The Wireless Monitoring Of Vital Signs

Advances in electronics, telecommunications, information technology, specifically in mobile solutions, have enabled the development of numerous devices and applications into the field of medicine, achieving greater coverage and therefore and improvement in the provision health services. The wireless monitoring of vital signs is a topic of great interest to academic, industrial and medical community.
The main objective is to provide timely services to patients in and out health centers. In addition to the global trend of information and communication technology is to allow users to access any kind of information of real world in real time. Medicine is not the exception to this trend and, in this field, the promptness of the information means to save lives and prevent morbidity. Electrocardiogram (ECG) is a diagnostic tool that allows lifesaving decisions, as in coronary thrombolytic case, whose diagnosis should be done in less than six hours of onset of symptoms.
This therapeutic approach is able to save myocardial issue functions and subsequent course and to save the life of a patient. To make this type of life-saving decisions it is indispensable to include in health care systems, special devices capable to detect ECG signals and send them where qualified medical staff can provide further assistance about decisions to be made on the patient served. Other physiological signals such as blood pressure and body temperature are also of great interest and provide additional information in diagnosis. Different prototypes of remote monitoring systems have been proposed and developed in recent years, which have evolved continuously from systems using FM radio transmitters to those using Bluetooth technology. Similarly visualizing devices such as PDA or mobile devices.
They describe the development of a system for measuring three types of physiological signals, including phonocardiogram's, electrocardiograms and body temperature measurements, using PDA's and Bluetooth technology, whose purpose is to reduce service costs and increase efficiency in health care systems. In a system that measures and real time processing ECG signals and transmits them via Bluetooth to a PDA is presented.
All bio-signals data are stored and automatically analyzed by neural network. System can evaluate presence of critical values which could be the sign of worse medical condition of a patient. In, Lee Y. presents a prototype for non invasive monitoring of cardiac sounds in real time using a FM transmitter-Receiver module and a personal computer. In a wireless system for patient monitoring is purposed. The developed prototype sends ECG signals to a personal computer with Bluetooth signal receiver. In a wireless ECG plaster prototype device is purposed, which can be used for real time monitoring of ECG in cardiac patients.
The system includes two parts, a wireless ECG acquisition plaster and a personal waterway (remote station). The ECG plaster contains a custom designed ECG front-end chip, a microcontroller, and a Zigbee transceiver. The plaster records the ECG and wireless transfers the data a remote data center. In this paper, a remote monitoring system capable of reading ECG and temperature signals is purposed. The elements and the devices used to capture and conditioning of the signals have a low-cost, and the software for the development application may be freely distributed. Besides, according to a recent insight into the mobile market made by the analytics firms Nielsen and comScore almost 50% of smart phones owners in the U.S prefer Android Operating System.

During the first quarter of the present year, the total market was led by Android, followed by IOS with a 32% and RIM with an 11%. Also, an earlier study made by comSoc revealed the world trend of mobile owners, showing that smart phone use is being increased compared to other options. The information was sent via Bluetooth to a display module that could be a personal computer (PC) or a mobile phone. The captured information is sent via GPRS or Wi-Fi, to an implemented database working on a web server for storage and later reference if needed.
A web application (servlet) allows accessing data from any device with internet connectivity. There are several error sources in the capture of the ECG signal, like artifacts which cause problems in interpretation and therefore error in diagnosis. Others like mechanical error sources can even simulate arrhythmias; and excessive movement can cause false readings and appearances of outdated ST segments. Non invasive procedures to obtain physiological signals have become increasingly necessary and make the current trend in medical practice, due to the convenience of implementation.

2.1. Real time monitoring of patients using bio-signals through embedded computer
The embedded computer system based on the telecommunication technology and computer multimedia technology is useful for multipurpose health care monitoring. Telemedicine system usually contains tele-diagnosing, tele-monitoring, tele-education, long-range medicine information service. Since some diseases break out accidentally, such as heart disease, time is critical for doctor in the acute treatment of heart attack or sudden cardiac death. In emergency cases the immediate medical treatment is vital, and recent studies conclude that early and specialized hospital patient management contributes to the patient's survival.
It is impossible for a doctor to spend all of his time in treating one patient with heart disease. Recent studies show that the number of patients being managed at home is increasing, which can part of the high hospitalization's cost and increase patient's comfort. With the increasing development of communication technology, internet and GPRS have played an important role in people's lives. The embedded computer system with powerful processing ability and low power consumption makes it widely used in many mobile fields and has a great impact on people's lives. It is a good choice to use embedded system for telemedicine system.
In many cases, embedded system can work well and replace traditional industry computer with less volume, lower price and lower power consumption. In telemedicine system, the embedded computer system can exert its powerful abilities of real time monitoring and network communication, and it can also analyze and diagnose the patient's health information in time and send the information to monitoring center via internet or GPRS. According to telemetry information, doctors know the patient's health circumstances at all times and the patient's needn't to stay in hospital any longer. So it is worthwhile to investigate in its possible use in telemedicine system. This telemedicine system contains two major parts: telemedicine terminal and telemedicine center. The hardware of telemedicine terminal mainly consists of multi-biomedical signal sampling circuit, GPRS module, and the embedded computer system, and its software mainly includes customized embedded Linux operating system and its application software.
The ECG sampling circuit always contains ECG signal acquisition and amplification, baseline-drift circuit, 0.03Hz high-pass circuit, 50Hz-bandstop circuit and 100Hz low-pass circuit. Through these necessary signal processing circuits, the primary ECG signal can be obtained and converted the analog ECG Signal into digital signal. Digital filter can be used to process the signal in embedded computer. In this way the standard ECG signal can be obtained. As for the detection of blood pressure signal. MPX5050GP pressure sensor is used to detect BP signal.
The air pump controlled by MCU pumps the bandage with air and then the MCU well regulates the bleed value to release the air. MPX5050GP pressure sensor is used to detect the air pressure inside the bandage and it can get the primary blood pressure signal, that needs to be filtered by the necessary analog circuit to remove the noise, and the prototype of blood pressure signal is obtained. The prototype of blood pressure signal is converted into digital signal, and the embedded computer can process and calculate the signal with the arithmetic of oscillate graph to get the value of the patient's blood pressure.

