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Virtualizing physical space
(2021)
The true cost for virtual reality is not the hardware, but the physical space it requires, as a one-to-one mapping of physical space to virtual space allows for the most immersive way of navigating in virtual reality. Such “real-walking” requires physical space to be of the same size and the same shape of the virtual world represented. This generally prevents real-walking applications from running on any space that they were not designed for.
To reduce virtual reality’s demand for physical space, creators of such applications let users navigate virtual space by means of a treadmill, altered mappings of physical to virtual space, hand-held controllers, or gesture-based techniques. While all of these solutions succeed at reducing virtual reality’s demand for physical space, none of them reach the same level of immersion that real-walking provides.
Our approach is to virtualize physical space: instead of accessing physical space directly, we allow applications to express their need for space in an abstract way, which our software systems then map to the physical space available. We allow real-walking applications to run in spaces of different size, different shape, and in spaces containing different physical objects. We also allow users immersed in different virtual environments to share the same space.
Our systems achieve this by using a tracking volume-independent representation of real-walking experiences — a graph structure that expresses the spatial and logical relationships between virtual locations, virtual elements contained within those locations, and user interactions with those elements. When run in a specific physical space, this graph representation is used to define a custom mapping of the elements of the virtual reality application and the physical space by parsing the graph using a constraint solver. To re-use space, our system splits virtual scenes and overlap virtual geometry. The system derives this split by means of hierarchically clustering of our virtual objects as nodes of our bi-partite directed graph that represents the logical ordering of events of the experience. We let applications express their demands for physical space and use pre-emptive scheduling between applications to have them share space. We present several application examples enabled by our system. They all enable real-walking, despite being mapped to physical spaces of different size and shape, containing different physical objects or other users.
We see substantial real-world impact in our systems. Today’s commercial virtual reality applications are generally designing to be navigated using less immersive solutions, as this allows them to be operated on any tracking volume. While this is a commercial necessity for the developers, it misses out on the higher immersion offered by real-walking. We let developers overcome this hurdle by allowing experiences to bring real-walking to any tracking volume, thus potentially bringing real-walking to consumers.
Die eigentlichen Kosten für Virtual Reality Anwendungen entstehen nicht primär durch die erforderliche Hardware, sondern durch die Nutzung von physischem Raum, da die eins-zu-eins Abbildung von physischem auf virtuellem Raum die immersivste Art von Navigation ermöglicht. Dieses als „Real-Walking“ bezeichnete Erlebnis erfordert hinsichtlich Größe und Form eine Entsprechung von physischem Raum und virtueller Welt. Resultierend daraus können Real-Walking-Anwendungen nicht an Orten angewandt werden, für die sie nicht entwickelt wurden.
Um den Bedarf an physischem Raum zu reduzieren, lassen Entwickler von Virtual Reality-Anwendungen ihre Nutzer auf verschiedene Arten navigieren, etwa mit Hilfe eines Laufbandes, verfälschten Abbildungen von physischem zu virtuellem Raum, Handheld-Controllern oder gestenbasierten Techniken. All diese Lösungen reduzieren zwar den Bedarf an physischem Raum, erreichen jedoch nicht denselben Grad an Immersion, den Real-Walking bietet.
Unser Ansatz zielt darauf, physischen Raum zu virtualisieren: Anstatt auf den physischen Raum direkt zuzugreifen, lassen wir Anwendungen ihren Raumbedarf auf abstrakte Weise formulieren, den unsere Softwaresysteme anschließend auf den verfügbaren physischen Raum abbilden. Dadurch ermöglichen wir Real-Walking-Anwendungen Räume mit unterschiedlichen Größen und Formen und Räume, die unterschiedliche physische Objekte enthalten, zu nutzen. Wir ermöglichen auch die zeitgleiche Nutzung desselben Raums durch mehrere Nutzer verschiedener Real-Walking-Anwendungen.
