Development of Smart Healthcare System for Visually Impaired using Speech Recognition

Almutairi, Khloud; Ismail, Ahmed; Abdlerazek, Samir; El-Bakry, Hazem M.

doi:10.14569/ijacsa.2020.0111275

Cited by 5 publications

(4 citation statements)

References 11 publications

(13 reference statements)

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“…(a) Robotic wheelchair platform [ 203 ]. (b) Smart glasses prototype [ 204 ]. (c) A user interfaces for the hearing-impaired person [ 205 ].…”

Section: Speech Recognition For Human-medical Equipment Interactionmentioning

confidence: 99%

“…Moreover, as shown in Fig. 23 (b), Almutairi et al proposed smart glasses that can navigate visually impaired patients to destinations based on Global Positioning System, Global System for Mobile communication, Google maps, and speech recognition [ 204 ]. The smart glasses designed by Punith et al can also help a person with a visual disability to read printed notes, which works with Optical Character Recognition and Text to Speech technology [ 215 ].…”

Section: Speech Recognition For Human-medical Equipment Interactionmentioning

confidence: 99%

See 1 more Smart Citation

Intelligent speech technologies for transcription, disease diagnosis, and medical equipment interactive control in smart hospitals: A review

Zhang

Qiu

et al. 2023

Computers in Biology and Medicine

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“…(a) Robotic wheelchair platform [ 203 ]. (b) Smart glasses prototype [ 204 ]. (c) A user interfaces for the hearing-impaired person [ 205 ].…”

Section: Speech Recognition For Human-medical Equipment Interactionmentioning

confidence: 99%

Section: Speech Recognition For Human-medical Equipment Interactionmentioning

confidence: 99%

Intelligent speech technologies for transcription, disease diagnosis, and medical equipment interactive control in smart hospitals: A review

Zhang

Qiu

et al. 2023

Computers in Biology and Medicine

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“…• The existing methods are not effective to face the issues of learning from imbalanced big data, as they are designed for small-sized datasets. Classification tasks can be more scalable by combining the data with high-performance computing architecture [44][45][46][47]. • In data stream classification, it is not pragmatic to suppose that all data are pre-classified.…”

Section: Related Workmentioning

confidence: 99%

Incremental Learning Framework for Mining Big Data Stream

Eisa¹,

El-Rashidy²,

Alshehri³

et al. 2022

Computers, Materials &Amp; Continua

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At this current time, data stream classification plays a key role in big data analytics due to its enormous growth. Most of the existing classification methods used ensemble learning, which is trustworthy but these methods are not effective to face the issues of learning from imbalanced big data, it also supposes that all data are pre-classified. Another weakness of current methods is that it takes a long evaluation time when the target data stream contains a high number of features. The main objective of this research is to develop a new method for incremental learning based on the proposed ant lion fuzzy-generative adversarial network model. The proposed model is implemented in spark architecture. For each data stream, the class output is computed at slave nodes by training a generative adversarial network with the back propagation error based on fuzzy bound computation. This method overcomes the limitations of existing methods as it can classify data streams that are slightly or completely unlabeled data and providing high scalability and efficiency. The results show that the proposed model outperforms stateof-the-art performance in terms of accuracy (0.861) precision (0.9328) and minimal MSE (0.0416).

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“…However, in developing countries such as China, with limited accessible infrastructure, many blind people struggle to be recognized (Yang, 2021). On the other hand, technological advancements have made people with disabilities more empowered than ever (Almutairi et al, 2020). For instance, voice-activated chatbots allow visually impaired people to control different devices used at home.…”

Section: Introductionmentioning

confidence: 99%

AI and supportive technology experiences of customers with visual impairments in hotel, restaurant, and travel contexts

Liu

Wang

et al. 2023

IJCHM

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Purpose The purpose of this study is to critically reflect on visually impaired customers’ technology assistance needs and the perceptions of existing technologies’ performance in the contexts of hospitality and tourism. Design/methodology/approach Following a qualitative approach, this study used in-depth semistructured interviews with 19 participants with visual impairments. Findings Positive and negative sides of technology-assisted experiences in the hotel, restaurant, and travel domains were summarized, and room for improvement was discussed to enhance the quality of life and travel experience of visually impaired customers. Practical implications Findings from this study offer actionable implications and future directions to technicians and managers to make hospitality and travel experiences more inclusive. Originality/value This timely reflection addresses a critical situation by offering original ideas and calling for more discussion of under-represented groups with visual impairments.

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Development of Smart Healthcare System for Visually Impaired using Speech Recognition

Cited by 5 publications

References 11 publications

Intelligent speech technologies for transcription, disease diagnosis, and medical equipment interactive control in smart hospitals: A review

Intelligent speech technologies for transcription, disease diagnosis, and medical equipment interactive control in smart hospitals: A review

Incremental Learning Framework for Mining Big Data Stream

AI and supportive technology experiences of customers with visual impairments in hotel, restaurant, and travel contexts

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