Non-invasive hypertension monitoring in smart furniture

Hypertension is a silent killer as it is difficult to be detected. Daily monitoring blood pressure is a good way for early diagnose hypertension. The common commercial hypertension monitoring device only consists of local data storage and normally equipped with cuff The data from the device is diffi...

Full description

Bibliographic Details
Main Author: Lum, Shirley
Format: Undergraduates Project Papers
Language:English
Published: 2017
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/25928/1/Non-destructive%20testing%20using%20infrared%20image%20for%20the%20measurement%20of%20compressive%20strength%20of%20IBS%20concrete%20panel.pdf
_version_ 1796993561010372608
author Lum, Shirley
author_facet Lum, Shirley
author_sort Lum, Shirley
collection UMP
description Hypertension is a silent killer as it is difficult to be detected. Daily monitoring blood pressure is a good way for early diagnose hypertension. The common commercial hypertension monitoring device only consists of local data storage and normally equipped with cuff The data from the device is difficult to be retrieved automatically and the repetition of pressure inflation during measurement may cause trauma. Recently, application of Internet of Things (loT) with home health monitoring system becomes a trend. This project proposed a cuffless hypertension monitoring, which embedded in the armchair, with a feature of automatically upload the recorded blood pressure and pulse rate readings to a cloud storage. An optical sensor is used to detect the photoplethysmography (PPG) wave from the fingertip of the patient. The raw PPG wave is filtered and amplified. Three parameters are taken from the PPG wave, including, systolic upstroke time (ST), diastolic time (DT), and time taken between systolic peak and diastolic peak (P2P) to estimate systolic blood pressure (SBP), diastolic blood pressure (DBP), and pulse rate (PR). Correlation and linear regression analysis are used to correlate this PPG parameter with blood pressure. The pulse rate is estimated by using the time taken between two successive optimum peaks in PPG wave. The mean difference of estimated SBP and DBP comparing to reference is 3.5909 ± 0.5478 mmHg and 3.6769 ± 0.6095 mmHg respectively. The mean difference of estimated PR comparing to reference is 5.914 ± 0.6970 BPM. The output, SBP, DBP, and PR, is uploaded to a cloud storage, Azure Blob Storage, and presented in Power BI dashboard. By providing cuffless blood pressure and pulse rate measurement and instantaneous upload BP and PR readings to cloud storage, the proposed solution has overcome the problem of common hypertension monitoring device.
first_indexed 2024-03-06T12:35:44Z
format Undergraduates Project Papers
id UMPir25928
institution Universiti Malaysia Pahang
language English
last_indexed 2024-03-06T12:35:44Z
publishDate 2017
record_format dspace
spelling UMPir259282023-10-18T05:55:38Z http://umpir.ump.edu.my/id/eprint/25928/ Non-invasive hypertension monitoring in smart furniture Lum, Shirley TS Manufactures Hypertension is a silent killer as it is difficult to be detected. Daily monitoring blood pressure is a good way for early diagnose hypertension. The common commercial hypertension monitoring device only consists of local data storage and normally equipped with cuff The data from the device is difficult to be retrieved automatically and the repetition of pressure inflation during measurement may cause trauma. Recently, application of Internet of Things (loT) with home health monitoring system becomes a trend. This project proposed a cuffless hypertension monitoring, which embedded in the armchair, with a feature of automatically upload the recorded blood pressure and pulse rate readings to a cloud storage. An optical sensor is used to detect the photoplethysmography (PPG) wave from the fingertip of the patient. The raw PPG wave is filtered and amplified. Three parameters are taken from the PPG wave, including, systolic upstroke time (ST), diastolic time (DT), and time taken between systolic peak and diastolic peak (P2P) to estimate systolic blood pressure (SBP), diastolic blood pressure (DBP), and pulse rate (PR). Correlation and linear regression analysis are used to correlate this PPG parameter with blood pressure. The pulse rate is estimated by using the time taken between two successive optimum peaks in PPG wave. The mean difference of estimated SBP and DBP comparing to reference is 3.5909 ± 0.5478 mmHg and 3.6769 ± 0.6095 mmHg respectively. The mean difference of estimated PR comparing to reference is 5.914 ± 0.6970 BPM. The output, SBP, DBP, and PR, is uploaded to a cloud storage, Azure Blob Storage, and presented in Power BI dashboard. By providing cuffless blood pressure and pulse rate measurement and instantaneous upload BP and PR readings to cloud storage, the proposed solution has overcome the problem of common hypertension monitoring device. 2017-06 Undergraduates Project Papers NonPeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/25928/1/Non-destructive%20testing%20using%20infrared%20image%20for%20the%20measurement%20of%20compressive%20strength%20of%20IBS%20concrete%20panel.pdf Lum, Shirley (2017) Non-invasive hypertension monitoring in smart furniture. Faculty of Manufacturing Engineering, Universiti Malaysia Pahang.
spellingShingle TS Manufactures
Lum, Shirley
Non-invasive hypertension monitoring in smart furniture
title Non-invasive hypertension monitoring in smart furniture
title_full Non-invasive hypertension monitoring in smart furniture
title_fullStr Non-invasive hypertension monitoring in smart furniture
title_full_unstemmed Non-invasive hypertension monitoring in smart furniture
title_short Non-invasive hypertension monitoring in smart furniture
title_sort non invasive hypertension monitoring in smart furniture
topic TS Manufactures
url http://umpir.ump.edu.my/id/eprint/25928/1/Non-destructive%20testing%20using%20infrared%20image%20for%20the%20measurement%20of%20compressive%20strength%20of%20IBS%20concrete%20panel.pdf
work_keys_str_mv AT lumshirley noninvasivehypertensionmonitoringinsmartfurniture