ISR-AIWALKER: Robotic Walker for Intuitive and Safe Mobility Assistance and Gait Analysis

Robotic walkers are assistive robotic devices that provide mobility assistance, in a domestic or clinical scenario, to individuals suffering from a gait disorder, being age related or due to injuries, surgery, or diseases. Walkers also provide a significant potential for lower limb rehabilitation. In this paper, we present a novel multimodal robotic walker platform, the ISR-AIWALKER, where innovative contributions were made both in the human- machine interface (HMI) and in a gait analysis system placed on board the platform. Taking into account the application potential of these devices, an effort was made to use low-cost sensors without sacrificing the overall performance of the system. A change was made in the HMI paradigm, moving from a force-sensing to a vision-based approach, while maintaining a natural user interaction and adding complementary safety features like correct gripping enforcement. To cope with the close proximity of the user's body, a multimodal sensor setup was considered. Using both RGB and depth map data, a kinematic model of the user's lower limbs is obtained, allowing the identification of a set of features that are used in a machine learning approach to discriminate gait asymmetries. Experiments made with several subjects revealed that the proposed HMI is able to correctly estimate the user intention in a natural and intuitive way. The gait analysis system was also evaluated and evidenced a good discrimination capability to distinguish between different gait patterns.