A Perspective on Using Virtual Reality to Incorporate the Affective Context of Everyday Falls Into Fall Prevention

Raffegeau, Tiphanie E.; Young, William R.; Fino, Peter C.; Williams, A. Mark

doi:10.2196/36325

Cited by 3 publications

(2 citation statements)

References 118 publications

(185 reference statements)

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“…These studies were also limited in the range of risky conditions that could safely be used. One potential way to address this limitation is to use virtual reality (VR) in combination with physical perturbations to create complex walking scenarios that mimic the real world ( Cano Porras et al, 2018 , 2019 ; Raffegeau et al, 2023 ). An advantage of this method is that it would allow for the evaluation of decision-making in real-world scenarios within a controlled and safe environment.…”

Section: Behavioral Riskmentioning

confidence: 99%

“…These outcomes may be presented in the form of trips or slips, which are often the cause of falls in both young and older adults and are, therefore, ecologically valid decision consequences. Technologies such as augmented and virtual reality (VR) can be particularly useful in these contexts as they allow for the simulation of real-world environments within which one or more factors can be systematically manipulated ( Cano Porras et al, 2018 , 2019 ; Raffegeau et al, 2023 ). For example, the effects of movement context may be studied by using multiple virtual environments such as road-crossing in traffic, hiking on a trail, or navigating in a crowded mall.…”

Section: Opportunities For Advancing Theoretical Understanding and As...mentioning

confidence: 99%

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Aberrant decision-making as a risk factor for falls in aging

Jain,

Schweighofer,

Finley

2024

Front. Aging Neurosci.

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Neuromotor impairments resulting from natural aging and aging-related diseases are often accompanied by a heightened prevalence of falls and fall-related injuries. Conventionally, the study of factors contributing to falls focuses on intrinsic characteristics, such as sensorimotor processing delays and weakness, and extrinsic factors, such as environmental obstacles. However, the impact of these factors only becomes evident in response to people’s decisions about how and where they will move in their environment. This decision-making process can be considered a behavioral risk factor, and it influences the extent to which a person engages in activities that place them near the limits of their capacity. While there are readily available tools for assessing intrinsic and extrinsic fall risk, our understanding of how to assess behavioral risk is limited. Measuring behavioral risk requires a systematic assessment of how people make decisions when walking in complex environments and how these decisions relate to their functional capacity. We propose that experimental methods and computational models derived from behavioral economics can stimulate the development of such assessments. Behavioral economics relies on theoretical models and empirical studies to characterize the factors that influence how people make decisions under risky conditions where a given decision can have variable outcomes. Applying a behavioral economic approach to walking can provide insight into how internal assessment of one’s fall risk influences the tasks that one is willing to perform. Ultimately, these assessments will allow us to identify people who make choices that increase their likelihood of fall-related injuries.

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Section: Behavioral Riskmentioning

confidence: 99%

Section: Opportunities For Advancing Theoretical Understanding and As...mentioning

confidence: 99%

Aberrant decision-making as a risk factor for falls in aging

Jain,

Schweighofer,

Finley

2024

Front. Aging Neurosci.

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Behavioral risk models explain locomotor and balance changes when walking at virtual heights

Seddighi,

Woo,

Montoya

et al. 2024

Preprint

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Walking in daily life requires humans to adapt to environments that can influence fear of falling and anxiety about a potential fall. In such environments, individuals may adopt compensatory locomotor and balance changes to maintain a constant expected risk function equal to the product of the probability of some event (e.g., a fall) and the cost of that event (e.g., injury or death). Here, we tested whether locomotor behaviors broadly align with this risk model in two experiments with height-related threats in immersive virtual reality. In Experiment 1, we examined how individuals change their locomotor trajectory while walking along a straight high-elevation walkway. In Experiment 2, we examined how individuals change trajectory and balance control during curved walking where the location of high elevation threat varied. Participants adopted two behaviors that decreased their probability of falling off the edge and aligned with the risk-based model: participants altered their proximity to perceived threats that pose high costs (e.g., a high-elevation ledge), and decreased mediolateral center of mass velocity when that was not possible. Taken together, our results suggest that individuals alter locomotor behavior to change the probability of falling based on the perceived cost of that fall.

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The Interface of Minds Human-Machine Interaction in the Digital Age

Vanisri,

Padhy

2024

Advances in Computational Intelligence and Robotics

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Artificial intelligence (AI) is an increasingly expanding domain within the field of computer science that engenders intelligent machines competent in executing human tasks. The implementation of AI technology is progressively becoming more prevalent in sectors such as healthcare, banking, and transportation. The efficacy, accuracy, and decision-making capabilities of AI have the potential to revolutionize a wide array of industries. AI acquires knowledge and enhances its proficiency by utilising machine learning algorithms. These algorithms allow robots to assess extensive datasets, subsequently discovering patterns and insights that surpass human comprehension. Human-machine interaction centres on the collaboration between individuals and computers or machines, where it can anticipate assumptions and methods utilized to facilitate a spontaneous framework. The basic purpose of human-computer interaction (HCI) is to create functional systems that end users find useable, safe, and effective.

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A Perspective on Using Virtual Reality to Incorporate the Affective Context of Everyday Falls Into Fall Prevention

Cited by 3 publications

References 118 publications

Aberrant decision-making as a risk factor for falls in aging

Aberrant decision-making as a risk factor for falls in aging

Behavioral risk models explain locomotor and balance changes when walking at virtual heights

The Interface of Minds Human-Machine Interaction in the Digital Age

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