چكيده به لاتين
Nowadays, calculating the angle of the body joints has many uses in the field of medicine and sports, such as physiotherapy, sports training in various fields. One method of estimating joints is to use inertial sensors. The advantage of this method over other methods such as video processing is the cheapness of these sensors. In this project, first, the methods of estimating the angle of the joints that have been done so far are reviewed. The problem with this method is the low accuracy of measurements by MEMS inertial sensors, which have errors such as bias and scale factor. As a result, the presence of these errors in the sensors will reduce the accuracy of the estimate. For this reason, an algorithm for online estimation of the bias of MEMS inertial sensors is presented, which is added to one of the algorithms and leads to the elimination of the measurement bias and thus increases the accuracy of calculating angles by the system. Then, the angle of the joints is estimated using a neural network, which is much more accurate than the methods presented so far. In addition, in the neural network algorithm, only one accelerometer sensor is used, while in other algorithms, at least the accelerometer and gyroscope must be used, and this is another advantage of the neural network. Using a neural network to estimate the angle of the joints is a new method. The accuracy of angle estimation by neural network method is also evaluated by the number of neurons and different training algorithms.
