). Force was produced under different force levels (5%, 25%, 50% MVC) with and without visual feedback. Force variability was assessed using the standard deviation and root mean square error, and inter-digit individuation was examined using cross-approximate entropy. Force variability increased with the force level, the removal of visual feedback, and also in the Parkinson's disease compared to the young and elderly matched control participants. There was a reduction in the degree of inter-digit individuation, with increases in force level, the removal of visual feedback, and in Parkinson's disease participants compared to the matched controls. Overall, there was a negative correlation between the degree of inter-digit individuation and force variability. The force fluctuations in precision grip revealed a continuum for the degree of inter-digit individuation in which task constraints, aging, and Parkinson's disease alter the coupling between the digits in controlling grip force.