2.2. Real time monitoring of ECG signal using PIC and web server:
In most of the instances, the cause for prolonged stay of patient in the hospital is not that the patient in reality needs proper medical attention. The reason for a patient to be hospitalized is for continuous monitoring especially in case of aged people. In recent years, hospital expenditures have increased dramatically. So, for those patients who need to be under observation shouldn't necessarily stay in the hospital and by doing so more space will be available for those who needs immediate medical care. So, for this several attempts have been made and the focus is on how to provide preventive care outside the hospital. Presently, there are some wireless monitoring setups which have been designed.
These mostly employ a PC or a mobile phone. The ECG is the cost of a PC, availability and the delay which occurs for truning on PC in order to transmit data and mostly aged people are not very comfortable using a PC especially if they are already under continuous care for a treatment. Most of the existent methodologies carry the signals to the base station through an analog link causing the degradation of signal while transmitting.

The system described here can reduce the unnecessary stay in hospital for the sick patients who had to stay longer in hospitals owing to serious health issues but now they need only regular monitoring for knowing the after effects of medication. This system presents a methodology where a group of sensor nodes placed near the heart will continuously monitor the parameters and signals are transmitted to the base station. For instance if a patient has earlier got a heart attack then he is likely to have another one. To avoid this, the person to be monitored has to put ECG. Measuring electrodes which will monitor the heart behavior. Then, the analog signals are digitized and sent to the access point present in the home.
This wireless access point is then connected to the hospital server which regularly monitors the ECG. On the hospital side, ECG viewer software generates the ECG graph which tells about patient's condition and if any irregularity is there then the doctor can take necessary steps by contacting the patient or send an ambulance to the patient's home. GAO suggests a network made of sensors in urgent situation. The ECG signals are recorded and sent through 802.15.4 standard to a laptop for analyzing.Fensli suggested using PDA to store ECG signals. Then, the recorded data will be transmitted to a remote location using GPRS. Jun suggested recording the data from ECG detector and then transmitting it to PC via Bluetooth. Khoor suggested an online monitoring system but failed to provide the design aspects. Coosemans suggested a monitoring system fitted in garment which can be extended up to a distance of 18cm.
The suggested system provides benefits for those patients who wish to enjoy their normal routine life and for doctors who wish to distantly monitor their patients without unnecessarily staying in hospital and thus eliminating PC for data transfer from patient side to hospital side. Today, medical practitioners and hospital require a structured and dependable wireless observation system to monitor the real time ECG signal from patients who are staying outside hospital with maximum accuracy.

2.3. Remote monitoring of heart sounds in real time:
Heart sound can be heard from the chest through a stethoscope a device commonly used for screening and diagnosis in primary health care. The art of evaluating the acoustic properties of heart sounds and murmurs, including the intensity, frequency, duration, number, and quality of the sounds, are known as cardiac auscultation.
Phonocardiography is the study of heart sounds, consists of several different components, the first and second heart sounds are the most significant ones. There are still other events, nevertheless, that may be recorded, including the third and forth heart sounds heart murmur and noise, most of the stethoscopes were acoustic in nature with very less sound amplification of advent technology the transition took place into electronic and the more powerful digital electronic stethoscopes. The acoustic and the electronic and the more powerful digital electronic stethoscopes. The acoustic and the electronic stethoscopes are widely prevalent in the current market. A fewer number of companies produce stethoscopes each with their unique features.
The PCG-based Heart Rate (HR) measurement is carried out using the detection of cardiac pulse peaks. These algorithms assume a general heart sound model. With a basic normalization, Shannon energy and thresholding on PCG, S1 and S2 are detected, extracted and counted to derive the HR. PCG segmentation techniques that analyze heart sound features are also introduced to make the detection more robust. But by calculating the Shannon energy, and also by the segmentation of S1 and S2 s, it becomes complicated to find HR. This paper presents an algorithm not only for the direct measurement of heart rate based on PCG but also for the remote monitoring of these signals.
Wavelet transform is adopted for PCG time-series processing. Mother wavelet, Daubechies family is used to filter out the added noise from the heart sound signal. Then by taking the square of the filtered heart sound signal peaks are directly detected and then the heart rate. Hence the processing makes easy. However, since heart sounds vary in a great extent, this method effectively deal with unexpected PCG patterns that differ from the presumed model. More importantly the saved data on the server can be accessed anytime from anywhere for the reference or for the expert advice. A module which acquires the heart sounds and processed them to get the phonocardiogram and heart rate has been developed and this cans tele-monitor PCG.
A general physician can interact with the module and get quick preliminary diagnosis of heart problems of patients who cannot be easily shifted to advanced hospitals which are at a distance and also who cannot afford high consultation fee and traveling cost. The Module has a provision of extracting information at the end of every step instead of working as a black box to the user. Such module will be a step towards the development of efficient medical care. It will overcome the deficiency of expert cardiologist in both urban and rural areas.
2.4. A Low-Cost, Portable, High-Throughput Wireless Sensor System for Phonocardiography Applications
The emerging Wireless Sensor Network technologies have begun to advance the monitoring and control of many complexes, real-world systems, such as in structural and mechanical environmental, healthcare, and military applications. A WSN consists of multiple small, foot-print wireless devices called 'sensor nodes,' each of which is typically composed of a radio (RF) transceiver, microcontroller, memory unit, and battery. WSN technologies using Zigbee protocol (IEEE 802.15.4) allow sensor nodes to collect data by using low-cost microcontrollers and Radio Frequency (RF) transceivers. Some of the lightweight Zigbee WSN platforms include Mica2, MicaZ, TelosB for low-end, and Yale's XYZ and Intel's IMote2 for high performance applications pertinently, the WSN technologies offer significant potential to transform healthcare monitoring practice.
WSN allows medical professionals to remotely track and monitor a patient's physiological signals, such as blood pressure, heart rate, ECG, and heart sound, continuously over an extended period of time. Especially in the case of critical-care patients who require a round-the-clock monitoring system, WSN devices allow medical doctors to detect abnormal signals in a timely manner. WSN devices also enable patients to have greater freedom of movement and less discomfiture compared to traditional wired devices. Additionally, WSN devices may ultimately be used by patients for self-diagnosis. According to the British Medical Bulletin , cardiovascular diseases are the leading cause of death globally.
Significant efforts have been made to address the diagnostics of various cardiovascular disorders using a variety of sensors, including electrocardiography (ECG), magnetic resonance imaging (MRI), and phonocardiography (PCG).In particular, PCG is a common method for a physician or medical doctor to analyze a patient's heart. PCG techniques use heart sound signals collected from a highly sensitive microphone for heart condition monitoring. A PCG sensor offers certain advantages over other physiological sensors, including ECG and MRI, because acoustic monitoring of a heart condition using PCG is harmless and nonintrusive, the setup is lightweight, and a relatively low level of experience and skill is needed to set up the system and acquire the signals.

