Iris Movement Based Assistance for Catatonic Patients

Bhaskar, A. R.; Shaikh, Rehan; Hartalkar, Aditya; Jacob, Rohan Ninan; Rajput, Manita

doi:10.1109/i2ct.2018.8529370

Cited by 1 publication

(2 citation statements)

References 6 publications

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“…By centering on patient-centric approaches, the implementation of nature-inspired algorithms can contribute to more collaborative and informed healthcare decision-making, ultimately improving patient outcomes and satisfaction in the IoT-based healthcare landscape. 153…”

Section: Patient-centric Approachesmentioning

confidence: 99%

“…Additionally, efforts can be directed towards enhancing the interpretability of algorithmic decisions for patients, fostering better understanding and trust. By centering on patient‐centric approaches, the implementation of nature‐inspired algorithms can contribute to more collaborative and informed healthcare decision‐making, ultimately improving patient outcomes and satisfaction in the IoT‐based healthcare landscape 153 …”

Section: Open Issuesmentioning

confidence: 99%

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The applications of nature‐inspired algorithms in Internet of Things‐based healthcare service: A systematic literature review

Amiri,

Heidari,

Zavvar

et al. 2024

Trans Emerging Tel Tech

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Nature‐inspired algorithms revolve around the intersection of nature‐inspired algorithms and the IoT within the healthcare domain. This domain addresses the emerging trends and potential synergies between nature‐inspired computational approaches and IoT technologies for advancing healthcare services. Our research aims to fill gaps in addressing algorithmic integration challenges, real‐world implementation issues, and the efficacy of nature‐inspired algorithms in IoT‐based healthcare. We provide insights into the practical aspects and limitations of such applications through a systematic literature review. Specifically, we address the need for a comprehensive understanding of the applications of nature‐inspired algorithms in IoT‐based healthcare, identifying gaps such as the lack of standardized evaluation metrics and studies on integration challenges and security considerations. By bridging these gaps, our paper offers insights and directions for future research in this domain, exploring the diverse landscape of nature‐inspired algorithms in healthcare. Our chosen methodology is a Systematic Literature Review (SLR) to investigate related papers rigorously. Categorizing these algorithms into groups such as genetic algorithms, particle swarm optimization, cuckoo algorithms, ant colony optimization, other approaches, and hybrid methods, we employ meticulous classification based on critical criteria. MATLAB emerges as the predominant programming language, constituting 37.9% of cases, showcasing a prevalent choice among researchers. Our evaluation emphasizes adaptability as the paramount parameter, accounting for 18.4% of considerations. By shedding light on attributes, limitations, and potential directions for future research and development, this review aims to contribute to a comprehensive understanding of nature‐inspired algorithms in the dynamic landscape of IoT‐based healthcare services.

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Section: Patient-centric Approachesmentioning

confidence: 99%

Section: Open Issuesmentioning

confidence: 99%