My Undergraduate Thesis Project
Reading heart signal- Transmit to Server - Analyze on Server - Forward analized data to Web and Android Phone.
Heart signal readed using photoplethysmogram (PPG) sensor placed on wrist front. PPG used in the project is a product by Joel and Yury (Pulse Sensor)
The sensor is controlled by an ESP8266-12E, an S.o.C which already has WiFi module embedded on it. The sketch writed using Platform.io ATOM IDE.
The heart rate analyzed to obtain:
- Heart Rate
- Arrhytmhia Classification
The analizing process followed these steps:
- Receive heart signal sampled at 3ms (~300 Hz)
- Start filtering and feature extraction algorithm
Filtering and Feature extraction algorithm described on Pan and Tompkins algorithm. Which band pass (combined of high pass and low pass) filter and Sliding Window thresholding. - Start Classification algorithm
The project use Naive Bayes classifier, trained with UCI-Lab dataset, using features:- QRS duration
- RR Interval
- Age
- Sex
- Forward Heart Rate and Arrhythmia Classification to subscriber
Server run on Node.JS(v6.9.1) using Mongodb(v.3.2.10) as database. The project depedency can be found on project folder.
The result will be forwarded to web and android phone using WebSocket and MQTT respectively.
Copyright 2016 Muhammad Alif Akbar
Telkom University, Informatics Department
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
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http://www.apache.org/licenses/LICENSE-2.0
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