The PCG recording also requires only a single probe and does not use wires, the time required to set up PCG recording is shorter, compared to ECG and MRI. More importantly, PCG offers the ability to quantitate the sounds made by the heart providing information not readily available from more sophisticated tests. The ECG, which reveals the electrical activity of the heart, is used to detect heart abnormalities by drawing a graph of the electrical impulses moving through the heart. Although acquisition of ECG is noninvasive and painless, and the ECG signals provide useful information of the electrical activity of the heart, these signals do not always permit an accurate diagnosis due to multiple factors affecting electrical activity of the heart.
This method also requires relatively high level of experience and skill to set up the system and perform an analysis. Hence, ECG and MRI are not normally used unless a problem has been previously detected by PCG or auscultation. Although, a PCG sensor offers certain advantages over other physiological sensors, heart sounds collected using PCG usually include undesirable noises from other parts of the body and also from the surrounding environment. To address this issue, many techniques have been developed to remove undesirable noises from heart sounds collected using PCG.
2.5. Electrocardiogram (EKG) Data Acquisition and Wireless Transmission
An EKG is a measurement of the electrical activity of the heart (cardiac) muscle as obtained from the surface of the skin. As the heart performs its function of pumping blood through the circulatory system, the result of the action potentials responsible for the mechanical events within the heart is the generation of a certain sequence of electrical events. The electrical impulses within the heart act as a source of voltage, which generates a current flow in the torso and corresponding potentials on the skin. The potential distribution can be modeled as if the heart were a time-varying electric dipole. If two leads are connected between two points on the body (forming a vector between them), electrical voltage observed between the two electrodes is given by the dot product of the two vectors.

An accurate indication of the frontal projection of the cardiac vector can be provided by three leads/electrodes, one connected at each of the three vertices of the Einthoven triangle. Generally, as many as twelve leads are used to monitor cardiac signals. The development of EKG acquisition hardware has impacted the progression of research in electrophysiology. The goal of the work reported in this paper was to build a system to benefit and facilitate related telemedicine projects in our laboratory.
The following subsections are synopsis of the noise-reduction techniques used in the construction of the signal acquisition hardware, a brief mention of the software we designed for signal analysis, visualization, and diagnosis of EKG-related health issues, and communication technologies designed and developed for signal transmission. Work is currently ongoing for improving aspects of the system in both hardware and software activities. Wireless transmission of digitized signals was accomplished using 802.11b protocol at the lower level. The application level protocol was developed to allow for flawless communication among various chipsets involved in the system including the PC software. When the ADC conversion cycles produced data for the 10-second period, the ADC was halted to avoid any over-writing of the buffered data.
The serial port was activated on the ADuC831 to transfer the data onto the IP??8930'. Once the data, which was divided into 32-byte packets to follow the IP??8930' MCU interface protocol, was fully transferred, the ADuC831 reset one of the ports (Port 2 in current setup) of the IP??8930' general purpose I/O ports. The PC side software continuously polled to check if the Port 2 of the IP??8930' was set. When the port was set, it started reading data using ICP from the IP??8930'.

2.6. Wireless Body Area Networks for Healthcare-A Survey:
The increase in average lifespan and health cost in many developed nations are catalysts to innovation in health care. These factors along with the advances in miniaturization of electronic devices, sensing, battery and wireless communication technologies have led to the development of Wireless Body Area Networks (WBANs). WBANs consist of smart miniaturized devices (motes) that are able to sense, process and communicate. They are designed such that they can be worn or implanted, and monitor physiological signals and transmit these to specialized medical servers without much interference to the daily routine of the patient industry. By doing this we hope to stimulate more research in the area by identifying open research issues. In section II we survey monitoring and sensing in WBANs.
A pulse oximeter is a medical device that indirectly measures the oxygen saturation levels (SpO2) in an individual's blood as well as the changes in blood volume in the skin that coincide with the cardiac cycle. Typically, a pulse oximeter is attached to a finger or an earlobe, and it consists of red and infra-red light-emitting diodes (LEDs) and a photo detector.
The photo detector measures the amount of red and infra-red light that is transmitted through or effected by the body part, which is partially dependent on the amount of light absorbed by the blood that perfuse the body part. The relative absorption of red and infra-red light by the blood is related to the ratio oxygenated hemoglobin to deoxygenated hemoglobin, and this serves as the basis of the SpO2 measurement.
The overall amount of light absorption varies as the pulsatile volume of blood within the body part changes with time. This quasi-periodic signal is called a photoplethysmograph (PPG), and can be used to determine heart-rate. A wearable PPG biosensor in the form of a ring has been developed by Yang and Rhee. As an article of clothing, a ring is more likely to be worn continuously, making it suitable for continuous monitoring applications. Asada et. al. have further refined the design of the ring sensor to ensure that the PPG signal output is more resistant to noise components due to motion artifacts and changes in ambient light levels . Also, they have sought to reduce power consumption by using a high frequency, low duty cycle modulation scheme. Shnayder, et al. have designed a pulse oximeter that integrates a BCI micro power oximeter wireless sensor platform.
This pulse oximeter serves as a node in a medical sensor network platform developed by a research group at Harvard University called Code Blue .An liker et. al. have also designed a pulse oximeter sensor as a part of their wearable multiparameter medical monitoring and alert system called AMON(Advanced care and alert portable telemedical Monitor).The pulse oximeter sensor is integrated into a single wearable wrist device with the other sensor components of this system. Although WBANs have been developed for medical applications, they can be easily tailored for smart environments that combine sectors such as business, entertainment and education for a heightened seamless experience. The recent explosion of personal computing devices into the consumer market that combine social networking applications can be boosted with the introduction of WBANs without active involvement of the individual at the center of the networks. This kind of passive involvement in data transfer can ease the cognitive burden on the individual and result in more unobtrusive computing applications. It also has the potential for breakthroughs in the study of medicine, ecology and other civilian and military applications.

