Intelligent Alarm System for Physically Disabled People: Design and a Pilot Study

Fakher Rahim^*

Department of Bioinformatics, Health Research Institute, Research Center of Thalassemia and Hemoglobinopathies, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran

*Corresponding Author: Fakher Rahim
Department of Bioinformatics, Health Research Institute, Research Center of Thalassemia and Hemoglobinopathies, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
Tel: +986133367652
E-mail: Bioinfo2003@gmail.com

Received: August 17, 2020 Accepted: October 21, 2020 Published: October 28, 2020

Citation: Rahim F (2020) Intelligent Alarm System for Physically Disabled People: Design and a Pilot Study. J Trauma Stress Disor Treat 9:5.. doi: 10.37532/jtsdt.2020.9(5).210

Today, as medical science is developing and progressing, it is essential to use technology in prevention, control, and treatment. Clearly, falling is one of the most serious concerns of the elderly and those with various disabilities. In this paper, we introduce a new low-cost fall detection system with a highly portable sensor for physically disabled people. We recruited 15 patients with physical disabilities of which data were acquired. Data of 22 falling events; altogether, 19 falling events were submitted for analysis. The rest of the events were rejected because of the age restriction inclusion criteria. Findings have confirmed the helpfulness and usefulness of the method to process the proposed model properly and detect, track, and classify physically disabled people as moving objects. To solve the fall detection problem, many devices using the inertial sensors have been introduced so far, which differ in the placement, sensors, and approach. This system has the ability to provide a weekly and monthly daily report to a doctor. Data stored as a graph on the app itself or on the paper output, or in the case of physician collaboration, will be displayed online on the doctor’s website. Our findings demonstrate the rational performance of the suggested fall detection system in the tested situations.