Opinion - (2025) Volume 12, Issue 5
Received: 01-Oct-2025, Manuscript No. bset-26-181403;
Editor assigned: 03-Oct-2025, Pre QC No. P-181403;
Reviewed: 17-Oct-2025, QC No. Q-181403;
Revised: 22-Oct-2025, Manuscript No. R-181403;
Published:
29-Oct-2025
, DOI: 10.37421/2952-8526.2025.12.279
Citation: How to cite this article: Morales, Elena F.. ”Intelligent Systems for Geriatric and Home Healthcare.” J Biomed Syst Emerg Technol 12 (2025):279.
Copyright: © 2025 Morales F .Elena This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution and reproduction in any medium, provided the original author and source are credited.
The burgeoning field of intelligent biomedical systems is revolutionizing healthcare, particularly within the domain of geriatric and home-based care. These advanced systems are instrumental in enhancing patient monitoring capabilities, facilitating the early detection of diseases, and enabling the development of highly personalized treatment plans tailored to the unique needs of the elderly. The overarching aim is to significantly improve the quality of life for older adults, fostering greater independence and autonomy in their daily lives. Technological advancements have paved the way for the integration of wearable sensors and Internet of Things (IoT) devices, offering continuous remote monitoring solutions for elderly individuals. This integration presents both significant challenges and abundant opportunities in the critical areas of data acquisition, transmission, and analysis, ultimately aiming to provide timely interventions and robust support for the effective management of chronic conditions within the home environment. A significant area of focus within this domain is the development of intelligent algorithms specifically designed for fall detection and prevention among older adults. By leveraging machine learning techniques applied to sensor data, these systems can accurately identify fall events and predict potential fall risks, thereby playing a crucial role in enhancing safety and security within home settings. Complementing these monitoring and detection systems are smart home technologies and ambient assisted living solutions, which are designed to comprehensively support the independent living of seniors. These integrated systems offer assistance with a wide array of daily activities, provide timely medication reminders, and generate immediate emergency alerts when needed, ensuring a higher level of safety and support. However, the widespread adoption of intelligent biomedical systems in home healthcare for the elderly is accompanied by critical ethical considerations and privacy concerns. Addressing data security, obtaining informed patient consent, and ensuring algorithmic fairness are paramount to building trust and ensuring the responsible implementation of these technologies. Furthermore, the advancement of telemedicine platforms, significantly enhanced by artificial intelligence, is transforming remote diagnostics and consultations in geriatric care. These AI-powered platforms are instrumental in bridging geographical barriers, thereby improving access to essential and specialized medical services for elderly individuals, regardless of their location. The concept of digital twins is emerging as a powerful tool for personalized health management in the elderly population. By creating a virtual representation of an individual, these digital twins can simulate the potential outcomes of various treatment strategies, allowing for the optimization of care plans and interventions to achieve the best possible health results. Natural Language Processing (NLP) is another key technology being employed to analyze patient narratives and electronic health records. This application of NLP extracts valuable insights that can significantly enhance clinical decision support systems, leading to more informed and effective care strategies for geriatric patients. The integration of robotics with intelligent systems holds immense promise for assisting elderly individuals with mobility challenges and performing daily tasks. Robotic companions and assistive devices have the potential to greatly enhance independence and alleviate the burden often placed on caregivers. Finally, the successful implementation of intelligent systems in home healthcare hinges on a user-centered design approach. Prioritizing usability, accessibility, and patient engagement for older adults is essential for developing effective and intuitive biomedical technologies that truly meet their needs and improve their well-being.
The application of intelligent biomedical systems is gaining traction in geriatric and home healthcare, focusing on improving patient monitoring, early disease detection, and personalized treatment plans for the elderly to enhance their quality of life and independence [1].
The integration of wearable sensors and IoT devices facilitates continuous remote monitoring of elderly individuals, addressing challenges in data acquisition, transmission, and analysis for timely interventions and chronic condition management at home [2].
Machine learning algorithms are being developed for fall detection and prevention in older adults, utilizing sensor data to accurately identify falls and predict risks, thereby improving safety in home environments [3].
Smart home technologies and ambient assisted living solutions play a crucial role in supporting the independent living of seniors by offering assistance with daily activities, medication reminders, and emergency alerts through integrated systems [4].
Ethical considerations and privacy concerns, including data security, patient consent, and algorithmic fairness, are critical aspects that must be carefully addressed during the implementation of AI-powered healthcare systems for the elderly in home settings [5].
Telemedicine platforms, enhanced with AI, are advancing remote diagnostics and consultations in geriatric care, effectively bridging geographical barriers and improving access to specialized medical services for older adults [6].
Digital twins offer a promising avenue for personalized health management in the elderly by creating virtual representations that simulate treatment outcomes and optimize care strategies for improved health results [7].
Natural Language Processing (NLP) is being employed to analyze patient narratives and electronic health records, extracting valuable insights to enhance clinical decision support systems for geriatric medicine [8].
Robotics and intelligent systems are being explored to assist elderly individuals with mobility and daily tasks, with the potential for robotic companions and assistive devices to boost independence and reduce caregiver burden [9].
User-centered design principles are vital for developing intelligent systems in home healthcare, emphasizing usability, accessibility, and patient engagement for older adults to create effective and intuitive biomedical technologies [10].
This collection of research highlights the transformative potential of intelligent biomedical systems in geriatric and home healthcare. Key areas of focus include enhancing patient monitoring through wearable sensors and IoT devices, improving safety with AI-driven fall detection systems, and supporting independent living via smart home technologies. The papers also delve into advanced applications such as AI-powered telemedicine, digital twins for personalized health management, and the use of Natural Language Processing for clinical decision support. Furthermore, the ethical and privacy implications of these technologies are examined, emphasizing the need for responsible implementation. A user-centered design approach is stressed for creating accessible and effective solutions. The integration of robotics is also explored as a means to assist the elderly and reduce caregiver burden. Collectively, these efforts aim to improve the quality of life, independence, and overall well-being of older adults through technological innovation.
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