2.7. An ECG Patch Combining a Customized Ultra-Low-Power ECG SoC with Bluetooth Low Energy for Long Term Ambulatory Monitoring
It is foreseen that healthcare system and services will radically change in the near future. Small and low power sensors able to monitor vital signs and activity patterns can provide a great opportunity in shifting to a new patient centric paradigm, characterized by the delocalization of care from hospitals to home, and a focus on prevention and just-in-time intervention. Cardiac disease is the leading cause of death in the U.S. and it is well established that early detection is critical for survival. Wearable sensors play a key role in continuous chronic disease monitoring during a person's daily life, allowing for both just-in-time interventions and more accurate diagnosis. The emphasis on individual health and well-being recently increased, triggering the development of many products and research prototypes targeting this field.
The first group often employs ultra-low power radios and protocols in order to save power, together with general purpose microcontrollers, lacking wear ability, standardization, ease of use, and ultra low power processors for on board signal processing (DSPs) . In the latter group, some systems offer reliable, easy to use sensors, equipped with Bluetooth (BT) radios that allow plug and play functionalities with mobile phones and PCs. The trade-off this time is on power consumption, since these systems can last for only a few hours, in fact limiting significantly practical application and usefulness of the devices for long term monitoring.
In this paper, we report an ECG patch based on the combination of an ultra-low power ECG SoC, and Bluetooth Low Energy, overcoming the lack of wear ability, standardization or lifetime of previous systems. In this paper we presented a demonstrator of a personal health monitor using Bluetooth Low Energy and a customized ultra-low power ECG SoC. Such a system provides connection to PCs and mobile phones through a standard protocol, and maintains very low power consumption for long-term monitoring in the home environment, closing the gap between research prototypes and commercial products. Other operation modes including real-time artifact reduction, arrhythmia detection and ECG streaming are currently under development.

2.8. Enabling Technologies for Wireless Body Area Networks: A Survey and Outlook
A wireless body area network (WBAN) is a radio frequency (RF)-based wireless networking technology that interconnects tiny nodes with sensor or actuator capabilities in, on, or around a human body. Typically, the transmissions of these nodes cover a short range of about 2 m. Complementing wireless personal area networks (WPANs),1 in which radio coverage is usually about 10 m, WBANs target diverse applications including healthcare, athletic training, workplace safety, consumer electronics, secure authentication, and safeguarding of uniformed personnel. A WBAN can also be connected to local and wide area networks by various wired and wireless communication technologies, WBANs will play an important role in enabling ubiquitous communications, creating a huge potential market.
In the area of healthcare, according to the World Health Organization's statistics, millions of people suffer from obesity or chronic diseases every day, while the aging population is becoming a significant problem. Both the current situation and future trend call for new technologies such as WBANs to facilitate first-hand health monitoring and medical care (point of care). From the consumer electronics perspective, short-range wireless technologies for human-computer interaction (HCI) and entertainment are booming. Take Bluetooth Low Energy technology as an example; a recent report predicts the initial market volume of those ultra-low-power products to be in the billions.
Unlike conventional wireless sensor networks (WSNs), WBANs have their own characteristics, as discussed below, which distinguish them from WSNs and also create new technical challenges. Architecture: A WBAN consists of two categories of nodes: sensors/actuators in or on a human body, and router nodes around WBAN wearers or second-tier radio devices equipped on the wearers, functioning as an infrastructure functions as a sensor node as well as a router node. Density: The number of sensors/actuators deployed on the wearer depends on use cases. Typically, they are not deployed with high redundancy to tolerate node failures as in conventional WSNs, and thus do not require high node density. Data rate: Most WSNs are applied for event based monitoring, where events can happen irregularly. In contrast, WBANs are employed for monitoring human physiological activities, which vary in a more periodic manner.
As a result, the application data streams exhibit relatively stable rates. Typical WBAN sensors are summarized later. Latency: For both healthcare and consumer applications, latency resulting from the underlying network such as a WBAN should be minimized. While power saving is definitely beneficial, replacement of batteries in WBAN nodes is much easier than in WSNs, in which nodes may be physically unreachable after deployment. Therefore, it may be necessary to maximize battery life in a WSN at the expense of higher latency. Mobility: Wearers of WBANs may move around. WBAN nodes affiliated with the same wearer move together and in the same direction. In contrast, WSN nodes are usually considered to be stationary, and any node mobility does not occur in groups.

2.9. The Heart Spy: on-line GPRS mobile long-term ECG monitoring with internet based decision support system
An internet information system was developed for the on-line analysis of real-time mobile GPRS extended length ambulatory ECG registrations. The individual cardiovascular risk would be calculated by various methods, the aim of our study was to predict the outcome of severe chronic heart failure (CHF) patients by nonlinear beat-to-beat long term ambulatory ECG data analysis. The authors follow their works in the telemedicine field with wireless ECG. For long term risk management the actual short (minutes to hours) time-series are compared to the previous (days) data and the system 'remembers' the signs which shift to the (more) pathological state (e.g. loss of complexity).
The time-stamping of the patient observed signs and symptoms makes possible to recalculate or re-confirm the ECG data in the actual period. In the default option the rhythm analysis (normal, atrial fibrillation, or flutter, ventricular arrhythmias), the non-linear heartbeat analysis (quantitative and qualitative measurements of Poincare (R-R_0 vs. R-R_1) plots, detrended fluctuation analysis (DFA)), and approximate entropy (ApEn) calculations were performed . New methods would be also easily implemented, for example the DFA analysis with alpha-beta filter. Using the alpha-beta filter a local least-squares fitting for tracking the evolution of the gradient as a function of log time scales (the scaling exponent of the average root-mean-squared fluctuations as a function of time scales) recursively could be estimated.

