Gait Analysis and Classification for an Intelligent Robotic Walker

During the past decade, robotic technology has evolved considerably towards the development of cognitive robotic systems that enable close interaction with humans. Application fields of such novel robotic technologies are now wide spreading covering a variety of human assistance functionalities, aiming in particular at supporting the needs of human beings experiencing various forms of mobility or cognitive impairments. Mobility impairments are prevalent in the elderly population and constitute one of the main causes related to difficulties in performing Activities of Daily Living (ADLs) and consequent reduction of quality of life.

The motivation behind this research work stems from our vision to develop technologies that will support intelligent robotic assistive devices aiming to provide user-adaptive and context-aware mobility assistance to physically and cognitively impaired persons. To achieve such targets, a large spectrum of multimodal sensory processing and interactive control modules need to be developed and seamlessly integrated. In this context, this research focuses on the tracking, analysis and classification of human gait patterns, based on non-intrusive laser rangefinder data. Experiments are currently ongoing and results are promising demonstrating that such a framework can be used efficiently and effectively to provide user-adapted mobility assistance that can enhance the functionality of such robotic devices.



C. Tzafestas, X. Papageorgiou, G. Moustris, G. Chalvatzaki, A. Dometios,
User-Oriented Human-Robot Interaction for an Intelligent Walking Assistant Robotic Device,
Workshop IEEE/RSJ Int'l Conf. on Intelligent Robots and Systems, Invited Session: "Cognitive Mobility Assistance Robots: Scientific Advances and Perspectives", Hamburg, Germany, Sept. 28 - Oct. 02, 2015.