Patient Status Monitoring For Smarthome Healthcare
The purpose of this project is to create a patient status monitoring system for smart home healthcare. The suggested setup monitors the patient's vital signs and activity levels using wireless sensors and Wi-Fi technologies. The system gathers information from a variety of sensors, including...
Saved in:
Main Author: | |
---|---|
Format: | Final Year Project Report |
Language: | English English |
Published: |
Universiti Malaysia Sarawak (UNIMAS)
2023
|
Subjects: | |
Online Access: | http://ir.unimas.my/id/eprint/43024/1/Vivian%20Ping%20Thomas%20%2824pgs%29.pdf http://ir.unimas.my/id/eprint/43024/4/Vivian%20Ping%20ft.pdf http://ir.unimas.my/id/eprint/43024/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Universiti Malaysia Sarawak |
Language: | English English |
id |
my.unimas.ir.43024 |
---|---|
record_format |
eprints |
spelling |
my.unimas.ir.430242024-01-04T06:45:57Z http://ir.unimas.my/id/eprint/43024/ Patient Status Monitoring For Smarthome Healthcare Ping, Vivian Thomas T Technology (General) The purpose of this project is to create a patient status monitoring system for smart home healthcare. The suggested setup monitors the patient's vital signs and activity levels using wireless sensors and Wi-Fi technologies. The system gathers information from a variety of sensors, including heart rate, concentration of oxygen level and body temperature. The acquired data is subsequently sent to a cloud server for analysis and processing. The analyzed data are used to deliver real-time information on the patient's health state to caregiver and medical experts, which enables immediate actions and medical attention. The system is designed to be easily integrated into the existing smart home infrastructure and is intended to improve the quality of life and health outcomes of the patient’s population in urban areas. All the objectives have been accomplished. Due to a significant inaccuracy, the outcome is, nevertheless, not very precise. The average percentage of inaccuracy for LM 35 was determined to be 4.43%. Meanwhile for MAX30102, which can detect concentration of oxygen level and heart rate have a percentage error of 0.6% and 9.7%. Universiti Malaysia Sarawak (UNIMAS) 2023 Final Year Project Report NonPeerReviewed text en http://ir.unimas.my/id/eprint/43024/1/Vivian%20Ping%20Thomas%20%2824pgs%29.pdf text en http://ir.unimas.my/id/eprint/43024/4/Vivian%20Ping%20ft.pdf Ping, Vivian Thomas (2023) Patient Status Monitoring For Smarthome Healthcare. [Final Year Project Report] (Unpublished) |
institution |
Universiti Malaysia Sarawak |
building |
Centre for Academic Information Services (CAIS) |
collection |
Institutional Repository |
continent |
Asia |
country |
Malaysia |
content_provider |
Universiti Malaysia Sarawak |
content_source |
UNIMAS Institutional Repository |
url_provider |
http://ir.unimas.my/ |
language |
English English |
topic |
T Technology (General) |
spellingShingle |
T Technology (General) Ping, Vivian Thomas Patient Status Monitoring For Smarthome Healthcare |
description |
The purpose of this project is to create a patient status monitoring system for smart
home healthcare. The suggested setup monitors the patient's vital signs and activity levels
using wireless sensors and Wi-Fi technologies. The system gathers information from a
variety of sensors, including heart rate, concentration of oxygen level and body temperature.
The acquired data is subsequently sent to a cloud server for analysis and processing. The
analyzed data are used to deliver real-time information on the patient's health state to
caregiver and medical experts, which enables immediate actions and medical attention. The
system is designed to be easily integrated into the existing smart home infrastructure and is
intended to improve the quality of life and health outcomes of the patient’s population in
urban areas. All the objectives have been accomplished. Due to a significant inaccuracy, the
outcome is, nevertheless, not very precise. The average percentage of inaccuracy for LM 35
was determined to be 4.43%. Meanwhile for MAX30102, which can detect concentration of
oxygen level and heart rate have a percentage error of 0.6% and 9.7%. |
format |
Final Year Project Report |
author |
Ping, Vivian Thomas |
author_facet |
Ping, Vivian Thomas |
author_sort |
Ping, Vivian Thomas |
title |
Patient Status Monitoring For Smarthome Healthcare |
title_short |
Patient Status Monitoring For Smarthome Healthcare |
title_full |
Patient Status Monitoring For Smarthome Healthcare |
title_fullStr |
Patient Status Monitoring For Smarthome Healthcare |
title_full_unstemmed |
Patient Status Monitoring For Smarthome Healthcare |
title_sort |
patient status monitoring for smarthome healthcare |
publisher |
Universiti Malaysia Sarawak (UNIMAS) |
publishDate |
2023 |
url |
http://ir.unimas.my/id/eprint/43024/1/Vivian%20Ping%20Thomas%20%2824pgs%29.pdf http://ir.unimas.my/id/eprint/43024/4/Vivian%20Ping%20ft.pdf http://ir.unimas.my/id/eprint/43024/ |
_version_ |
1787519571182223360 |