In this way the DFA should not reduce to quantify only two (short- and long-term range) scaling exponents. The non-linear heartbeat a alysis the detrended fluctuation analysis (DFA), and approximate entropy (ApEn) calculations, and the quantitative and qualitative measurements of Poincare (R-R_0 vs. R-R_1) plots were chosen. The comet-shaped pattern (typical for healthy people) is characterized with a wide range of R-R intervals, extending 500-1000 msec along both axis, and as R-R interval increases, the dispersion of subsequent R-R intervals increased. The torpedo shape pattern reveals little or no increase in R-R interval dispersion as heart rate slowed. In the fan or triangular shape the points radiated in a relative symmetric manner from a narrow base at the lower RR-intervals.
The complex pattern shows several clusters of points, often with some of the features of both the fan and torpedo formations. All of the four typical patterns (Figure-1: comet-, torpedo-, fan- and complex-shaped) were quantified: the length (P-L), the area (P-A) and the highest variability extension (P-HVE). Other quantitative parameters were also calculated with the method of Huikuru et al: the STD1 (SD of instantaneous RR-interval variability measured from axis-1), the STD2 (SD of long-term continuous RR-interval variability measured from axis 2), DaMiHRV, the distance between the centroid and the averaged maximum of instantaneous RR-interval variability, and DMiHRV, the distance between the centroid and the maximum instantaneous RR-interval variability.

2.10. WAP Implementation-Based Telemedicine System for Patient Monitoring:
Wireless Application Protocol (WAP) is a specification and application environment for a set of communication protocol to standardize the way of wireless device, such as cellular telephones and radio transceivers that can be used for internet acces.Typical application of WAP include news, games, e-banking, shopping and e- mail . WAP will continue to be a common feature in hand-held devices and it is worthwhile to investigate its possible use in telemedicine. The ultimate goal of telemedicine is to provide a quality health care to anyone for medical diagnosis, treatment, and patient care. Usually, it is quite difficult for patients to get latest information about their health status where they need to go to hospital to know their condition. This situation must be difficult for people who are staying far away from hospital. People also need to leave their work and go to hospital or clinic to make an appointment with the doctor.

A WAP Implementation-Based Telemedicine System for Patient Monitoring has been developed to make user access patient data easily and to utilize WAP devices as mobile access terminals for general inquiry and patient monitoring services. Users simply need to subscribe WAP data service by using WAP phone. It uses WAP devices as mobile access terminals for general inquiry and patient monitoring services. Users can browse the patients' general data, BP and ECG reading on WAP device in store-and forward mode. Users also can browse patient record, clinic and hospital inquiry and doctor's appointment. WAP programming model consists of a WAP device, WAP gateway and server.
The architecture for the connection between WAP device and server. WAP device communicates with the server; which store information and responds to user's request. The gateway translates and passes the information between the WAP device communicates with the server; which store information and responds to user's request. The gateway translates and passes the information between the connections with the database. User interface was written in WML, and executed at WAP device after it has been downloaded from server. The other part of the application has been written in PHP. All the data are stored in server database. During WAP access, the data are retrieved the application through PHP's database interface. By using this application, patient general data, BP reading, and ECG data will be displayed on a mobile phone. Application will be loaded directly from server to computer or mobile phone via internet. All the accessed and manipulated data are stored in a relational database system. This design demonstrated telemedicine application that uses cellular phones and the internet.


Figure: 3.1 System Diagram

Figure: 3.2 Data Flow Diagram

Figure: 3.3 System overview Architecture

Figure: 3.3.1 Sender (ECG Monitor) Architecture

Figure: 3.3.2 Receiver (Android phone) Architecture

Figure: 3.4 Proposed system overview

It is a language. It is not simply a notation for drawing diagrams. It is a complete language for capturing knowledge (semantics) about a subject and expressing knowledge (syntax) regarding the subject for the purpose of communication. It is used for both database and software modeling. Version 1.1 was adopted by the object Management Group (OMG) as a standard language for object-oriented analysis and design. Ivar Jacobson is known as the father of Use Cases. Static structures include use cases, class and object diagrams.Behaviour includes state-chart, activity, sequence and collaboration diagrams. Implementation includes component and deployment diagrams.UML is effective for modeling large, complex software systems. It is simple to learn for most developers, but providers advanced features for expert analyst, designers and architects. It can specify systems in an implementation independent manner. Use case modeling specifies the functional requirements of system in an object-oriented manner.

Use Case Diagrams describe the functionality of a system and users of the system. It models the dynamic aspects the system. Actors represent users of system, including human users and other systems. Use Cases represent functionality provided by a system to users.Dependency, generalization and association relationships are included in use case diagram. Interaction diagram shows interactions of set of objects, their relationship and the messages dispatched among them. Two types of interaction diagram are Sequence Diagram and Collaboration Diagram. Sequence diagram contains the objects. Messages represent communication between objects. Lifelines represent the existence of an object over a period of the time. Activations represent the time during which an object is performing an operation. Collaboration diagram contains the structural organization of the objects that send and receive messages and have collection of vertices and arcs. The links are adorned with the messages that the objects send and receive. Path indicates how one object is linked to another object. Sequence Number indicates the time order of a message.


' In existing system, ECG is used to measure the rate and reliability of heartbeats, as well as the size and location of the chambers, the presence of any harm to the heart, and the property of drugs or policy used to regulate the heart, such as a pacemaker.
' An ECG is a non-persistent monitor, which can be utilized to evaluate the heart electrical activity, measure the rate and timekeeping of heartbeats, the position of the chambers, recognize any damage to the heart and investigate the effect of drugs and devices used to regulate the heart.
' This process is very useful for monitoring people with (or susceptible to) impairments in their cardiac activity.


