@article{ref1,
title="Elderly fall detection and prediction system with MEMS sensors and IoT [conference abstract]",
journal="Pratibodh A Journal for Engineering",
year="2023",
author="Editor, Pratibodh-Journal and Kumawat, Yamini and Shekhawat, Yuvraj Singh and Singh, Aditya Kumar and Soni, Yash and Mishra, Mr Jai Prakash",
volume="RACON 2023",
number="",
pages="-",
abstract="This paper presents a patient-specific fall prediction and detection prototype system that utilizes a single tri-axial accelerometer attached to the patients to distinguish between activities of daily living and fall events. Falls in older adults are a major cause of morbidity and mortality and are a key class of preventable injuries. Elderly people often injure themselves from falling more especially when they are living alone. This method will restrict the user movement and produce high false alarm due to frequent swinging and movement of the device. For fall detection, accelerometer and gyroscope was used to detect acceleration and body tilt angle of the faller respectively and is based on microcontroller (Adriano-UNO) and the sensor is MPU6050 Accelerometer and Gyro Chip.<p /> <p>Language: en</p>",
language="en",
issn="2583-4495",
doi="",
url="http://dx.doi.org/"
}