Proposed expert system
TG, knee effusion, effusion, Tightrope
EFFUSION
The proposed ES (Fig. The flowchart of the proposed ESThe main sources of knowledge for rehabilitation after ACLR were obtained from sports medicine and physiotherapist through several interviews, debates, and surveys of the Wii Fit exergames. According to the experts’ responses, the most important assessment variables for optimal rehabilitation consisted of knee effusion, TG, KFR, BESS, and MSEBT used as ES inputs.After the exergames verifying, ten exercises were chosen including; Ski Slalom, Ski Jump, Table Tilt, Table Tilt Plus, Tightrope Walk, Balance Bubble, Balance Bubble Plus, Penguin Slide, Snowboard Slalom, and Skateboard Arena with three levels of difficulty; beginner, advanced, and expert.After collecting and analyzing data of the patients by ES, preliminary calculations were carried out to determine the differences of effusion, TG, and KFR between healthy and reconstructed knees.The BESS scores were checked, the differences of Double-Leg (DL), Single-Leg (SL), and Tandem (T) from stable and unstable positions were obtained and summed up, and finally, their means were calculated (Eq. The reach distances of the MSEBT test in three directions and their mean were calculated (Eq. The ES forward-chaining strategy is an inferential method that begins with a set of known facts and generates new facts using rules that are applied to the facts. This process continues until a rule can no longer be used in the inference process [Designed rules will select Wii Fit exergames according to the patient's condition. The output of the ES is a training program based on ten selected games with its level of difficulty and duration. The rules are planned to make it possible to exercises easier form while the patient is in a poor situation. The duration and difficulty of the rehabilitation program have gradually grown to ensure that treatment progresses.The UI is intended to communicate between the user and the ES and compare the patient's condition in different sessions using graphical charts. Through this reporting system, the patient can assess his condition during the rehabilitation. Another part of the UI was the scoring system to evaluate the progress of the patient's rehabilitation during 12 sessions.According to the experts' opinions, the patients were labeled in five categories; deterioration, unchanged, low, moderate, and excellent based on their improvement by the scoring system.The ES was developed by Python version 3.6 and graphical UI by Tkinter-toolbox. The Microsoft SQL Server was used to store the data. After preliminary evaluation of the proposed ES by an experienced orthopedic surgeon and a sports physician, they expressed their satisfaction with its performance and ensuring the system’s rules validity.