Assisting people with visual impairments in aiming at a target on a large wall-mounted display

Aldas

ACM Trans. Access. Comput.

et al. 2022

Locating and grasping objects is a critical task in people’s daily lives. For people with visual impairments, this task can be a daily struggle. The support of augmented reality frameworks in smartphones can overcome the limitations of current object detection applications designed for people with visual impairments. We present AIGuide, a self-contained smartphone application that leverages augmented reality technology to help users locate and pick up objects around them. We conducted a user study to investigate the effectiveness of AIGuide in a visual prosthetic for providing guidance; compare it to other assistive technology form factors; investigate the use of multimodal feedback, and provide feedback about the overall experience. We gathered performance data and participants’ reactions and analyzed videos to understand users’ interactions with the nonvisual smartphone user interface. Our results show that AIGuide is a promising technology to help people with visual impairments locate and acquire objects in their daily routine. The benefits of AIGuide may be enhanced with appropriate interaction design.

Section: Hand Guidancementioning

confidence: 99%

Section: Hand Guidancementioning

confidence: 99%

Section: Nonvisual Guidance Interfacementioning

confidence: 99%

See 1 more Smart Citation

AIGuide: Augmented Reality Hand Guidance in a Visual Prosthetic

Aldas

ACM Trans. Access. Comput.

et al. 2022

Extended Abstracts of the 2020 Annual Symposium on Computer-Human Interaction in Play

“…We measured effectiveness (using correctness) and efficiency (using RT); which are valid scales grounded in the literature [24]. However, it is arguable that different scales and techniques such as, sensor data [19], computer vision [22], multi scale measurements [1,28] could had been used. Though we followed an ecological and accurate research design, we understand that other methodological decisions may play an important role in the results.…”

Section: Limitations and Conclusionmentioning

confidence: 99%

Children's Interaction with Motion-Based Touchless Games

Lee-Cultura

Sharma

Aloizou

et al. 2020

Leveraging movement data to support children's learning is appealing and technically challenging. However, there is limited knowledge about exploiting the complete design potential of bodily interplay in learning games. We conducted an in-the-wild study with 8 children, with special educational needs, playing a language based educational motion-based touchless game. We collected children's interaction data (correctness and reaction time), and data regarding the different design elements (game settings) implemented in 90 game sessions. Our analysis shows that number of items on-screen, selection gestures, and time to select items, impact the effectiveness (correctness) and efficiency (reaction time) of the children. We highlight the value of interaction analytics and quantify the relationship between different game design elements and children's efficiency and effectiveness. Our findings help shape the future of learning research by emphasising the substantial benefits of collecting movement data during children's interaction with learning games. CCS CONCEPTS • Human-centered computing → Gestural input; Empirical studies in HCI; Empirical studies in interaction design; Empirical studies in accessibility; • Applied computing → Interactive learning environments.

“…In 2016, Kibum Kim et al [16] had introduced a novel haptic gadget, which investigates the utilization of vibrotactile input in visually impaired client look systems on a huge divider mounted display. Utilizing mid-air motions helped by vibrotactile criticism, they thought about three target-pointing systems: Random (benchmark) and two novel strategies -Cruciform and Radial.…”

Section: Review Of Existing Literaturesmentioning

confidence: 99%

Gesture Recognition Algorithm for Visually Blind Touch Interaction Optimization Using Crow Search Method

Aslam

Samreen

2020

IEEE Access

Touch screen interaction system is highly demanding for new innovations from the point of visual sensing, as familiar and easily tracing the virtual key board on the screen, three dimensional gesture communications methods, and RFID sensing etc. In spite of the existence of these types of interaction methods, visually impaired people struggle to have easy access to touch screens. The main goal of the research is to overcome the navigation problems that blind people face while interacting with touch screens. In this examination we centered to build up a Braille sketch; a motion put together information technique with respect to contact screen advanced mobile phones for outwardly debilitated individuals. Utilizing Braille codes to perform motions on contact screen makes the outwardly tested people agreeable in light of the fact that Braille is the reason for correspondence. The streamlining procedure is the demonstration of amplifying or limiting a genuine function by systematic choosing input parameters from an accessible pool of parameters and to figure the estimation of function. Here, we accept variables as hand finger motion facilitate, for example, the coordinate values on x and y axises, swipe limit speed, swipe least separation, pixel rate and speed of X and Y. To build the execution of the system structure, we improve by differing shrouded layer and neuron using Crow Search Algorithm (CSO). The ANN with CSA achieves the Optimal Hidden Layer and Neuron (OHLN) to anticipate the right motion yields. These strategies present an answer that will consequently perceive the hand signals so impeded individual can without much of a stretch speak with ordinary individuals. The proposed model will give high precision with ideal execution measurements contrasted with other existing created demonstrate.