With the advent of the intelligent era, the combination of Internet of things in various fields has gradually been widely used. In order to better serve consumers, traditional adult pull-ups and paper-based incontinence products not only need to have basic performance, but also need to constantly strengthen their functions. This led to the research of intelligent adult pull-ups sensor system. In a short time, from the scheme design to the actual prototype, the complete development of sensors, detection devices, smart phones and server platform was realized, and the performance and application of the system were verified. However, in view of the experience, time and experimental conditions, the system still has some problems that need to be further improved, mainly including the following aspects.
The 8-bit microprocessor ADuC834 is selected as the lower computer of the system. Although its powerful 24 bit ADC conversion module can detect very weak current signal, the sampling speed will be relatively slow. The voltage resolution of the smallest 12 bit DAC in this system is only 1.2MV, and there are problems in the accuracy of the electrochemical test method of voltage change. Therefore, more advanced microprocessors (such as STM32) can be matched with 16 bit D / a conversion chip to achieve more accurate measurement.
The detection indicators of the system are few. At present, it can only detect glucose and uric acid. There are still many indicators in the routine urine examination in the hospital. It is necessary to prepare electrochemical sensors suitable for multiple index detection, and upgrade the functions of hardware circuit and software program. Due to time constraints, the system is still in the prototype stage of the laboratory, which can verify the urine of healthy adult men. More experiments need to be carried out on more disabled elderly people in hospitals or nursing institutions.
The connection between the detection device and the smart phone can only be connected through the LAN. When uploading data, the application needs to disconnect the connection with the detection device and use the wan to transmit and query data. Therefore, in the later research, the detection device can connect to the Internet through wireless module and gateway to realize data cloud. Through a long time and a large number of equipment data collection, the use of big data analysis algorithm can predict the physical condition of users.
Compared with traditional urine analysis instruments, intelligent adult pull-ups and paper-based incontinence sensing systems are smaller, easy to operate and low cost. The experimental results show that the system has high accuracy, sensitivity and selectivity in the detection of glucose and uric acid. The smartphone can receive the test results within seconds of the wearer's urination and upload them to the server. The system can also help researchers reveal the relationship between certain diseases and various disease markers in urine.
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