Design and Implementation of an Intelligent Assistive System for Visually Impaired People for Aerial Obstacle Avoidance and Fall Detection

Chang, Wan-Jung; Chen, Liangbi; Chen, Ming-Che; Su, Jie; Sie, Cheng-You; Yang, Chen-Chung

doi:10.1109/jsen.2020.2990609

Cited by 59 publications

(33 citation statements)

References 30 publications

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“…The findings hopefully empower the knowledge of how the visually impaired persons are stressed and emotionally affected by SSD navigation and contribute to the development of the intelligent navigation devices, aiming for the VIPs’ safety and well-being. The results of our work can inspire researchers working in the field of IoT devices comprising sensors, antennas, and Bluetooth, which have created navigation rules based on a fuzzy controller [ 69 ], GPS embedded in a stick with voice recognition for obstacles detection [ 70 ], computer vision-based assistants [ 71 ], or assistive systems relying on wearable smart glasses and mobile applications [ 72 ].…”

Section: Discussionmentioning

confidence: 99%

Cognitive and Affective Assessment of Navigation and Mobility Tasks for the Visually Impaired via Electroencephalography and Behavioral Signals

Lupu

Mitruț

Stan

et al. 2020

Sensors

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This paper presented the assessment of cognitive load (as an effective real-time index of task difficulty) and the level of brain activation during an experiment in which eight visually impaired subjects performed two types of tasks while using the white cane and the Sound of Vision assistive device with three types of sensory input—audio, haptic, and multimodal (audio and haptic simultaneously). The first task was to identify object properties and the second to navigate and avoid obstacles in both the virtual environment and real-world settings. The results showed that the haptic stimuli were less intuitive than the audio ones and that the navigation with the Sound of Vision device increased cognitive load and working memory. Visual cortex asymmetry was lower in the case of multimodal stimulation than in the case of separate stimulation (audio or haptic). There was no correlation between visual cortical activity and the number of collisions during navigation, regardless of the type of navigation or sensory input. The visual cortex was activated when using the device, but only for the late-blind users. For all the subjects, the navigation with the Sound of Vision device induced a low negative valence, in contrast with the white cane navigation.

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Section: Discussionmentioning

confidence: 99%

Cognitive and Affective Assessment of Navigation and Mobility Tasks for the Visually Impaired via Electroencephalography and Behavioral Signals

Lupu

Mitruț

Stan

et al. 2020

Sensors

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“…Consequently, framing safe navigation as an obstacle avoidance task is a more complete problem approach for BVIP navigation, than traversable area detection. Obstacle avoidance has become a high active research area in recent years, across robot navigation systems [ 133 ], BVIP navigation systems [ 23 , 28 ], and autonomous vehicles [ 134 ] research domains. To explore it more fully, we identify two groupings in the research approaches used.…”

Section: Real-time Navigationmentioning

confidence: 99%

“…They also utilized a liquid sensor to detect wet floors. Chang et al [ 28 ] used an infrared transceiver sensor to detect the distance between users and aerial obstacles. Islam et al [ 70 ] used three ultrasonic sensors to detect obstacles on the left, right, and in front of the user.…”

Section: Real-time Navigationmentioning

confidence: 99%

A Systematic Review of Urban Navigation Systems for Visually Impaired People

El-taher

Taha

Courtney

et al. 2021

Sensors

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Blind and Visually impaired people (BVIP) face a range of practical difficulties when undertaking outdoor journeys as pedestrians. Over the past decade, a variety of assistive devices have been researched and developed to help BVIP navigate more safely and independently. In addition, research in overlapping domains are addressing the problem of automatic environment interpretation using computer vision and machine learning, particularly deep learning, approaches. Our aim in this article is to present a comprehensive review of research directly in, or relevant to, assistive outdoor navigation for BVIP. We breakdown the navigation area into a series of navigation phases and tasks. We then use this structure for our systematic review of research, analysing articles, methods, datasets and current limitations by task. We also provide an overview of commercial and non-commercial navigation applications targeted at BVIP. Our review contributes to the body of knowledge by providing a comprehensive, structured analysis of work in the domain, including the state of the art, and guidance on future directions. It will support both researchers and other stakeholders in the domain to establish an informed view of research progress.

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“…Inspired by these constraints, many techniques have been developed based on smart sensor technology and digital data processing to enhance the mobility of BVIP and help them to move freely in an environment regardless of its dynamic changes. Based on the related literature, these techniques are classified into two main types: sonar input [ 25 , 26 ] and camera input systems [ 27 , 28 , 29 , 30 ]. Generally, the sonar systems are based on ultrasonic, laser, and infrared signals as inputs, which can provide a range of information of an obstacle.…”

Section: Introductionmentioning

confidence: 99%

Design and Development of a Wearable Assistive Device Integrating a Fuzzy Decision Support System for Blind and Visually Impaired People

Bouteraa

2021

Micromachines

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In this article, a new design of a wearable navigation support system for blind and visually impaired people (BVIP) is proposed. The proposed navigation system relies primarily on sensors, real-time processing boards, a fuzzy logic-based decision support system, and a user interface. It uses sensor data as inputs and provides the desired safety orientation to the BVIP. The user is informed about the decision based on a mixed voice–haptic interface. The navigation aid system contains two wearable obstacle detection systems managed by an embedded controller. The control system adopts the Robot Operating System (ROS) architecture supported by the Beagle Bone Black master board that meets the real-time constraints. The data acquisition and obstacle avoidance are carried out by several nodes managed by the ROS to finally deliver a mixed haptic–voice message for guidance of the BVIP. A fuzzy logic-based decision support system was implemented to help BVIP to choose a safe direction. The system has been applied to blindfolded persons and visually impaired persons. Both types of users found the system promising and pointed out its potential to become a good navigation aid in the future.

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Design and Implementation of an Intelligent Assistive System for Visually Impaired People for Aerial Obstacle Avoidance and Fall Detection

Cited by 59 publications

References 30 publications

Cognitive and Affective Assessment of Navigation and Mobility Tasks for the Visually Impaired via Electroencephalography and Behavioral Signals

Cognitive and Affective Assessment of Navigation and Mobility Tasks for the Visually Impaired via Electroencephalography and Behavioral Signals

A Systematic Review of Urban Navigation Systems for Visually Impaired People

Design and Development of a Wearable Assistive Device Integrating a Fuzzy Decision Support System for Blind and Visually Impaired People

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