Fuzzy Logic Implementation in Patient Monitoring System for Lymphatic Treatment of Leg Pain

Abstract

Leg pain occurs in many people nowadays due to today's lifestyle. This leads to various treatments for leg pain with an unprecedented monitoring system. However, there are some issues regarding the existing leg pain treatments concerning a suitable monitoring procedure. The first issue is the treatment method, where most treatments for leg pain use compression. Still, they are costly, time-consuming, and cumbersome, requiring patients to visit hospitals regularly and affecting patients' compliance to continue with treatments. The second issue is the treatment period for leg pain within a short time frame, whereby it is difficult to see the major effect of a certain treatment. The third issue is the lack of a system to monitor patient's rehabilitation progress to increase patients' confidence to continue treatment consistently to cure their leg pain. Therefore, a patient monitoring system needs to be developed to cover existing research issues under the main area of health informatics. This system will apply the double-loop feedback theory that includes the agile framework to continue the process. The double-loop framework will ensure all the problems and preferred modifications will undergo a simultaneous fixation once each development segment is completed. This patient monitoring system is a computational intelligence system that focuses on fuzzy logic, producing a decision-making outcome based on collected data. This process aims to perform a valid treatment analysis as accurately as possible. Its development is significant for the national agenda as it falls under the national research priority area of health and medicine. The expected outcome would be introducing a computational intelligence inpatient monitoring system for lymphatic treatment of leg pain based on double-loop feedback theory.