Integrated Solution for Physical Activity Monitoring Based on Mobile Phone and PC / 대한의료정보학회지

OBJECTIVES: This study is part of the ongoing development of treatment methods for metabolic syndrome (MS) project, which involves monitoring daily physical activity. In this study, we have focused on detecting walking activity from subjects which includes many other physical activities such as standing, sitting, lying, walking, running, and falling. Specially, we implemented an integrated solution for various physical activities monitoring using a mobile phone and PC. METHODS: We put the iPod touch has built in a tri-axial accelerometer on the waist of the subjects, and measured change in acceleration signal according to change in ambulatory movement and physical activities. First, we developed of programs that are aware of step counts, velocity of walking, energy consumptions, and metabolic equivalents based on iPod. Second, we have developed the activity recognition program based on PC. iPod synchronization with PC to transmit measured data using iPhoneBrowser program. Using the implemented system, we analyzed change in acceleration signal according to the change of six activity patterns. RESULTS: We compared results of the step counting algorithm with different positions. The mean accuracy across these tests was 99.6 +/- 0.61%, 99.1 +/- 0.87% (right waist location, right pants pocket). Moreover, six activities recognition was performed using Fuzzy c means classification algorithm recognized over 98% accuracy. In addition we developed of programs that synchronization of data between PC and iPod for long-term physical activity monitoring. CONCLUSIONS: This study will provide evidence on using mobile phone and PC for monitoring various activities in everyday life. The next step in our system will be addition of a standard value of various physical activities in everyday life such as household duties and a health guideline how to select and plan exercise considering one's physical characteristics and condition.

A Study on the Patient Location Monitoring System Based on RFID - RSSI / 대한의료정보학회지

OBJECTIVE: The location services has been an important research area in the U-Healthcare. The location services in medical environment can be implemented by Radio Frequency Identification (RFID), and Received Signal Strength Indication (RSSI) which is the location tracking method by RFID. In this study, we was designed the Patient Location Monitoring System based on RFID using RSSI method. METHODS: The RSSI method is a distance measurement method from reference points to object using the Friis's Principle and the Triangulation. The Patient Location Monitoring System was implemented by XML Data transmitted from the Positioning Server to the application. The Patient Location Monitoring System was designed by C# of Visual Studio 2005 and MS-SQL 2005 Express. RESULTS: The Patient Location Monitoring System had the location-tracking average error of 90.50cm, the standard-deviation of 13.34cm in Open-Space test. And, the designed system had the location-tracking average error of 163.24cm, the standard-deviation of 16.85cm in Closed-Space Test. Also, a patient waiting-list guide performance of the Patient Location Monitoring System had successes of 85~100%. CONCLUSION: In this study, the Patient Location Monitoring System, combined with both patient location-tracking function and patient waiting-list guide function, was validated by experiments in medical environment and this system can be applicable to patient management and further applications.

Design of Real-time Ambulance Location Monitoring System using Open API and GPS Based on Web 2.0 / 대한의료정보학회지

OBJECTIVE: The term "Open API" has been recently in use by recent trends in social media and web 2.0. It is currently a heavily sought after solution to interconnect Web sites in a more fluid user-friendly manner. We could have many benefits easily development and high efficiency. In this paper, Real-time ambulance location monitoring system including Integrated Maps was designed by using Maps Open API based on Web 2.0. METHODS: Integrated Maps were used by using Google Maps Open API and Naver Maps Open API respectively. GPS Web Browser was implemented to present integrated Maps on the designed system continuously. The development environments of the designed systems were C# and ASP.NET Platform. RESULTS: The designed systems contained three parts composed to Integrated Maps, Ambulance System, and Center Monitoring System respectively. Integrated Maps could offer Satellite, Map and Hybrid typed maps at Real-time Ambulance Location Monitoring System. CONCLUSION: Real-time Ambulance Location Monitoring System could be developed with low cost using a Open API at available emergency situations. We expect to more using Open API in medical systems.

Advanced algorithms of motion estimation for an elder at living room using Principal Component Analysis / 대한의료정보학회지

OBJECTIVE: Development of telemedicine for an elder has been an important research area in an aging society, and effective Personal Emergency Response System(PERS) can provide exact medical decision and prompt treatment under emergency conditions. Previous studies have been focused on adapting troublesome sensors or passive calling system to monitor the old in their house. However, these previous systems might have limited applications due to its difficulties in usage and restraints in their daily activities, especially in the emergency. METHODS: In this study, the real time algorithms using surveillance camera was developed to monitor their pose change, such as emergency and falling motion. To estimate the motion of elder people, this research use a ratio of eigenvectors of the Principal Component Analysis (PCA) technique. RESULTS: In this system, no additional motion sensors or devices were applied to the object and it can be automatically controlled and monitor the old from a distance. It was found that this system can successfully monitor the old in living room regardless of surveillance camera angles and a silhouette size depending camera distance as using image processing and PCA. CONCLUSION: This algorithm was validated by experiments in a living room and this technique can be applicable to home monitoring and further applications.