S. Ranka et al. (Eds.): IC3 2010, Part I, CCIS 94, pp. 340–349, 2010. © Springer-Verlag Berlin Heidelberg 2010 A Framework for Synthesis of Human Gait Oscillation Using Intelligent Gait Oscillation Detector (IGOD) Soumik Mondal, Anup Nandy, Anirban Chakrabarti, Pavan Chakraborty, and G.C. Nandi Robotics & AI Lab, Indian Institute of Information Technology, Allahabad {soumik,anup,anirban,pavan,gcnandi}@iiita.ac.in Abstract. The main objective of this paper illustrates an elementary concept about the designing, development and implementation of a bio-informatics diagnostic tool which understands and analyzes the human gait oscillation in order to provide an insight on human bi-pedal locomotion and its stability. A multi sensor device for detection of gait oscillations during human locomotion has been developed effectively. It has been named “IGOD”, an acronym of the “Intelligent Gait Oscillation Detector”. It ensures capturing of different person’s walking pattern in a very elegant way. This device would be used for creating a database of gait oscillations which could be extensively applied in several im- plications. The preliminary acquired data for eight major joints of a human body have been presented significantly. The electronic circuit has been attached to IGOD device in order to customize the proper calibration of every joint angle eventually. Keywords: Intelligent Gait Oscillation Detector, Bio-informatics, Bi-pedal locomotion, Human gait oscillation, Lissajous curve. 1 Introduction Learning to walk is a daunting task for a human baby. It takes close to a year for a human baby to stand on its two legs, balance and then learn to walk. The human bi- pedal locomotion, which we commonly known as simple “walking”, involves a high amount of balancing and stability along with complex synchronous oscillation of its different joints of the body. These oscillations not only provide the required motion, but also the stability and balance. A combination of rhythmic activities of a nervous system composed of coupled neural oscillators and the rhythmic movements of a musculoskeletal system including interaction with its environment [1] produces the stable gait. An in depth study the human bipedal motion through different oscillations of its body limbs holds great potential in understanding the dynamic human body. It is to be noted, that the upper body oscillation is in synchronicity with the lower body to pro- vide a smooth and stable gait cycle. Our aim is to acquire these oscillation angles of different limbs of the human body, in real time. There have been many attempts in acquiring the limb movements for training hu- manoid robots. One such method is using image processing on real time video. Su and