With the rise of living standard and the advance of medical technologies today, human life is being extended and the number of living-alone elders is increasing. In this situation, the importance of medical services for improving their life quality is highly recognized. That is, the paradigm of medical services is changing from the diagnosis and treatment of diseases to the prevention and management of diseases. This change is particularly remarkable in the area of mobile healthcare, which can manage diseases and health at any time and in any place during daily life. Mobile healthcare is a technology that acquires various biomedical data using wearable biomedical signal monitoring devices, analyzes the data, and provides services such as the treatment of diseases and health management, and it is applicable to chronic disease patients, emergent situation monitoring, health management for ordinary people, etc. Research on wearable biomedical signal monitoring devices to be used in daily life is being made actively in Korea and other countries. The Harvard University in the U.S. is conducting the CodeBlue Project that develops wireless sensor network technology to be used in various medical applications including the management of emergent medical services before and during hospitalization and the rehabilitation of stroke patients1). The AMON Project developed a wearable personal health system that monitors and evaluates biomedical signals using bio-sensors. This system can be worn on the wrist, and transmits vital sign data such as heart rate, ECG, blood pressure, and body temperature to a remote server through GSM so that patients or ordinary people can get services2). Besides, LifeShirt of Vivometrics Company developed a garment-type system for monitoring biomedical signals. It measures various parameters including information on breath, heart rate, and posture using 1-channel ECG sensor, 2-axis accelerometer, respiration sensor, etc.3). LifeGuard is a biomedical monitoring system developed jointly by NASA and Stanford University in the U.S. This system is composed of sensors to measure ECG, respiration, SpO2, blood pressure, etc., a portable device to process and record the measured biomedical signals, and tablet PC or PDA to display and analyze recorded biomedical signals4). Jovanov at Alabama University proposed a health monitoring system using Wireless Body Area Network (WBAN) for monitoring biomedical signals and motion signals5).

It was implemented for monitoring individuals' biomedical signals and motion signals during their movement. This system used two accelerometers to measure motion signals, and had a 1-channel bio-amplifier to measure patents' heart rate. Table 1 compares the characteristics of portable or wearable monitoring systems developed until now. The four types of portable or wearable systems presented in Table 1 are superior in functionality itself but they need many further improvements in order to provide continuous healthcare services. The ring-type is convenient to carry, but battery life is short. The bracelet-type is easier to develop and uses the battery longer than the ring-type, but it has to use PDA or PC to transmit data. In addition, the portable-type is easier to develop than the bracelet-type, but is inconvenient to carry. Lastly, the garment-type sets all the biomedical sensors inside the clothes, and thus it is stable and acquires precise biomedical data, but the system is large in size and heavy. Thus, to solve these problems, the present study designed a system that, using a belt-type integrated device, can measure ECG and motion signals continuously at any time and in any place during daily life and, on the occurrence of an emergent situation, inform a remote doctor of the situation by sending emergent situation data to a remote server through CDMA network. In addition, this study purposed to build a system usable in real life through performance evaluation of the developed system.

Figure 1 is the schematic diagram of the system that uses the developed device. This system is composed of a biomedical mobile device and a remote medical server. The belt-type biomedical mobile device developed in this study was designed to collect the user's biomedical signals continuously and, on the occurrence of a problem, to send the data immediately to a remote medical server through CDMA network. Among various biomedical parameters, ECG was used, which is studied most frequently as an indicator of cardiovascular diseases. Also, in order to measure the user's daily movements in addition to ECG, the system was embedded with an accelerometer. This device was designed to measure both ECG and acceleration signal simultaneously. By measuring the user's ECG and motion signals such as sitting, walking, and running, it can figure out the user's current situation.

The present study developed an integrated system that can measure ECG and motion signals continuously while the user is moving and, on the occurrence of an emergent situation, transmits emergent situation data to a remote medical server through CDMA network and reports the situation, and tested the system's accuracy, reliability and operability, applicability to daily life, and SMS alarm function through experiments. First, we examined the accuracy of R-R interval through comparative analysis of signals obtained using the developed device and a commercialized ECG system while the subjects were sitting, standing, lying, or cycling. In the four types of gesture, the percentage of heart beats with R-R interval error less than 5 ms was over 99%, proving that the device is as good in measuring heart rate as commercialized non-portable systems. Second, we tested whether data are transmitted reliably to the remote server when two types of emergent events are generated in the developed device using a patient simulator, and measured battery life together to see if the device is usable for a long time. The device operated for around 13 hours with 3 AAA batteries, and around 24 hours with 3 AA batteries. This results show that the developed system can perform both the holter ECG function and the event-recorder function at the same time. Third, we tested whether the corresponding data are transmitted accurately to the remote server when two types of events are generated using CDMA network for each of seven types of action in daily life. The existing holter system recorded the variation of ECG waveform continuously and detected cardiovascular diseases based on the variation of waveform in the recorded data. A shortcoming of this system is that the user's current situation is unknown. Therefore, we tried to measure 3-axis acceleration signal together with ECG in order to figure out the user's current state. This is expected to make health state evaluation and treatment more meaningful, and produced data are considered quite useful in evaluating patients' behavior6-8). In addition, remote management using CDMA network will enable a prompt action in emergency. Lastly, this study tested the SMS alarm function. This function was designed for the old, the weak or chronic disease patients to get prompt rescue or first aid services through the biomedical mobile device. That is, medical staff examines the waveforms of ECG and acceleration transmitted to a remote medical server, and if they find any problem they let the patient know the situation by sending an emergent message to the patient.

The present study developed a belt-type biomedical mobile device and concluded as follows. When the subjects' biomedical signals and motion signals were collected and compared, the device showed high accuracy, reliability and operability, applicability to daily life, and SMS alarm function to be used during daily life. It is also considered usable to cope with emergent situations promptly and applicable to patients who need to be monitored continuously for chronic disease management and health management. In addition, the device may be integrated into systems for monitoring ordinary people or the old and weak in daily life, and a remote server will enable continuous monitoring of patients' state and prompt help in emergency. The system will be improved further to be applicable to real patients by adding various types of heart disease information, and the size will be reduced further. In addition, it will be studied in connection to injuries caused by falling that is frequent in elders and physical impaired people, and the existing algorithm will be extended to detect falling as well.