Human gait analysis based on automatic recognition: A review

Abstract

Gait analysis is one of the most important challenging research areas in clinical and computing settings. Gait biomechanics and gait human recognition are two major areas of interest. Alterations in walking can cause physical and metal health problems in people, so diagnoses and treatments derived from optimal gait analysis are very useful in clinical settings. This paper surveys the gait analysis methods, applications and platforms, gait biomechanics, as well as, gait recognition approaches, and datasets. Then, we describe contributions in gait forward kinematics, useful to assess gaits such as crouched and normal. Also, a framework for antalgic gait recognition based on human activity, using the gyroscope embedded in a smartphone is described. Different algorithms and metrics were used to perform the gait recognition, highlighting Support Vector Machines, Naive Bayes, k- Nearest Neighbours, and Accuracy and F-measure, respectively. Finally, we discuss the challenges and future perspectives on gait recognition.