Simon M. Hsiang

Gait characteristics of children with hemiplegic cerebral palsy before and after modified constraint-induced movement therapy

This investigation assessed selected gait parameters of children with hemiparesis before and after participation in a modified constraint-induced movement therapy program (mCIMT). Recent advances in the understanding of the relationship between mCIMT and cortical reorganization supports the use of upper-extremity mCIMT to treat lower extremity deficits. However, the effects of mCIMT on the gait patterns of children with hemiparesis remain unclear. Twelve preschool children participated in a mCIMT program for 5 consecutive days, 6 h each day. Pre- and post-intervention data, on the temporal-spatial aspects of gait, were collected with the GAITRite walkway. Data were analyzed using a repeated measures generalized linear model. Base of support decreased significantly (p < 0.001) following treatment and improvements were noted in most other gait descriptors. The results of this study suggest that mCIMT can increase stability and improve the overall gait pattern. This study provides a new dimension in the effects of pediatric mCIMT programs and could begin to shift the focus of this intervention to remediation of lower extremity deficits. Additional studies with a longitudinal follow-up focus to determine the long-term effects of mCIMT on walking balance and stability would be beneficial.

Characterisation of mental models in a virtual reality-based multitasking scenario using measures of situation awareness

The objective of this study was to assess an empirical approach to the characterisation of mental models in a multitasking scenario. A virtual reality task was used, in which participants were required to attend to and detect multiple types of perceptual events occurring randomly in time while carrying on steady physical activity (walking on a treadmill). Based on a cognitive task analysis, different forms of mental models for performing the task were hypothesised. Responses to situation awareness (SA) probes delivered during experiment trials, mental workload ratings and task performance measures were collected and compared with response patterns expected for specific mental model types. Results demonstrated utility of categorical SA responses for identifying different mental model types. However, in the multitasking scenario, the process of developing ‘good’ SA was significantly influenced by the physical and cognitive task demands and the progressive development of accurate isomorphic mental models of event distributions appeared to be restricted by this. Possible applications of the results of this study include the development of training programmes for mobile, visual inspection tasks, such as airport roving security patrols, towards accurate mental model development and promoting detection of critical events.

The effects of a suspended-load backpack on gait

A suspended-load backpack is a device that is designed to capture the mechanical energy created as a suspended backpack load oscillates vertically on the back during gait. The objective of the current study was to evaluate the effect of a suspended-load backpack system on selected temporal and kinetics parameters describing gait. Nine male participants carried a suspended-load backpack as they walked on an instrumented treadmill with varied levels of load (no backpack, 22.5 kg, and 29.3 kg) and walking speed (1.16 m/s, 1.43 m/s, 1.70 m/s). As the participants performed this treadmill task, ground reaction forces were collected from an instrumented treadmill system. From these data, temporal variables (cycle time, single support time, and double support time) and kinetic variables (normalized weight acceptance force, normalized push-off force, and normalized mid-stance force) were derived. The results showed that the response of the temporal variables were consistent with previous studies of conventional (i.e. stable load) backpacks. The response of the normalized push-off force, however, showed that increasing walking speed significantly (p<0.05) decreased the magnitude of this force, a result contrary to the literature concerning conventional backpacks where this force has been shown to significantly increase. Further evaluation revealed that this reduction in force was the result of a phase shift between the movement of the carried load and the movement of the torso. This suggests that the motion of the load in a suspended-load backpack influences the gait biomechanics and should be considered as this technology advances.

Prediction accuracy in estimating joint angle trajectories using a video posture coding method for sagittal lifting tasks

This study investigated prediction accuracy of a video posture coding method for lifting joint trajectory estimation. From three filming angles, the coder selected four key snapshots, identified joint angles and then a prediction program estimated the joint trajectories over the course of a lift. Results revealed a limited range of differences of joint angles (elbow, shoulder, hip, knee, ankle) between the manual coding method and the electromagnetic motion tracking system approach. Lifting range significantly affected estimate accuracy for all joints and camcorder filming angle had a significant effect on all joints but the hip. Joint trajectory predictions were more accurate for knuckle-to-shoulder lifts than for floor-to-shoulder or floor-to-knuckle lifts with average root mean square errors (RMSE) of 8.65°, 11.15° and 11.93°, respectively. Accuracy was also greater for the filming angles orthogonal to the participants sagittal plane (RMSE = 9.97°) as compared to filming angles of 45° (RMSE = 11.01°) or 135° (10.71°). The effects of lifting speed and loading conditions were minimal. To further increase prediction accuracy, improved prediction algorithms and/or better posture matching methods should be investigated. Statement of Relevance: Observation and classification of postures are common steps in risk assessment of manual materials handling tasks. The ability to accurately predict lifting patterns through video coding can provide ergonomists with greater resolution in characterising or assessing the lifting tasks than evaluation based solely on sampling with a single lifting posture event.

Cost of temperature history data uncertainties in short term electric load forecasting

Short-term load forecasting has received a lot of attention from both researchers and practitioners. Many techniques, such as neural networks, fuzzy logic, and time series models, are developed to improve the modeling and forecasting process with varying success. Some research has also been devoted to improving the weather forecast or relieving the impact of uncertainties in the weather forecast. Nowadays, the quality of load and weather data history becomes a bottleneck of enhancing the forecast accuracy. With the emerging Smart Grid initiatives, the utilities have the opportunities to upgrade their infrastructure, which includes the advanced metering systems. These upgrades will potentially lead to a high quality load history in the near future. On the other hand, quality of weather history has been a concern of the small and medium sized utilities. This paper presents a recent study for a medium sized utility in eastern US. Multiple linear regression, which is currently deployed in this utility, is used to generate the base forecast in this paper. A Monte Carlo based methodology is proposed to quantify the cost of the data uncertainties in the temperature history. Finally, a cost-benefit analysis is performed to help the utilities decide how many weather stations should be installed.

