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.