This research focuses on development of a multi-sensing platform for diagnosis of urinary tract stones in early stage of formation which contributes to prevention of urolithiasis. The system uses mirco-fluidic channel technology and three sensing mechanisms (potentiometric by using ion sensitive field effect transistor, amperometric by utilizing three-electrode enzyme sensing strip and conductometric that has four-electrode sensor). The system employs innovative readout circuits, digital processing system and WiFi enabled communications. Four core parameters in urine sample are measured by the system. The parameters are pH, Ca2+ ion concentration, uric acid concentration and urine conductivity. By storing the measurement results in the cloud database, such daily-based urine parameters recording from healthy individuals or patients creates valuable information that could be used for early detection of urinary tract stone and helps urine stone recurrence prevention.

The presented system allows accurate, simultaneous collection and storage of measurement tests from patients in any locations. It combines reliable measurement techniques with micro-fluidic channel and modern sensors. The reliable results are  for statistical analysis and big data modeling. The data can short period of time through the distributed systems, and to correlate the relationship between measured parameters and risk factor. It will shorten the process of diagnosis and allows early detection of disease. Early prediction  to show the major symptoms will be a breakthrough in the healthcare system, especially it is through non-invasive personal care devices. There will be huge financial relief from health care system by using this home-care based system and approach.

The analysis of the big data collected by this system will ultimately provide the pattern required for early detection and prevention of kidney stone formation. The system can measure the temperature, pH and concentration of Ca2+, uric acid concentration. The total dissolved salt is measured by using conductivity biosensor. An ARM® based micro-controller with embedded ADC serves as digital back-end and control section of the system. A single-board computer is added to the system that serves as local database, graphic user interface and connectivity to the internet. The test results of this proposed system show its potential application for urolithiasis prevention. In addition, it can also be used for pet health monitoring and management system through the evaluation of urine quality.