DEEP LEARNING BASED WEARABLE DEVICE FOR OLDER PEOPLE MONITORINGSYSTEM

Abstract

Activity recognition (AR) systems for older people are common in residential health care settings such as hospitals and nursing homes, thus numerous methodologies and studies have been developed to improve the effectiveness of AR systems. However, developing sufficiently robust AR systems using sensor data obtained is a challenging task. In this paper, a novel Smart Belt (S-Belt) for Monitoring of elder people using IoT is a smartphone application that predicts a health monitor for elder people and then sends that status together with the health state and anticipated behaviour to the family. Initially, the sensors in the smart belt such as temperature sensor, heartbeat sensor, oxygen sensor, and glucometer are used to gather data from the elders. The details from the sensors will be preprocessed using Stationary wavelet Transformer (SWT) technique and then classified using Multihead-CNN. Then the classified result will be sent to the end users such as doctors and their relatives through a mobile application. The simulation finding shows proposed method performance was evaluated in terms of ACU, PRE, REC, and F1S. The S-Belt model achieves the overall accuracy of 99.64%. MHCNN network improves the accuracy range by 9.5%, 4.42%, and 0.8% better than DNN, RNN, and CNN respectively.

Authors and Affiliations

C. S. Sabitha and Hari Krishna Kalidindi

Keywords

Related Articles

JARROT BUTTERFLY OPTIMIZED FLAMINGO SEARCH ALGORITHM FOR OPTIMAL ROUTING IN WSN

Wireless sensor networks (WSN) are widely used nowadays, particularly for automated event tracking and monitoring. However, certain issues persist as a result of inadequate cluster formation and CH selection methods, suc...

DETECTION OF VIOLENCE IN FOOTBALL STADIUM THROUGH BIG DATA FRAMEWORK AND DEEP LEARNING APPROACH

Football is the most famous game in the world, with over 4 billion supporters worldwide. Football hooliganism refers to the aggressive or destructive actions of a supporter or player in a stadium while watching or partic...

CLASSIFICATION OF LIVER CANCER VIA DEEP LEARNING BASED DILATED ATTENTION CONVOLUTIONAL NEURAL NETWORK

Liver cancer occur when normal cells develop aberrant DNA alterations and reproduce uncontrollably. Patients with cirrhosis, hepatitis B or C, or both have an increased risk of developing the progressing stage of cancer....

DEEP LEARNING BASED WEARABLE DEVICE FOR OLDER PEOPLE MONITORINGSYSTEM

Activity recognition (AR) systems for older people are common in residential health care settings such as hospitals and nursing homes, thus numerous methodologies and studies have been developed to improve the effectiven...

REAL TIME REMOTE MONITORING VIA HORSE HEAD OPTIMIZATION DEEP LEARNING NETWORK

Over the past few decades, IoT has become indispensable in many industries. More people can now get healthcare and their general health can be improved thanks to recent developments in the healthcare sector. Predictive a...

Download PDF file
  • EP ID EP734437
  • DOI -
  • Views 128
  • Downloads 0

How To Cite

C. S. Sabitha and Hari Krishna Kalidindi (2024). DEEP LEARNING BASED WEARABLE DEVICE FOR OLDER PEOPLE MONITORINGSYSTEM. International Journal of Data Science and Artificial Intelligence, 2(01), -. https://europub.co.uk/articles/-A-734437