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.