1.1 Modern Health Care and Monitoring
The worldwide population of people over the age of 65 has been predicted to more than double from 375 million in 1990 to 761 million by 2025 [1]. In Taiwan, the average age of the population has risen from 26 to 36 within the past twenty years and the number of people below the age of 25 is rapidly decreasing [2]. Figure 1.1 shows the aging trend in Taiwan. Within a few years, society will be faced with the problem of an aged population. The aging of the population will inevitably add to the burden of an already fragile healthcare system plaguing virtually every major government. An aged population implies a decline in the size of the working age group, producing a higher percentage of persons above 65 years of age. This trend is sure to result in a shortage of medical personnel, which, along with rising costs will leave hospitals unable to meet the medical requirements of a growing number of elderly patients. In addition, the development of long-term health care environments has lagged behind compared to advancements in medical science. Therefore, whilst life expectancy is seen to be rising, inadequacies in daily healthcare may decrease the quality of life of the aged.
Technology can assist in alleviating the burden of doctors and medical staff by introducing a shift in the healthcare infrastructure [3]. While current medical paradigms are able to provide extremely professional and precise responses to illnesses that may occur, it is fundamentally a clinic-oriented structure optimized for crisis reaction. To maintain prolonged wellness, technologies designed for healthcare can be pushed towards the home environment enabling real-time monitoring, diagnosis, and prevention. Such technologies help senior patients become more independent in terms of healthcare, and can benefit the general population by providing a ubiquitous healthcare environment.
(a) (b)
Figure 1.1 (a) Average age of the population in Taiwan, 1906-2006 (b) Number of people below the age of 25 in Taiwan, 1984-2006 [2]
For the elderly, heart disease is a major concern in the health factor.
Cardio-vascular diseases (CVD) are the leading cause of death in many countries including the United States [4]. CVD claimed 831,272 lives in the United States in 2006.
Of the total deaths, 82% of the victims were above the age of 65 [5]. As the elderly population increases, death from CVD is a rising concern, thus technologies in at-home healthcare and patient monitoring products for early detection of heart disease have become more important than before.
At home healthcare technologies can enable early detection of diseases or complications resulting from diagnosed or dormant CVD. After detection, preventive steps can be taken to neutralize the problem before it develops into a life-threatening condition. Moreover, monitoring systems can provide remote observation of patients during prolonged treatment and indicate the state of recovery. Thus, whether used in formal (physician-based) or informal (user-based) applications, ubiquitous healthcare for cardiac related diseases is essential in improving the quality of life and longevity of our gradually aging population.
1.2 Previous Literature
The study and development of portable systems for wireless medical healthcare services has gained widespread interest in the last 10 years. With the recent advancements in wireless technology, many studies have been devoted to the design and implementation of a portable ECG healthcare system for a wide range of applications. In the MyHeart Project, the genres of ECG monitoring where classified into four types of concept applications. The MyHeart Project [6,7] is a project of the European Union aiming to develop intelligent systems for the prevention and monitoring of cardiovascular diseases.
The classified concepts encompassed four major user scenarios: exercise sessions of the healthy (Activity Coach), those at risk for developing CVD (Take Care), sufferers from a cardiac event (Neurological Rehabilitation), and chronically ill people (Heart Failure Management). The MyHeart Project proposed the prevention and early diagnosis of CVD through the use of wearable technology for monitoring of vital body signs in these scenarios. By processing the measured data and giving (therapy) recommendations to the user of the system, complications from CVD could be reduced and general wellness can be maintained.
In many studies, the respective proposed systems correspond to the ‘Take Care’
and ‘Heart Failure Management’ frameworks classified by the MyHeart Project. In such studies, developed structures include acquisition of ECG signals and wireless transmission to a remote station for use in at-home monitoring or emergency applications.
In [8] a wireless 2-lead ECG system was developed to monitor vital signs and cardiac information with ultimate deployment in intensive care units (ICU). Their system used radio frequencies in the ISM band at either 433MHz or 916MHz for wireless transmission. A 433 MHz FM/FSK transmitter was also used in [9] for wireless transmission of ECG signals. The application of wireless ECG realized a medical
biotelemetry. The use of standard wireless technologies has also been proposed in many studies. Bluetooth was used in [7,10,11,12] for wireless transmission of ECG, whereas ZigBee was used in [13,14,15,16,17].
