U-Healthcare Monitoring and Reporting Using Smartphone

U-헬스 케어 모니터링 과 보고 사용스마트 폰

IEEK FALL CONFERENCE 2013

Rajeev Piyare & Seong Ro Lee

Department of Electronics

Mokpo National University

Outline

▪ Motivation

▪ Problem

▪ Implementation Overview

▪ Data Aggregation Process

▪ ECG Processing Algorithms

▪ Mobile Application

▪ Conclusion

Motivation

▪ Chronic diseases are recognized as the leading cause of mortality in the World. According tostatistics [1], among the top 10 leading causes of death in 2009 in South Korea, eight are chronicdiseases, as shown in Table 1.

[1]. Statistics Korea. Causes of Death Statistics in 2009. Available online: http://www.kostat.go.kr

Lack of Quality Healthcare Systems In Developing Countries

▪ Shortage of medical professionals and hospitals

▪ Patients must travel long distances to gain access to healthcare

▪ Patients fail to receive continuous care

▪ Communication issues often arise between the doctor and patients

Rise of Mobile Phones In Underprivileged Regions

▪ 2.2 billion mobile phones in the developing world in contrast to the 11million hospital beds

▪ Mobile phone technology has cheaper, more powerful, and moreaccessible

▪ Mobile network coverage is becoming more widespread

Source: Vodafone Foundation

Adoption of Smart phones for Healthcare Applications

▪ Smart phones can assist health professionals when diagnosing,treating, or monitoring a patient

▪ Minimize patient traveling for health services

▪ Storage and exchange of patient information

▪ Avoid confusion or miscommunication between doctors and patients

Introduction

Continuous MonitoringCertain illnesses/sectors of

population

NEED of Wireless Telemedicine

SOLUTION: M-health

Quality of life1)

Mobility2)

Traditional wired sensors

Implementation Overview - Wireless Health Monitoring System

SPO2

ECG

GPS

InternetInternet

Medical premises

Wifi

2. CENTRAL

CONTROL SYSTEM

Intelligent Node (IN)

(Smart Phone)

Pulse-oximeter

GPS3. CONTROL and MONITORING UNITS

GPRS/

UMTS

1. PATIENT BODY AREA NETWORK

ECG Belt

Internet

Smart phone in charge of collecting

the signals from wireless sensors

and sending them through an hybrid

(GPRS/UMTS/Wifi) system. It also

detects medical alarms (emission of

SMS) and enables remote

programming of sensors

Software for the remote

control and monitoring of the

BAN. Also portable to a smart

phone

In charge of storing biosignals and enabling

remote monitoring from any Internet node

Parameters Monitored

▪ ECG for heart monitoring

▪ Pulse and Oxygen in Blood (SPO2)

▪ Body Temperature

▪ Galvanic Skin Response (GSR)

▪ Airflow (Breathing)

▪ Patient Position (Acc)

▪ Blood Pressure

Figure 3: U-Healthcare Monitoring Sensors

Data Aggregation Process- ECG

▪ To obtain the ECG sensory data accurately from the ECG device, the communication

between the sensor nodes and the ECG device is of primary importance.

Figure 4. Communication between the sensor node and the ECG device.

Data Extraction and Manipulation Process

Figure 5. Data manipulation process

Figure 6. Schematic representation of normal ECG

ECG Processing

▪ To perform precise ECG data analysis on a resource-limited mobile phone at realtime, an accurate and simple technique is required instead of complicatedtechniques which involve more processing memory.

▪ QRS detection algorithm by Tompkins [2] is adopted for the detection of the QRSpeak in the ECG waveform.

▪ Information such as QRS interval time, QT interval time and RR interval time can beobtained from the detection of QRS peaks.

▪ This information is useful for pathophysiological indications of ECG. As an example, ashortened QT interval indicates hypercalcemia where as a prolonged QT intervalindicates hypocalcemia.

[2] Pan, J.; Tompkins, W. A real time QRS detection algorithm. IEEE Trans. Biomed. Eng. 1985, 32, 230-236.

QRS detection and Beat Classification

Figure 7. Overview of the algorithm for heartbeat detection and classification.

Android Mobile Application

Figure 8. Android App Screenshots

Comparison with Previous Work

Project Name Tracked Parameters Communication Tech

KNOWME [2012] Activity Bluetooth

Rofouei et al [2011] Sleep IEEE 802.15.4

MEDISN [2010] ECG, HR, SPO2 IEEE 802.15.4

HealthGear [2006] Microsoft HR, SPO2 Bluetooth

MyHeart [2006] ECG, HR Bluetooth

Fensli et al. [2005] ECG RF at 869.7 MHZ

AMON [2004] Bpr, ECG, HR, SPO2 Cellular Network (GSM)

This Work ECG, HR, SPO2, BPr, GSR,

Airflow, Body Temperature,

Position/Posture

Bluetooth, GSM

Table 2: Comparison of Selected WHMS

Conclusion

▪ Android™ based ubiquitous healthcare system is able to monitor ECG vital signs inreal time.

▪ Other health parameters such as blood pressure, blood oxygen level and bodytemperature are also included in this system, to provide more health informationand a more precise monitoring scheme.

▪ An alarm system has also be included in the system to activate an alarm soundsending warning messages wirelessly to a doctor’s mobile phone when an eventoccurs.

▪ Using GPS capability, the location of the patient is easily tracked if rescue isneeded.