' The regular monitoring of physiological parameter such as electrocardiography, oxygen saturation in hemoglobin and irregularity of cardiac regularity may provide critical information for a rapid diagnosis of medical conditions patients.
' Preventing the enlargement of any health situation to proportions vulnerable to cause mission failure or even death of a patient.


' The monitoring system proposed is based on achievement, condition and wireless transmission of two biomedical signals to a local or remote visualization system, two signal types were taken: ECG and temperature.
' For ECG acquisition, System designed by a 3-lead module is implemented, followed by a filtering and amplification stage. It is calibrated to correctly detect human beings temperature range. Under normal conditions, body temperature remains between 36:5 _C and 37:5 _C, and is usually taken in three body parts: armpit, mouth and rectum. Rectal and oral temperature correspond to the internal body temperature, providing a more accurate measure compared to the armpit temperature, which is, in average, 0.5 _C below real value.
' Analog to Digital conversion is made using the microcontroller board ARDUINO UNO, which includes the microcontroller ATmega328 for A/D and serial transmission purposes. The communication is made through virtual serial ports created in a PC during the matching between transmitter and receiver.
' Now Remote monitor continuously monitoring the ECG and body temperature. It saves the life of the patient and protects them from side effects. But still the ECG and temperature value is monitored thoroughly.


' It is made through virtual serial ports created in a PC during the matching between transmitter and receiver.
' Remote Monitoring of ECG & body temperature with affecting the day to day life of patient is done by the system itself.

In this module system is based on the acquisition, conditioning and wireless transmission of two biomedical signals to a local or remote visualization system.
This module has to take the two signals like the ECG and temperature. For the ECG acquisition, a 3 'lead module is implemented, followed by a filter and amplification stage. The INA 128P integrated circuit is used due to its benefits and because it is one of the most recommended devices in biomedical device implementations.
Additionally, a band pass analog filter is designed to cover the spectral width of the ECG signal (0.5-150Hz).Analog to Digital conversion is made using the microcontroller board ARDUINO UNO, which includes the microcontroller ATmega328 for Analog to Digital and serial transmission purposes.
This module describes the configuration needed for serial Bluetooth USB transmission. programming codeless developed to read analog ECG and temperature inputs and convert them to a 10 bit digital value ,to be written then in serial output port, so it is possible to identify the PHY and MAC layer requirements for transmission are set any the standard IEEE 802.11.1, which sets the operating frequency at 2.4GHZ and allows maximum distances up to 100m ,so the RN-41 Bluetooth USB transmission is encoding codeless developed to read analog ECG and temperature inputs and convert them to a 19 bit data once captured by the receptor.
The Analog to Digital conversion is defined by the ratio. So the RN-41 Bluetooth module was used to manage the stack protocol for wireless transmission. The communication is made during virtual serial ports created in a PC during the matching between the transmitter and receiver.

These signals could be received in two different devices like a mobile phone or a PC, if they count with the application software for such purpose. In this case, two different applications are developed.
1) PC: The reception and visualization interface was developed in java, under platform Net beans. Such interface make possible to visualize both of the signals simultaneously. Also it allows sending them via IP to a web server and storing them in a configured database with patient's registry. This application is developed to fill medical personnel information requirements.
2) Mobile Phone: For mobile communication, a library called Amarino is used. This is constituted by three main parts: the first one, for Operating systems using Android, the second one, which uses the Meet Android library installed inside the folders of Arduino and a third one called Plug-in Bundle. The mobile device is previously programmed complete the connection to bluetooth module by using the information about MAC address.


The captured and visualized signals are sent for storage, to a remote database through IP networking. Database access can be made in a local or remote way, since user count with internet connectivity, even without QoS service previously configured. This is the information load to suitable for low speed connections.
A web server application (servlet) is developed; this is called 'Biomedical Visual Platform' which links the application with the database information. The served developed receives the request made from the application and establish a linking channel through MySQLconnection class.

Electrocardiogram (ECG) is a diagnostic tool that allows lifesaving decisions, as in coronary thrombolytic case, whose diagnosis should be done in less than six hours of onset of symptoms. Information is sent to a database server containing clinical data, through IP (GPRS or Wi-Fi). It can be accessed through a web application. By testing different patients with the support of a doctor, obtaining a positive performance the system can be assessed.



