Knee Fracture Surgery Monitoring for Advanced Post-Operative System Using IOT

An accurate assessment of joint kinematic patients, who walk with neuromuscular and musculoskeletal disorders may provide essential data regarding modifications of disease status and the efficacy of pharmacological treatments and rehabilitation regimens. This research study introduces a cost effective wearable device for monitoring the long term conditions of joint kinematics patients. The respective data are taken from 17 people, who are made to walk at three different speeds while wearing a retractable string sensor integrated with two points on different regions of the knee joint. The proposed Random Forest (RF) algorithm is used to measure the calibrated sensor inputs. Hence, a wearable device can accurately measure the flexibility of knee angles at different walking speeds during locomotion. This type of wearable technology has a potential to monitor the patients conditions, rehabilitation programmes, and improve therapeutic outcomes.