Fuzzy Model for Back Posture Correction During the Walk

Abstract

The body posture is not a purely aesthetic problem, due to it can produce a multitude of adverse effects on health, even extremities disorders (injuries) and malfunction of organs. This study focuses on the correct and incorrect detection of the position of the spine and extremities while walking. A database of three patients with lumbago and sciatica, with diagnosis of muscle tension due to poor posture while walking, has been used in this article. These patients underwent physiotherapy treatment and were later filmed taking a short walk of 2 min to see the results. This process was developed for a period of 4 weeks, divided into 2 h of physiotherapy per week and 1 h of compilation of videos with the results obtained. To detect the correct movement of each of the patients, the Kinect Xbox One device was used. It identifies all body points, alignment, speed and angles during the walk. 25 points of human body in three dimensions are detected in real time by the Kinect, which allows to generate a data collection in real time and more efficiently. With the database of patients, a pre-processing of the information is done to identify the most relevant points for our study. A fuzzy model is generated which determines maximum and minimum thresholds for the posture of the back (angle of inclination), shoulders posture (shoulders inclination with respect to the spine), head posture (inclination with respect to horizontal vision) and movement of arms. The model dynamically identifies which position is correct for the movement during the walk, and in addition, the progress that is generated during a time series. This prototype detector is used for rehabilitation of high-performance athletes and is an approximation for the correct posture during long and medium distance races, jumps, among other sports that use the walk as a basis in their workouts. This study was based on the solution of back problems in clinical patients. These preliminary tests have given excellent results in the testing phase, which validates it as an option to prevent injuries in patients with these conditions.