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Search Results (8)
  • Open Access

    ARTICLE

    Parameter-Tuned Deep Learning-Enabled Activity Recognition for Disabled People

    Mesfer Al Duhayyim*

    CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 6287-6303, 2023, DOI:10.32604/cmc.2023.033045 - 29 April 2023

    Abstract Elderly or disabled people can be supported by a human activity recognition (HAR) system that monitors their activity intervenes and patterns in case of changes in their behaviors or critical events have occurred. An automated HAR could assist these persons to have a more independent life. Providing appropriate and accurate data regarding the activity is the most crucial computation task in the activity recognition system. With the fast development of neural networks, computing, and machine learning algorithms, HAR system based on wearable sensors has gained popularity in several areas, such as medical services, smart homes,… More >

  • Open Access

    ARTICLE

    Deep Transfer Learning-Enabled Activity Identification and Fall Detection for Disabled People

    Majdy M. Eltahir1, Adil Yousif2, Fadwa Alrowais3, Mohamed K. Nour4, Radwa Marzouk5, Hatim Dafaalla6, Asma Abbas Hassan Elnour6, Amira Sayed A. Aziz7, Manar Ahmed Hamza8,*

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3239-3255, 2023, DOI:10.32604/cmc.2023.034037 - 31 March 2023

    Abstract The human motion data collected using wearables like smartwatches can be used for activity recognition and emergency event detection. This is especially applicable in the case of elderly or disabled people who live self-reliantly in their homes. These sensors produce a huge volume of physical activity data that necessitates real-time recognition, especially during emergencies. Falling is one of the most important problems confronted by older people and people with movement disabilities. Numerous previous techniques were introduced and a few used webcam to monitor the activity of elderly or disabled people. But, the costs incurred upon… More >

  • Open Access

    ARTICLE

    Hand Gesture Recognition for Disabled People Using Bayesian Optimization with Transfer Learning

    Fadwa Alrowais1, Radwa Marzouk2,3, Fahd N. Al-Wesabi4,*, Anwer Mustafa Hilal5

    Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 3325-3342, 2023, DOI:10.32604/iasc.2023.036354 - 15 March 2023

    Abstract Sign language recognition can be treated as one of the efficient solutions for disabled people to communicate with others. It helps them to convey the required data by the use of sign language with no issues. The latest developments in computer vision and image processing techniques can be accurately utilized for the sign recognition process by disabled people. American Sign Language (ASL) detection was challenging because of the enhancing intraclass similarity and higher complexity. This article develops a new Bayesian Optimization with Deep Learning-Driven Hand Gesture Recognition Based Sign Language Communication (BODL-HGRSLC) for Disabled People.… More >

  • Open Access

    ARTICLE

    Automated Disabled People Fall Detection Using Cuckoo Search with Mobile Networks

    Mesfer Al Duhayyim*

    Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 2473-2489, 2023, DOI:10.32604/iasc.2023.033585 - 15 March 2023

    Abstract Falls are the most common concern among older adults or disabled people who use scooters and wheelchairs. The early detection of disabled persons’ falls is required to increase the living rate of an individual or provide support to them whenever required. In recent times, the arrival of the Internet of Things (IoT), smartphones, Artificial Intelligence (AI), wearables and so on make it easy to design fall detection mechanisms for smart homecare. The current study develops an Automated Disabled People Fall Detection using Cuckoo Search Optimization with Mobile Networks (ADPFD-CSOMN) model. The proposed model’s major aim… More >

  • Open Access

    ARTICLE

    Enhanced Adaptive Brain-Computer Interface Approach for Intelligent Assistance to Disabled Peoples

    Ali Usman1, Javed Ferzund1, Ahmad Shaf1, Muhammad Aamir1, Samar Alqhtani2,*, Khlood M. Mehdar3, Hanan Talal Halawani4, Hassan A. Alshamrani5, Abdullah A. Asiri5, Muhammad Irfan6

    Computer Systems Science and Engineering, Vol.46, No.2, pp. 1355-1369, 2023, DOI:10.32604/csse.2023.034682 - 09 February 2023

    Abstract Assistive devices for disabled people with the help of Brain-Computer Interaction (BCI) technology are becoming vital bio-medical engineering. People with physical disabilities need some assistive devices to perform their daily tasks. In these devices, higher latency factors need to be addressed appropriately. Therefore, the main goal of this research is to implement a real-time BCI architecture with minimum latency for command actuation. The proposed architecture is capable to communicate between different modules of the system by adopting an automotive, intelligent data processing and classification approach. Neuro-sky mind wave device has been used to transfer the… More >

  • Open Access

    ARTICLE

    Deep Learning-Based Sign Language Recognition for Hearing and Speaking Impaired People

    Mrim M. Alnfiai*

    Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 1653-1669, 2023, DOI:10.32604/iasc.2023.033577 - 05 January 2023

    Abstract Sign language is mainly utilized in communication with people who have hearing disabilities. Sign language is used to communicate with people having developmental impairments who have some or no interaction skills. The interaction via Sign language becomes a fruitful means of communication for hearing and speech impaired persons. A Hand gesture recognition system finds helpful for deaf and dumb people by making use of human computer interface (HCI) and convolutional neural networks (CNN) for identifying the static indications of Indian Sign Language (ISL). This study introduces a shark smell optimization with deep learning based automated… More >

  • Open Access

    ARTICLE

    A Smart Room to Promote Autonomy of Disabled People due to Stroke

    Moeiz Miraoui1,2,*

    Computer Systems Science and Engineering, Vol.44, No.1, pp. 677-692, 2023, DOI:10.32604/csse.2023.025799 - 01 June 2022

    Abstract A cerebral vascular accident, known as common language stroke, is one of the main causes of mortality and remains the primary cause of acquired disabilities in adults. Those disabled people spend most of their time at home in their living rooms. In most cases, appliances of a living room (TV, light, cooler/heater, window blinds, etc.) are generally controlled by direct manipulation of a set of remote controls. Handling many remote controls can be disturbing and inappropriate for these people. In addition, in many cases these people could be alone at home and must open the… More >

  • Open Access

    ARTICLE

    Sign Language Recognition and Classification Model to Enhance Quality of Disabled People

    Fadwa Alrowais1, Saud S. Alotaibi2, Sami Dhahbi3,4, Radwa Marzouk5, Abdullah Mohamed6, Anwer Mustafa Hilal7,*

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3419-3432, 2022, DOI:10.32604/cmc.2022.029438 - 16 June 2022

    Abstract Sign language recognition can be considered as an effective solution for disabled people to communicate with others. It helps them in conveying the intended information using sign languages without any challenges. Recent advancements in computer vision and image processing techniques can be leveraged to detect and classify the signs used by disabled people in an effective manner. Metaheuristic optimization algorithms can be designed in a manner such that it fine tunes the hyper parameters, used in Deep Learning (DL) models as the latter considerably impacts the classification results. With this motivation, the current study designs… More >

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