RAM : 256 MB
FDD : 1.44 MB
HDD : 40 GB

Android is an operating system based on the Linux kernel, and designed primarily for touch screen mobile devices such as smart phones and tablet computers. Initially developed by Android, Inc., which Google backed financially and later bought Android was unveiled in 2007 along with the founding of the Open Handset Alliance: a consortium of hardware, software, and telecommunication companies devoted to advancing open standards for mobile devices.[14] The first Android phone (HTC Dream) was sold in October 2008.
The user interface of Android is based on direct manipulation, using touch inputs that loosely correspond to real-world actions, like swiping, tapping, pinching and reverse pinching to manipulate on-screen objects. Internal hardware such as accelerometers, gyroscopes and proximity sensors are used by some applications to respond to additional user actions, for example adjusting the screen from portrait to landscape depending on how the device is oriented. Android allows users to customize their home screens with shortcuts to applications and widgets, which allow users to display live content, such as emails and weather information, directly on the home screen. Applications can further send notifications to the user to inform them of relevant information, such as new emails and text messages.
Android is open source and Google releases the source code under the Apache License. This open-source code and permissive licensing allows the software to be freely modified and distributed by device manufacturers, wireless carriers and enthusiast developers. However, most Android devices ship with additional proprietary software. Additionally, Android has a large community of developers writing applications ("apps") that extend the functionality of devices, written primarily in the Java programming language. In October 2012, there were approximately 700,000 apps available for Android, and the estimated number of applications downloaded from Google Play, Android's primary app store, was 25 billion. A developer survey conducted in April'May 2013 found that Android is the most popular platform for developers, used by 71% of the mobile developer population.
Android is the world's most widely used smart phone platform, overtaking Symbian in the fourth quarter of 2010. Android is popular with technology companies who require a ready-made, low-cost, customizable and lightweight operating system for high techdevices. Despite being primarily designed for phones and tablets, it also has been used in televisions, games consoles, digital cameras and other electronics. Android's open nature has encouraged a large community of developers and enthusiasts to use the open-source code as a foundation for community-driven projects, which add new features for advanced users or bring Android to devices which were officially, released running other operating systems.
Android's user interface is based on direct manipulation, using touch inputs that loosely correspond to real-world actions, like swiping, tapping, pinching and reverse pinching to manipulate on-screen objects.[49] The response to user input is designed to be immediate and provides a fluid touch interface, often using the vibration capabilities of the device to provide feed back to the user. Internal hardware such as accelerometers, gyroscopes and proximity sensors are used by some applications to respond to additional user actions, for example adjusting the screen from portrait to landscape depending on how the device is oriented, or allowing the user to steer a vehicle in a racing game by rotating the device, simulating control of a steering wheel.
Android devices boot to the home screen, the primary navigation and information point on the device, which is similar to the desktop found on PCs. Android home screens are typically made up of app icons and widgets; app icons launch the associated app, whereas widgets display live, auto-updating content such as the weather forecast, the user's email inbox, or a news ticker directly on the home screen. A home screen may be made up of several pages that the user can swipe back and forth between, though Android's home screen interface is heavily customizable, allowing the user to adjust the look and feel of the device to their tastes. Third-party apps available on Google Play and other app stores can extensively re-theme the home screen, and even mimic the look of other operating systems, such as Windows Phone. Most manufacturers, and some wireless carriers, customize the look and feel of their Android devices to differentiate themselves from their competitors.
Present along the top of the screen is a status bar, showing information about the device and its connectivity. This status bar can be "pulled" down to reveal a notification screen where apps display important information or updates, such as a newly received email or SMS text, in a way that does not immediately interrupt or inconvenience the user.[56] In early versions of Android these notifications could be tapped to open the relevant app, but recent updates have provided enhanced functionality, such as the ability to call a number back directly from the missed call notification without having to open the dialer app first. Notifications are persistent until read or dismissed by the user.

Android has a growing selection of third party applications, which can be acquired by users either through an app store such as Google Play or the Amazon Appstore, or by downloading and installing the application's APK file from a third-party site. The Play Store application allows users to browse, download and update apps published by Google and third-party developers, and is pre-installed on devices that comply with Google's compatibility requirements. The app filters the list of available applications to those that are compatible with the user's device, and developers may restrict their applications to particular carriers or countries for business reasons. Purchases of unwanted applications can be refunded within 15 minutes of the time of download, and some carriers offer direct carrier billing for Google Play application purchases, where the cost of the application is added to the user's monthly bill. As of September 2012, there were more than 675,000 apps available for Android, and the estimated number of applications downloaded from the Play Store was 25 billion.
Applications are developed in the Java language using the Android software development kit (SDK). The SDK includes a comprehensive set of development tools,[64] including a debugger, software libraries, a handset emulator based on QEMU, documentation, sample code, and tutorials. The officially supported integrated (IDE) is Eclipse using the Android Development Tools (ADT) plug-in. Other development tools are available, including a Native Development Kit for applications or extensions in C or C++, Google App Inventor, a visual environment for novice programmers, and various frameworks.

Memory management
Since Android devices are usually battery-powered, Android is designed to manage memory (RAM) to keep power consumption at a minimum, in contrast to desktop operating systems which generally assume they are connected to unlimited mains electricity. When an Android app is no longer in use, the system will automatically suspend it in memory ' while the app is still technically "open," suspended apps consume no resources (e.g. battery power or processing power) and sit idly in the background until needed again. This has the dual benefit of increasing the general responsiveness of Android devices, since apps don't need to be closed and reopened from scratch each time, but also ensuring background apps don't consume power needlessly. Android manages the apps stored in memory automatically: when memory is low, the system will begin killing apps and processes that have been inactive for a while, in reverse order since they were last used (i.e. oldest first). This process is designed to be invisible to the user, such that users do not need to manage memory or the killing of apps themselves. However, confusion over Android memory management has resulted in third-party task killers becoming popular on the Google Play store; these third-party task killers are generally regarded as doing more harm than good.
The main hardware platform for Android is the 32-bit ARMv7 architecture. There is support for x86 from the Android-x86 project, and Google uses a special x86 version of Android. In 2013, Free scale announced Android on its i.MX processor, i.MX5X and i.MX6X series. In 2012 Intel processors began to appear on more mainstream Android platforms, such as phones.
As of November 2013, current versions of Android require at least 512 MB of RAM, and a 32-bit ARMv7, MIPS or x86 architecture processor, together with an OpenGL ES 2.0 compatible graphics processing unit (GPU). Android supports OpenGL ES 1.1, 2.0 and 3.0. Some applications explicitly require certain version of the OpenGL ES, thus suitable GPU hardware is required to run such applications. Android devices incorporate many optional hardware components, including still or video cameras, GPS, hardware orientation sensors, dedicated gaming controls, accelerometers, gyroscopes, barometers, magnetometers, proximity sensors, pressure sensors, and touch screens.
Some hardware components are not required, but became standard in certain classes of devices, such as smart phones, and additional requirements apply if they are present. Some other hardware was initially required, but those requirements have been relaxed or eliminated altogether. For example, as Android was developed initially as a phone OS, hardware such as microphones were required, while over time the phone function became optional. Android used to require an autofocus camera, which was relaxed to a fixed-focus camera if it is even present at all, since the camera was dropped as a requirement entirely when Android started to be used on set-top boxes.
Android is developed in private by Google until the latest changes and updates are ready to be released, at which point the source code is made available publicly. This source code will only run without modification on select devices, usually the Nexus series of devices. The source code is, in turn, adapted by OEMs to run on their hardware. Android's source code does not contain the often proprietary devices that are needed for certain hardware components.
The green Android logo was designed for Google in 2007 by graphic designer Irina Blok. The design team was tasked with a project to create a universally identifiable icon with the specific inclusion of a robot in the final design. After numerous design developments based on science-fiction and space movies, the team eventually sought inspiration from the human symbol on restroom doors and modified the figure into a robot shape. As Android is open-sourced, it was agreed that the logo should be likewise, and since its launch the green logo has been reinterpreted into countless variations on the original design
Despite its success on smart phones, initially Android tablet adoption was slow.[166] One of the main causes was the chicken or the egg situation where consumers were hesitant to buy an Android tablet due to a lack of high quality tablet apps, but developers were hesitant to spend time and resources developing tablet apps until there was a significant market for them. The content and app "ecosystem" proved more important than hardware specs as the selling point for tablets. Due to the lack of Android tablet-specific apps in 2011, early Android tablets had to make do with existing smart phone apps that were ill-suited to larger screen sizes, whereas the dominance of Apple's iPad was reinforced by the large number of tablet-specific iOS apps.
Despite app support in its infancy, a considerable number of Android tablets (alongside those using other operating systems, such as the HP Touchpad and BlackBerry Playbook) were rushed out to market in an attempt to capitalize on the success of the iPad. InfoWorld has suggested that some Android manufacturers initially treated their first tablets as a "Franken phone business", a short-term low-investment opportunity by placing a smart phone-optimized Android OS (before Android 3.0 Honeycomb for tablets was available) on a device while neglecting user interface. This approach, such as with the Dell Streak, failed to gain market traction with consumers as well as damaging the early reputation of Android tablets.