Unsere Systeme erreichen dieses Resultat durch eine Repräsentation von Real-Walking-Erfahrungen, die unabhängig sind vom gegebenen Trackingvolumen – eine Graphenstruktur, die die räumlichen und logischen Beziehungen zwischen virtuellen Orten, den virtuellen Elementen innerhalb dieser Orte, und Benutzerinteraktionen mit diesen Elementen, ausdrückt. Bei der Instanziierung der Anwendung in einem bestimmten physischen Raum wird diese Graphenstruktur und ein Constraint Solver verwendet, um eine individuelle Abbildung der virtuellen Elemente auf den physischen Raum zu erreichen. Zur mehrmaligen Verwendung des Raumes teilt unser System virtuelle Szenen und überlagert virtuelle Geometrie. Das System leitet diese Aufteilung anhand eines hierarchischen Clusterings unserer virtuellen Objekte ab, die als Knoten unseres bi-partiten, gerichteten Graphen die logische Reihenfolge aller Ereignisse repräsentieren. Wir verwenden präemptives Scheduling zwischen den Anwendungen für die zeitgleiche Nutzung von physischem Raum. Wir stellen mehrere Anwendungsbeispiele vor, die Real-Walking ermöglichen – in physischen Räumen mit unterschiedlicher Größe und Form, die verschiedene physische Objekte oder weitere Nutzer enthalten.
Wir sehen in unseren Systemen substantielles Potential. Heutige Virtual Reality-Anwendungen sind bisher zwar so konzipiert, dass sie auf einem beliebigen Trackingvolumen betrieben werden können, aber aus kommerzieller Notwendigkeit kein Real-Walking beinhalten. Damit entgeht Entwicklern die Gelegenheit eine höhere Immersion herzustellen. Indem wir es ermöglichen, Real-Walking auf jedes Trackingvolumen zu bringen, geben wir Entwicklern die Möglichkeit Real-Walking zu ihren Nutzern zu bringen.
Background/Purpose
Muscular reflex responses of the lower extremities to sudden gait disturbances are related to postural stability and injury risk. Chronic ankle instability (CAI) has shown to affect activities related to the distal leg muscles while walking. Its effects on proximal muscle activities of the leg, both for the injured- (IN) and uninjured-side (NON), remain unclear. Therefore, the aim was to compare the difference of the motor control strategy in ipsilateral and contralateral proximal joints while unperturbed walking and perturbed walking between individuals with CAI and matched controls.
Materials and methods
In a cross-sectional study, 13 participants with unilateral CAI and 13 controls (CON) walked on a split-belt treadmill with and without random left- and right-sided perturbations. EMG amplitudes of muscles at lower extremities were analyzed 200 ms after perturbations, 200 ms before, and 100 ms after (Post100) heel contact while walking. Onset latencies were analyzed at heel contacts and after perturbations. Statistical significance was set at alpha≤0.05 and 95% confidence intervals were applied to determine group differences. Cohen’s d effect sizes were calculated to evaluate the extent of differences.
Results
Participants with CAI showed increased EMG amplitudes for NON-rectus abdominus at Post100 and shorter latencies for IN-gluteus maximus after heel contact compared to CON (p<0.05). Overall, leg muscles (rectus femoris, biceps femoris, and gluteus medius) activated earlier and less bilaterally (d = 0.30–0.88) and trunk muscles (bilateral rectus abdominus and NON-erector spinae) activated earlier and more for the CAI group than CON group (d = 0.33–1.09).
Conclusion
Unilateral CAI alters the pattern of the motor control strategy around proximal joints bilaterally. Neuromuscular training for the muscles, which alters motor control strategy because of CAI, could be taken into consideration when planning rehabilitation for CAI.
Background/Purpose
Muscular reflex responses of the lower extremities to sudden gait disturbances are related to postural stability and injury risk. Chronic ankle instability (CAI) has shown to affect activities related to the distal leg muscles while walking. Its effects on proximal muscle activities of the leg, both for the injured- (IN) and uninjured-side (NON), remain unclear. Therefore, the aim was to compare the difference of the motor control strategy in ipsilateral and contralateral proximal joints while unperturbed walking and perturbed walking between individuals with CAI and matched controls.
Materials and methods
In a cross-sectional study, 13 participants with unilateral CAI and 13 controls (CON) walked on a split-belt treadmill with and without random left- and right-sided perturbations. EMG amplitudes of muscles at lower extremities were analyzed 200 ms after perturbations, 200 ms before, and 100 ms after (Post100) heel contact while walking. Onset latencies were analyzed at heel contacts and after perturbations. Statistical significance was set at alpha≤0.05 and 95% confidence intervals were applied to determine group differences. Cohen’s d effect sizes were calculated to evaluate the extent of differences.