Biotelemetry and portable ECG systems can offer a more convenient way of acquiring ECG data, however, biotelemetry alone cannot solve the crisis that an aging population poses because it keeps expensive, overburdened doctors and nurses in the loop [18]. In other words, it is limited in that a remote PC station and physician is still required for further analysis and diagnosis of data. Integrated systems with functions for online and real-time analysis can offer a better solution to ubiquitous health-care and have also been widely studied.
[19] proposed a computer based wireless system for online acquisition, monitoring and digital processing of ECG. In [20] a wireless system for ECG recordings and real-time analysis of heart rate variability (HRV) was proposed. In their system, a PDA was used to receive ECG data from Bluetooth and run the software analysis program for time-domain analysis of HRV. Such studies adopt the use of software at the backend of the system for analysis of the ECG data. Other studies, however, focus on analysis of data on-the-fly before wireless transmission by using system-on-chip (SOC) technology. By performing analysis through SOC design, the system can have more mobility and portability. [21] proposed an SOC design with embedded ECG signal processing. An ARM processor was used for system control, wireless communication, and a simple beat detection function in their design. An ECG SOC design for wearable cardiac monitoring devices was also proposed in [22] which included an online QRS detector. In [23] a heart rate variability monitoring and assessment system-on-chip was proposed where the beat-to-beat intervals were calculated and used for HRV classification. Their studies would later go on to propose an application-specific integrated circuit (ASIC) designed for digital heart rate variability (HRV) parameter monitoring [24].
Portable ECG medical devices have become more and more widespread in recent years. The potential to acquire and monitor the ECG of a patient is a prospective ability with viable applications in telemedicine, long-term health care, and various researches.
However, such devices only provide a solution to wireless signal acquisition and very often a remote science station is still needed for off-line analysis of the ECG signal. For a truly ubiquitous health care system, the system should not only include basic functions for signal acquisition, but also provide the ability to perform accurate real-time analysis of the ECG data. Through SOC technology, integrated systems are able to acquire ECG data, perform real-time data analysis, and transmit data wirelessly all in a single low area and low power chip solution.
1.3 Scope and Contributions
In this thesis, a portable multi-channel ECG monitoring system-on-chip with an on-board effective HRV processor is proposed. The system includes a front-end circuit and ADC controller for acquisition of three-channel ECG. From the ECG, time-frequency analysis of HRV can be performed using a developed on-board HRV processor. A compression engine is included in the system to reduce the size of data before wireless transmission. In the proposed SOC, the UART standard is used as the method of output.
This makes the system more flexible, allowing for connection with Bluetooth, ZigBee, PC, or any other device using UART.
This thesis also consists of a study on spectral estimation methods for short-term frequency domain HRV analysis as well as implementation considerations for SOC design. The capabilities of the Lomb periodogram for spectral analysis over traditional methods such as Fourier transform were compared and analyzed. A VLSI implementation of an HRV processor for time-frequency HRV analysis using the Lomb periodogram has also been proposed. Finally, the HRV processor has been integrated into an ECG SOC for
applications in portable ECG monitoring and real-time HRV analysis. The proposed ECG SOC is suitable for use in portable wireless ECG medical devices where the system is constrained by power and area issues. Through an integrated SOC design, a portable system for on-line real-time analysis of ECG data that is low-power and low-area is possible. The significance of this ECG SOC is to enable practical development of portable real-time heart monitoring and analysis systems.
1.4 Organization of the Thesis
The organization of this thesis is as follows. Chapter 2 describes the importance and characteristics of an integrated ECG health-care system. The mechanics of ECG is first described as well as uses in clinical practice in this chapter. Next an overview of medical ECG systems and application scenarios is given. In Chapter 3 the proposed HRV processor is presented from algorithm study to final VLSI design. Section 3.3 details the design considerations and architecture of the HRV processer. The performance and analysis of the HRV processor is given in Section 3.4. In Chapter 4 the design of the integrated ECG SOC from a top-down view is described. The basic modules and functions of the SOC design are presented in this chapter. Chapter 5 the details and specifications of the final chip implementation is presented. Finally, the conclusion and future work is given in Chapter 6.