Spatial Knowledge via Auditory Information for Blind Individuals: Spatial Cognition Studies and the Use of Audio-VR

Afonso-Jaco, Amandine; Katz, Brian F. G.

doi:10.3390/s22134794

Cited by 8 publications

(4 citation statements)

References 71 publications

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“…This would be particularly interesting for large-scale capacity studies (such as navigation) as it would enable more flexible and safer experimental protocols, while guaranteeing the inclusion of visually impaired people in experimental protocols. Lastly, the question of the sound environment in addition to visualization in VR/VE would also be particularly relevant, given the great importance of auditory cues for the spatial perception of visually impaired people [59][60][61].…”

Section: Conclusion and Discussion: Ve In Future LV Researchmentioning

confidence: 99%

A review study of space perception and navigation of people with low vision: is simulated low vision a reliable methodology?

Dong,

Karmann

2024

IOP Conf. Ser.: Earth Environ. Sci.

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The inclusion of visually impaired participants in research protocols concerning their perception of space and navigation is essential for the reliability of the results, given the strategies developed by the people concerned in everyday life. However, the diversity of visual impairments, the scarcity of participants and possible safety issues due to obstacles in the physical space induce limitations and prompt researchers to look into alternative methodologies. Simulated low vision is seen as an option. This method involves sighted participants wearing goggles with customized filters or watching processed images in virtual environments. The objective of this study is to investigate the reliability of simulated low vision as a research method to describe the space perception and navigation of people with visual impairment. We conducted a literature review and identified 36 quantitative studies on low vision spatial performance involving multiple user groups. Simulated low vision proved effective in small-scale spatial ability evaluation, such as object detection and distance estimation, but remained challenging regarding large-scale capacity, such as navigation with mobility requirement. Advances in virtual environments suggest that they are a good alternative to goggles and screen displays because of their precision in mimicking ocular problems in simulation settings. Finally, the use of head-mounted-display (HMD) by people with real low vision could open up the possibility of greater testing in safer and controlled conditions, but requires confirmation of the validity of the protocols.

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Section: Conclusion and Discussion: Ve In Future LV Researchmentioning

confidence: 99%

A review study of space perception and navigation of people with low vision: is simulated low vision a reliable methodology?

Dong,

Karmann

2024

IOP Conf. Ser.: Earth Environ. Sci.

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show abstract

“…Furthermore, very few studies have dealt with the neural mechanisms of navigation, wayfinding and formation of allocentric cognitive maps ( Ottink et al, 2022 ). Future research should therefore focus on better studying these processes; an endeavor that can be facilitated by the recent advances in audio-based virtual reality ( Halko et al, 2014 ; Afonso-Jaco and Katz, 2022 ; Andrade et al, 2022 ).…”

Section: Discussionmentioning

confidence: 99%

Neural substrates of spatial processing and navigation in blindness: An activation likelihood estimation meta-analysis

et al. 2022

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Even though vision is considered the best suited sensory modality to acquire spatial information, blind individuals can form spatial representations to navigate and orient themselves efficiently in space. Consequently, many studies support the amodality hypothesis of spatial representations since sensory modalities other than vision contribute to the formation of spatial representations, independently of visual experience and imagery. However, given the high variability in abilities and deficits observed in blind populations, a clear consensus about the neural representations of space has yet to be established. To this end, we performed a meta-analysis of the literature on the neural correlates of spatial processing and navigation via sensory modalities other than vision, like touch and audition, in individuals with early and late onset blindness. An activation likelihood estimation (ALE) analysis of the neuroimaging literature revealed that early blind individuals and sighted controls activate the same neural networks in the processing of non-visual spatial information and navigation, including the posterior parietal cortex, frontal eye fields, insula, and the hippocampal complex. Furthermore, blind individuals also recruit primary and associative occipital areas involved in visuo-spatial processing via cross-modal plasticity mechanisms. The scarcity of studies involving late blind individuals did not allow us to establish a clear consensus about the neural substrates of spatial representations in this specific population. In conclusion, the results of our analysis on neuroimaging studies involving early blind individuals support the amodality hypothesis of spatial representations.

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“…AI-driven cognitive support technologies leverage natural language processing and machine learning to facilitate communication, memory Journal of Disability Research 2024 retention, and decision-making. These systems can assist in organizing schedules, providing reminders, and generating contextually relevant responses in conversations (Afonso-Jaco and Katz, 2022;Boulanger, 2022;Wieseler, 2022). By bridging cognitive gaps, these technologies empower individuals to maintain greater autonomy and participate more actively in social interactions and personal tasks.…”

Section: Cognitive Support For Nurturing Cognitive Autonomymentioning

confidence: 99%

A Conceptual Model for Inclusive Technology: Advancing Disability Inclusion through Artificial Intelligence

Almufareh,

Kausar,

Humayun

et al. 2024

Journal of Disability Research

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Artificial intelligence (AI) has ushered in transformative changes, championing inclusion and accessibility for individuals with disabilities. This article delves into the remarkable AI-driven solutions that have revolutionized their lives across various domains. From assistive technologies such as voice recognition and AI-powered smart glasses catering to diverse needs, to healthcare benefiting from early disease detection algorithms and wearable devices that monitor vital signs and alert caregivers in emergencies, AI has steered in significant enhancements. Moreover, AI-driven prosthetics and exoskeletons have substantially improved mobility for those with limb impairments. The realm of education has not been left untouched, with AI tools creating inclusive learning environments that adapt to individual learning styles, paving the way for academic success among students with disabilities. However, the boundless potential of AI also presents ethical concerns and challenges. Issues like safeguarding data privacy, mitigating algorithmic bias, and bridging the digital divide must be thoughtfully addressed to fully harness AI’s potential in empowering individuals with disabilities. To complement these achievements, a robust conceptual model for AI disability inclusion serves as the theoretical framework, guiding the development of tailored AI solutions. By striking a harmonious balance between innovation and ethics, AI has the power to significantly enhance the overall quality of life for individuals with disabilities across a spectrum of vital areas.

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Spatial Knowledge via Auditory Information for Blind Individuals: Spatial Cognition Studies and the Use of Audio-VR

Cited by 8 publications

References 71 publications

A review study of space perception and navigation of people with low vision: is simulated low vision a reliable methodology?

A review study of space perception and navigation of people with low vision: is simulated low vision a reliable methodology?

Neural substrates of spatial processing and navigation in blindness: An activation likelihood estimation meta-analysis

A Conceptual Model for Inclusive Technology: Advancing Disability Inclusion through Artificial Intelligence

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