Rozita Jailani
Universiti Teknologi MARA

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Journal : Indonesian Journal of Electrical Engineering and Computer Science

IoT framework of telerehabilitation system with wearable sensors for diabetes mellitus patients Muhammad Zakwan Abdul Karim; Rozita Jailani; Ruhizan Liza Ahmad Shauri; Norashikin M. Thamrin
Indonesian Journal of Electrical Engineering and Computer Science Vol 31, No 2: August 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v31.i2.pp1023-1031

Abstract

Physical activity is commonly used as a treatment for diabetes patients, although its effectiveness in improving cognitive functions such as learning, thinking, remembering, and decision making is not clear. Regular exercise can gradually improve metabolic abnormalities associated with pre-diabetes and assist patients with type-2 diabetes (T2D) in managing their pharmacological treatment. The usage of mobile health (mHealth) as a tool to help diabetes patients with their diabetes self-management have been demonstrated in previous studies and it can lead to reductions in glycosylated hemoglobin (HbA1c) levels. Heart rate readings during physical activity is beneficial for healthcare professionals (HCP) to ensure appropriate intensity levels for their patients is achieved. Additionally, the list of the tailored physical activities is long, and it is quite challenging for the T2D patients to remember. Therefore, Tele-DM is proposed, consisting of a smartwatch and mobile application that enable remote physiotherapy sessions for T2D patients. The smartwatch transfers the heart rate data to Tele-DM through Google Fit database. The system provides tailored exercise programs to help patients reduce their weight and HbA1c levels. With the ability to facilitate two-way communication between HCP and T2D patients, the Tele-DM system is designed to enable an effective remote rehabilitation process.
A scoping review of artificial intelligence-based robot therapy for children with disabilities Rusnani Yahya; Rozita Jailani; Fazah Akhtar Hanapiah; Nur Khalidah Zakaria
Indonesian Journal of Electrical Engineering and Computer Science Vol 33, No 3: March 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v33.i3.pp1855-1865

Abstract

The integration of artificial intelligence (AI)-based robot therapy (AIBRT) has become prominent in addressing the needs of children with disabilities, including autism spectrum disorder (ASD), attention deficit hyperactivity disorder (ADHD), learning disabilities, and speech delays. However, questions arise regarding the effectiveness of different AI techniques in enhancing therapy for children with specific needs. This review explores current literature on AIBRT for children with disabilities, aiming to understand the efficacy and potential of various AI techniques in improving their therapy. This paper presents a comprehensive search of research articles published from 2019 to September 2023. 39 articles focusing on AI-based robot platforms, the employed treatment or therapy methods, assessment procedures during therapy, and the variables or parameters used to measure intervention effectiveness have been discussed in detail. These AI-based robot platforms have been utilized to engage individuals diagnosed with ASD, offering therapeutic interventions and assessments. In conclusion, the integration of AI and robotics in therapy shows promise for enhancing the development and quality of life for children with disabilities. The findings of this review have implications for therapists, practitioners, and researchers interested in incorporating AI applications into therapy practices. This integration can lead to improved therapy outcomes, optimized children’s development, and enhanced quality of life.