An Optimal-Control Model of Vision–Gait Interaction in a Virtual Walkway

The specific aim of this paper is to model the vision-posture coupling behavior, which is important for astronauts to stabilize their locomotion in partial gravities as the national aeronautics and space administration plans for manned missions to the moon and mars . As such, an optimal scheme is assumed in postural-control processes to stabilize visual optical flows. An experiment was conducted, in which human subjects attended a visual-gait tracking task. In tracking control, head position errors can be used to regulate inputs so that appropriate compensatory changes can be obtained. The ldquooptimalrdquo scheme describes a compromise between postural adjusting efforts and tracking errors. The results show that the proposed optimal-control model describes the gait tracking process more reliably than McRuers crossover model of the human-plant compensatory behaviors. In practice, if the tracking goal is to be roughly right rather than precisely wrong, this paper also provides the experimental data regarding the human tolerance and achievable performance under various unloading conditions and tracking difficulties. This information and related experimental setup could also be applied to postsurgery gait rehabilitation.

The Development of Fault Diagnosis Methodologies using Hierarchical Clustering and Small World Network Stratification

Many conventional fault diagnosis techniques do not effectively and efficiently use the available information and cannot achieve a satisfactory diagnosis in high dimensional real-world problems. In this paper, the fault diagnosis method using hierarchical clustering (HC) and small world (SW) networks stratification has been proposed to utilize the available information and trace up/downward based on event hierarchy and up/downstream along the physical network. As such, one can determine if certain diagnosis is applicable globally or more depends on the nature of events or locations; consequently the diagnostic uncertainty can be reduced. Duke energy distribution outage data are used to generate examples for the purpose of illustrating the motivation, necessity, implementation planning, and potential benefits of HC-SW stratification for power distribution system outage cause identification

Dementia-Specific Gait Profile: A Computational Approach Using Signal Detection Theory and Introduction of an Index to Assess Response to Cognitive Perturbations

Elderly diagnosed with dementia are three times more likely to fall and over three times more likely to have severe injury compared to cognitively unimpaired elderly. Consequently, there is a need to identify biomarkers that can facilitate early detection, diagnosis, and progression of dementia. One of the characteristics of dementia is the inability to allocate attentional resources to concurrent tasks. Consequently, recent studies have used walking gait in conjunction with another cognitive or motor task to identify biomarkers related to the disease. However, in every study all temporal-spatial gait descriptors are being evaluated and, typically, the nonspecific velocity, double limb support, and stride variability are reported as significant. The purpose, therefore, of this investigation was to use a computational approach to first establish a dementia-specific gait profile irrespective of walking condition (talking, without talking) using the minimum number of temporal-spatial gait descriptors, second to investigate the effect of condition, and third to investigate the effect of an everyday realistic cognitive perturbation, resulting in potential falls, by constructing an index of responsiveness. Six normal elderly and seven diagnosed with dementia walked on an instrumented walkway: (i) without talking, (ii) conversing with an investigator, and (iii) conversing with an investigator, but including as part of the conversation a cognitive perturbation in the form of an unexpected direct question. To accomplish the first two goals we implemented signal detection theory combined with receiver operator characteristic curves. Based on these results we constructed the index of responsiveness that we compared between the two cohorts. Only six of thirteen gait variables were needed to distinguish individuals with dementia from normally aging, irrespective of whether gait was used as a stand-alone task, i.e., without talking, or under a dual-task paradigm, i.e., combined with a conversation. Double limb support was the most sensitive variable to describe adaptation to walking condition. The index of responsiveness was significantly larger for individuals with dementia. The six discriminating temporal-spatial gait descriptors provide new focus for health care professionals involved in diagnosis and treatment of elderly with dementia. The index of responsiveness can be used to describe a bandwidth of safety, identifying individuals with dementia at risk of falling.

Modeling trade-off between time-optimal and minimum energy in saccade main sequence

Saccadic eye movement is highly stereotyped and commonly believed to be governed by an open-loop control mechanism. We propose a principle combining time-optimal and minimum control energy criteria to account for the saccade main sequence as observed from empirical data. The model prediction revealed that the weighting factor of the energy conservation becomes more dominant than the time-optimal when the saccade amplitude is large. We demonstrate that the proposed model is a general form synthesizing the time-optimum, minimum torque change, and minimum control effort models. In addition, we show the connection between our model and the stochastic minimum variance models from the aspect of optimization.

An empirical validation of a base-excitation model to predict harvestable energy from a suspended-load backpack system

Suspended-load backpacks have been proposed as a way to provide power for small electronic devices by capturing the mechanical energy generated by the vertical movement of the suspended load and converting it into electrical energy. The aim of the current study was to build a base excitation model able to predict the relative velocity of the load (an index of the amount of harvestable energy of such a system) using as inputs the mass of the suspended load, the walking speed and the leg length of the user. Nine human participants walked on a treadmill under two load conditions (15.8 kg and 22.6 kg load) and three walking speed conditions (1.16 m/s, 1.43 m/s and 1.70 m/s). The predictions of the load velocity by the base-excitation model under these conditions were then compared with the measured load velocity. The results of this study showed a moderately strong correlation (0.76) between the root mean square of the predicted and measured relative velocity of the load, and the average absolute error of these predictions was 24.2%. These results provide support for the utility of this approach and also provide motivation for further refinement of the base excitation model for the prediction of the amount of energy able to be harvested from suspended-load backpack systems.