Please use this identifier to cite or link to this item:
https://observatorio.fm.usp.br/handle/OPI/56975
Title: | IoT Medical Device Architecture to Estimate Non-invasive Arterial Blood Pressure |
Authors: | MORENO, Ramon; DIAS, Felipe; ARRUDA, Marcelo; OLIVEIRA, Filipe; BULHOES, Thiago; KRIEGER, Jose; GUTIERREZ, Marco |
Citation: | 2022 SYMPOSIUM ON INTERNET OF THINGS, SIOT, 2022 |
Abstract: | High blood pressure (BP) is the leading cause of death worldwide. Besides being a treatable condition, alongside medication and a healthy diet, it requires regular BP measurements to assess whether a patient is properly responding to treatment. There have been many attempts to use the photoplethysmography (PPG) signal to estimate BP continuously, but there has yet to be an effective solution. This work presents our efforts to develop a new method for estimating BP from PPG and infrastructure to collect, process, and store this information. PPG signal is measured from a smartband; our App reads the data from the smartband to a smartphone, processes them using a machine learning method, and estimates BP, which is sent to a server that stores and displays the data |
Appears in Collections: | Comunicações em Eventos - FM/MCP Comunicações em Eventos - HC/InCor Comunicações em Eventos - LIM/13 Comunicações em Eventos - LIM/65 |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
art_DIAS_IoT_Medical_Device_Architecture_to_Estimate_Noninvasive_Arterial_2022.PDF Restricted Access | publishedVersion (English) | 615.5 kB | Adobe PDF | View/Open Request a copy |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.