nunoguedelha / mapest

Maximum A Posteriori estimation for human experiments.

MAPest

MAPest (Maximun-A-Posteriori estimation) is a probabilistic tool for estimating dynamics variables in humans. For a detailed theoretical description see in the paper: Latella, C.; Kuppuswamy, N.; Romano, F.; Traversaro, S.; Nori, F. Whole-Body Human Inverse Dynamics with Distributed Micro-Accelerometers, Gyros and Force Sensing. Sensors 2016, 16, 727, http://www.mdpi.com/1424-8220/16/5/727.

The code in this repository works only off-line and to solve the problem of the estimation of human dynamics you need to have a dataset of different measurements coming from sensors. For the moment the repository consists of two type of experiments:

1. 1st experiment (2dofBowingTask): where we consider a very simplified human model with 3 link and 2 Dofs and a sensor architecture composed by the Vicon motion capture + an IMU + one forceplate;
2. 2nd experiment (23links_human): where the model is composed by 23 links and for the sensor structure by the Xsens suit + two forceplates.

Detailes on the experiments in the README of each related Section.