Physical activity and frailty analysis system

• Main Authors: Yi-Zong Jhan, 詹益宗
• Other Authors: Yuh-Show Tsai
• Format: Others
• Language: zh-TW
• Published: 2012
• Online Access: http://ndltd.ncl.edu.tw/handle/43509492848078764317

碩士 === 中原大學 === 生物醫學工程研究所 === 100 === The occurring of physical frailty often causes the loss of body function and generates adverse disease. The process of frailty is subtle and slow, so without a long term record, to have the diagnosis by a single meeting is quite difficult. Traditionally, the diagnosis of doctors depends on their own experience, but it is too subjective and difficult to compare during varied periods. Although there are existing instruments can precisely assist in the diagnosis, these devices are still too expensive and complicated, and the measurement and data interpretation are also difficult. Therefore, an expert is needed during operation. Due to above reasons, these devices and methods are difficult to be used commonly. This research is going to present an analysis system of physical frailty, including the front-end hardware measurement devices and back-end data analysis and storage interface. By this system, the doctors can avoid high cost of equipment and have a simpler measurement process; on the other hand, it can help doctors to establish a data set of long-term changes in physical activity that can notice the occurring of limb degradation easily. The analysis system using a three-axis acceleration sensor as a front-end physical activity signal capture device, and hardware devices can have different measurement modes by different setting from the interface. With different mode, this system can measure varied parameters of gait and data of physical activity. On the back-end part, the programs are separated into two sets, the hospital end and the home end. The software for hospital can record the gait parameters, and data can be sent to the computer and displayed in real-time by Bluetooth devices in a wireless way. The software for home use is to collect the long-term data of activity. User wears the device on the waist and it can record the activity status daily. Before bedtime, the user can remove the device, and charge by USB port of computer and receive data form device. At last, the two sets of programs can upload data to the server and have unified management and storage. The doctor can use the interface of data analysis to recall the data of patients, so the differences of patients’ physical activities in varied time can be recheck, as an important factor of diagnosis. In this study, a lightweight and portable device has been successfully developed, and all the measurement of different physical activities can be evaluated by using the same set of hardware. It can avoid the inconvenient and complicated use of equipment and significantly decrease the cost. By the integrating of data from hospital end and the home end, the doctor can understand the long-term data of gait parameters of patients. By quantification of physical activity data, this system can help doctors have an objective and easy diagnosis of the frailty in the clinical.