Optimization Based Prediction of Human Gait A Feasibility Study to Examine the Use of Simple Mathematical Models and devices to Predict and Explain Normal and/or Pathological Gaits

The central aim of this work is build simple models that can be used to predict and explore the role of the trunk in walking and running especially when walking uphill or downhill or when speeding up or slowing down. The other aim is to investigate the use of portable devices and sensors fitted to the trunk that enables one to detect walking (running) events and phases, such as heel strike, ankle push-off, and stance phase. Evaluation of these time and special parameters during walking is helpful in assessing normal and abnormal gaits. The proposed methodology is based on optimization formulation that minimizes a given andldquo;cost functionandrdquo; (say the metabolic cost of transport or/and the effort on a particular joint) of the biped while considering associated physical and kinematic constraints. The first part of the study will be to choose a reasonable model that captures the characteristic of walking but yet simple enough to allow deeper understanding of the mechanics of walking. Some preliminary results as reported in [35,36]; were achieved based on a project funded by SQU under code number IG/ENG/MIED/12/01. The work as such will take about 3 years and will have a funded MSc student as well as a research assistant (RA). The RA is to work on the experimental setup and developing of the portable devices that can be used to detect gait status and events. The MSc student will work on developing the simple models needed to study the role that the trunk (torso) plays during walking (for both normal and certain classes of abnormal gaits).