Results
Participants with CAI showed increased EMG amplitudes for NON-rectus abdominus at Post100 and shorter latencies for IN-gluteus maximus after heel contact compared to CON (p<0.05). Overall, leg muscles (rectus femoris, biceps femoris, and gluteus medius) activated earlier and less bilaterally (d = 0.30–0.88) and trunk muscles (bilateral rectus abdominus and NON-erector spinae) activated earlier and more for the CAI group than CON group (d = 0.33–1.09).
Conclusion
Unilateral CAI alters the pattern of the motor control strategy around proximal joints bilaterally. Neuromuscular training for the muscles, which alters motor control strategy because of CAI, could be taken into consideration when planning rehabilitation for CAI.
Background: Gait speed declines with increasing age, but it is unclear if gait speed preferentially correlates with leg muscle strength or mass.
Objective: We determined the relationship between gait speed and (1) leg muscle strength measured at 3 lower extremity joints and (2) leg lean tissue mass (LTM) in healthy young (age: 25 years, n = 20) and old (age: 70 years, n = 20) adults.
Methods: Subjects were tested for maximal isokinetic hip, knee, and ankle extension torque, leg LTM by bioimpedance, and gait performance (i.e., gait speed, stride length) at preferred and maximal gait speeds.
Results: We found no evidence for a preferential relationship between gait performance and leg muscle strength compared with gait performance and leg LTM in healthy young and old adults. In old adults, hip extensor strength only predicted habitual gait speed (R-2 = 0.29, p = 0.015), whereas ankle plantarflexion strength only predicted maximal gait speed and stride length (both R-2 = 0.40, p = 0.003). Conclusions: Gait speed did not preferentially correlate with leg muscle strength or leg LTM, favoring neither outcome for predicting mobility. Thus, we recommend that both leg muscle strength and leg LTM should be tested and trained complementarily. Further, hip and ankle extension torque predicted gait performance, and thus we recommend to test and train healthy old adults by functional integrated multiarticular rather than monoarticular lower extremity strength exercises.
Methods: As part of the Potsdam Gait Study (POGS), healthy old adults completed a no-intervention control period (69.1 +/- 4A yrs, n =14) or a power training program followed by detraining (72.9 +/- 5.4 yrs, n = 15).We measured isokinetic knee extensor and plantarflexor power and measured hip, knee and ankle kinetics at habitual, fast and standardized walking speeds. Results: Power training significantly increased isokinetic knee extensor power (25%), plantarflexor power (43%), and fast gait velocity (5.9%). Gait mechanics underlying the improved fast gait velocity included increases in hip angular impulse (29%) and H1 work (37%) and no changes in positive knee (K2) and A2 work. Detraining further improved fast gait velocity (4.7%) with reductions in H1(-35%), and increases in K2 (36%) and A2 (7%). Conclusion: Power training increased fast gait velocity in healthy old adults by increasing the reliance on hip muscle function and thus further strengthened the age-related distal-to-proximal shift in muscle function. (C) 2016 Elsevier B.V. All rights reserved.
Background In patients with mild cognitive impairment (MCI), gait instability, particularly in dual-task situations, has been associated with impaired executive function and an increased fall risk. Ginkgo biloba extract (GBE) could be an effective mean to improve gait stability. Aims This study investigated the effect of GBE on spatiotemporal gait parameters of MCI patients while walking under single and dual-task conditions. Methods Fifty patients aged 50-85 years with MCI and associated dual-task-related gait impairment participated in this randomised, double-blind, placebo-controlled, exploratory phase IV drug trial. Intervention group (IG) patients received GBE (Symfona (R) forte 120 mg) twice-daily for 6 months while control group (CG) patients received placebo capsules. A 6-month open-label phase with identical GBE dosage followed. Gait was quantified at months 0, 3, 6 and 12. Results After 6 months, dual-task-related cadence increased in the IG compared to the CG (p = 0.019, d = 0.71). No significant changes, but GBE-associated numerical non-significant trends were found after 6-month treatment for dual-task-related gait velocity and stride time variability. Discussion Findings suggest that 120 mg of GBE twice-daily for at least 6 months may improve dual-task-related gait performance in patients with MCI. Conclusions The observed gait improvements add to the understanding of the self-reported unspecified improvements among MCI patients when treated with standardised GBE.