Fall Detection Wristband with Optimized Security and Health Monitoring
المؤلف | Al-Rowaili, Bashaer |
المؤلف | Al-Obaidli, Noor |
المؤلف | Al-Marri, Dana |
المؤلف | Abualsaud, Khalid |
المؤلف | Yaacoub, Elias |
تاريخ الإتاحة | 2024-10-08T07:41:54Z |
تاريخ النشر | 2024-05 |
اسم المنشور | 20th International Wireless Communications and Mobile Computing Conference, IWCMC 2024 |
المعرّف | http://dx.doi.org/10.1109/IWCMC61514.2024.10592481 |
الاقتباس | Al-Rowaili, B., Al-Obaidli, N., Al-Marri, D., Abualsaud, K., & Yaacoub, E. (2024, May). Fall Detection Wristband with Optimized Security and Health Monitoring. In 2024 International Wireless Communications and Mobile Computing (IWCMC) (pp. 697-702). IEEE. |
الترقيم الدولي الموحد للكتاب | 979-835036126-1 |
الملخص | Several people suffer from sudden falls, which puts them seriously at high risk if they do not get help right away. However, if people own a wearable device, they can utilize it to get them help from a nearest hospital whenever they feel tired or suffer from a sudden fall. Elderly people also tend to live alone. After a fall, it is rare for an elderly person to be able to get up or ask for assistance. Therefore, to enable patients to request assistance even in cases where they are unable to get up after a fall, an advanced fall detection system is required, with appropriate hardware and software components. Wireless sensors and Global Positioning System (GPS) gadgets are among the technologies that can be utilized in this regard. While sensors collect information about movement, a GPS device uses information from satellites to pinpoint an object's exact location inside a given space. The goal of this paper is to describe a developed and implemented fall detection wearable wristband with lightweight security for health monitoring. In the event of an emergency, the smartphone application will communicate the user's specific location to the nearest hospital and their emergency contacts. The proposed wristband achieved our goal by developing a system that can communicate with the mobile application. Furthermore, the model testing produced 92% overall accuracy. |
راعي المشروع | This publication was supported by Qatar University grant no. QUCD-IRCC-CENG-24-349. |
اللغة | en |
الناشر | Institute of Electrical and Electronics Engineers Inc. (IEEE) |
الموضوع | ambient assisted living (AAL) diabetes Fall detection smartphone application wearable devices wireless sensors |
النوع | Conference |
الصفحات | 697-702 |
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