The proposed system is a result of different hardware and software prototype compilation. It is mainly used for biomedical signal monitoring. This system is revised and verified by medical personnel thoroughly. The main advantages of this implementation are portability, low cost, connectivity easiness, and scalability. It is possible to add more signals as well as up to 3 more ECG inputs in the proposed system. The proposed system could be successfully applied to rural environments where connectivity issues persist.
In future plan to modifying the biometric authentication using ECG .the problem of identifying the password can be avoided. So that the circuit can be modified in such a way that it can be fixed on the body. The algorithms can elabrateded to detecting the additional heart ailments.

package com.example.test;
import android.content.Intent;
public class CSleeper
extends Activity implements Runnable
private Boolean done = Boolean.valueOf(false);
private MainActivity m_ma;
private CSampler m_sampler;
public CSleeper(MainActivity paramMainActivity, CSampler paramCSampler)
m_ma = paramMainActivity;
m_sampler = paramCSampler;
public void run()
} catch (Exception e) {
while (true)
// if(MainActivity.sms)
// startActivity(new Intent(getApplicationContext(),ContactActivity.class));
catch (InterruptedException localInterruptedException)

[1] J.-R. C. Chien and C.-C. Tai, 'A new wireless-type physiological signal measuring system using a pda and the bluetooth technology,' Biomedical Engineering Aplications, Basis and Communications, vol. 17, no. 5, pp.229'235, October 2005.
[2] O. Krejcar, D. Janckulik, L. Motalova, and K. Musil, 'Real time processing of ecg signal on mobile embedded monitoring stations,' Second International Conference on Computer Engineering and Applications, 2010.
[3] Y. M. Lee and M. Voghavvemi, 'Remot heart rate monitoring system based on phonocardiography,' Student Conference on Research and Development Proceedings, Shah Alam, Malasya, 2002.
[4] S. Khoor, J. Nieberl, K. Fugedi, and E. Kail, 'Telemedicine ecg telemetry with bluetooth technology,' Computers in Cardiology, 2001.
[5] D. R. Zhang, C. J. Deepu, X. Y. Xu, and Y. Lian, 'A wireless ecg plaster for real-time cardiac health monitoring in body sensor network,' Biomedical Circuits and Systems Conference (BioCAS), IEEE, 2001.
[6] Z. Whittaker, 'Nielsen: Smartphone owners surpass 50 percent mark,' Available on 50-percent-mark/76347, May 2012.
[7] D. Melanson, 'comscore report finds 42 percent of us mobile users have smartphones, android at nearly 50 percent,' Available on, February 2012.
[8] T. K. Kho, R. Besar, Y. S. Tan, K. H. Tee, and K. C. Ong, 'Bluetoothenabled ecg monitoring system,' Faculty of Engineering and Technology,Multimedia University (Melaka Campus), Jalan Ayer Keroh Lama,75450 Melaka, Malasya, 2005.
[9] A. Perry and P. Potter, Medicion de la temperatura oral. Medicion dela temperatura rectal. Medicion de la temperatura axilar, cuarta ed.M. H. Brace, Ed. Guia clinica de enfermeria. Tecnicas y procedimientos basicos, 1998.
[10] 'Instructions how to use the amarino toolkit to connect android phones to arduinos,' Available on
[11] M. B. khodabakhshi, and A. Janqorbani, "Screening and ECG signal using
a mobile phone, along with the diagnosis", Thesis, Shahed University, 2008.

[12] Chan, Brady, Harrigan, ornato, and rosen, ECG in Emergency Medicine
and Acute Care, 2005, PP.80-82.

[13] Pamnani Divya, Express Pharma-Fortnightly, insight for pharma
professionals, Jan. 16-31, 2009.

[14] A. khorovets, "What is an Electrocardiogram?" The internet journal of
Health, Vol. 1 Number 2, 2000.

[15] D. G. Clifford, A. Francisci, and P. E. McSharry, Advanced Methods and
Tools for ECG Data Analysis, 2006, pp.68'73.
[16] T. K. Kho, Rosli Besar, Y. S. Tan, K. H. Tee, K. C. Ong, 'Bluetooth-enabled ECG Monitoring System', Tencon 2005 IEEE Region 10, 2005, pp.1-5.

[17] D. Kammer, G. McNutt, and B. Senese, Bluetooth Application Developer's Guide, Syngress Publishing, Rockland, Mass, USA, 2002

[18] Jordan,R.;Abdallah and C.T., 'Wireless Communication And Networking An Overview'. IEEE Antennas and Propagation Magazine, vol 44 Issue:1, pp.185-193, Feb 2002.

[19] R. Bouhenguel, I. Mahgoub, and M. Ilyas, 'Bluetooth security in wearable computing applications,' in Proceedings of the International Symposium on High Capacity Optical Networks and Enabling Technologies, pp. 182'186, November 2008

[20] The official Bluetooth wireless info site , last accessed:[1/7/2012]




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