Arash Mahboobin

A mechanism for sensory re-weighting in postural control.

A key finding of human balance experiments has been that the integration of sensory information utilized for postural control appears to be dynamically regulated to adapt to changing environmental conditions and the available sensory information, a process referred to as “sensory re-weighting.” We propose a postural control model that includes automatic sensory re-weighting. This model is an adaptation of a previously reported model of sensory feedback that included manual sensory re-weighting. The new model achieves sensory re-weighting that is physiologically plausible and readily implemented. Model simulations are compared to previously reported experimental results to demonstrate the automated sensory re-weighting strategy of the modified model. On the whole, the postural sway time series generated by the model with automatic sensory re-weighting show good agreement with experimental data, and are capable of producing patterns similar to those observed experimentally.

2008 Special Issue: Sensory adaptation in human balance control: Lessons for biomimetic robotic bipeds

This paper describes mechanisms used by humans to stand on moving platforms, such as a bus or ship, and to combine body orientation and motion information from multiple sensors including vision, vestibular, and proprioception. A simple mechanism, sensory re-weighting, has been proposed to explain how human subjects learn to reduce the effects of inconsistent sensors on balance. Our goal is to replicate this robust balance behavior in bipedal robots. We review results exploring sensory re-weighting in humans and describe implementations of sensory re-weighting in simulation and on a robot.

Designing vibrotactile balance feedback for desired body sway reductions

Vibrotactile feedback about body position and velocity has been shown to be effective at reducing low frequency body sway (below about 0.5 Hz) in response to balance perturbations while standing. However, current devices cause an undesirable increase in high frequency body sway. In addition, unlike other sensory prostheses such as hearing aids, which are fine-tuned to the user, current vibrotactile balance prostheses largely employ a “one size fits all” approach, in that they use the same settings (i.e. parameter values) for all subjects. Rather than using a fixed design consisting of position and velocity feedback for all subjects, we propose a “custom design” approach that employs system identification methods to identify the feedback required to achieve a desired body sway frequency response for the subject. Our derivations and simulations show that in order to accomplish this objective, feedback consisting of a subject-specific filtered combination of body position, velocity and acceleration is required. Simulation results are provided to illustrate the results.

A Model-Based Approach To Attention and Sensory Integration in Postural Control of Older Adults

We conducted a dual-task experiment that involved information processing (IP) tasks concurrent with postural perturbations to explore the interaction between attention and sensory integration in postural control in young and older adults. Data were fit to a postural control model incorporating sensory integration and the influence of attention. This model hypothesizes that the cognitive processing and integration of sensory inputs for balance requires time, and that attention influences this processing time, as well as sensory selection by facilitating specific sensory channels. Differences in the time delay of the postural control model were found for age and IP task, suggesting enhanced vulnerability of balance processes in older adults to interference from interfering cognitive IP tasks

Effects of acute peripheral/central visual field loss on standing balance

Vision impairments such as age-related macular degeneration (AMD) and glaucoma are among the top risk factors for geriatric falls and falls-related injuries. AMD and glaucoma lead to loss of the central and peripheral visual fields, respectively. This study utilized a custom contact lens model to occlude the peripheral or central visual fields in healthy adults, offering a novel within-subject approach to improve our understanding of the etiology of balance impairments that may lead to an increased fall risk in patients with visual field loss. Two dynamic posturography tests, including an adapted version of the Sensory Organization Test and a virtual reality environment with the visual scene moving sinusoidally, were used to evaluate standing balance. Balance stability was quantified by displacement and time-normalized path length of the center of pressure. Nine young and eleven older healthy adults wore visual field occluding contact lenses during posturography assessments to compare the effects of acute central and peripheral visual field occlusion. The results found that visual field occlusion had greater impact on older adults than young adults, specifically when proprioceptive cues are unreliable. Furthermore, the results suggest that both central and peripheral visions are important in postural control; however, peripheral vision may be more sensitive to movement in the environment.

Model-Based Investigation of Ankle Stiffness Control Versus Active Feedback Control During Quiet Standing

The mechanisms involved in generating corrective torques to maintain balance during human upright stance have been attributed to passive control (i.e. intrinsic properties of muscles and tendons, such as the intrinsic stiffness and viscoelasticity of muscles) and active control (i.e. neurally-mediated sensory-based feedback control) [1–3]. While there continues to be some debate over the roles of active versus passive mechanisms in maintaining balance, especially during quiet (unperturbed) standing [4–6], the general consensus is that both mechanisms contribute to postural control [3]. However, active mechanisms have been shown to play a more dominant role in maintaining upright stance, particularly during perturbed conditions [7, 8].© 2011 ASME

Scaffolding to Support Problem-Solving Performance in a Bioengineering Lab—A Case Study

Background: Engineering programs must equip students to solve open-ended workplace problems. However, the literature points to actual or potential difficulties faced by students in solving open-ended or complex problems. During Fall 2014, the authors’ students experienced difficulties in solving open-ended bio-signals laboratory problems of designing input signals to analyze unknown systems via MATLAB programming. These difficulties resulted in low performance. Intended Outcomes: To support, or scaffold, problem-solving in subsequent semesters, a strategy of frequent and timely monitoring and feedback was used. The hypotheses were that these scaffolding strategies would be associated with enhanced performance on open-ended projects, and would support students in similar future work once removed. Application Design: Based upon strategies from the scaffolding literature, assignments that guided problem decomposition were used. Flipped instruction challenged students to prepare for the laboratory by reviewing worked programming examples and completing online assessments. The laboratory sessions were reserved for collaborative, hands-on programming, with instructor oversight, as in a problem-based learning environment. Students submitted frequent progress reports for self-monitoring and feedback throughout each project. Findings: A statistical comparison of project scores across semesters revealed performance improvements with scaffolding. Post-scaffolding assessment in a follow-up course determined scaffolding to be helpful and applicable by these students for similar projects. These preliminary results are important for STEM students and instructors encountering challenges with open-ended problem-solving of this nature, and they provide quantitative evidence recently called for by the STEM scaffolding literature.

Improved Simulation of Heel Contact During Normal Walking

Causes of slips and falls involve the interaction of complex environmental and human factors [1]. While experimental studies have been useful to identify biomechanical variables that may impact slipping severity, it is unclear how these factors interact. Relying on experiments alone to acquire this knowledge and establishing cause-effect relationships in complex dynamic systems is difficult. Computational modeling and forward dynamics simulations of walking and slipping are needed to meet these research needs.Copyright