Related papers: Asynchronous Averaging of Gait Cycles for Classifi…
Previous gait phase detection as convolutional neural network (CNN) based classification task requires cumbersome manual setting of time delay or heavy overlapped sliding windows to accurately classify each phase under different test cases,…
Different technologies can acquire data for gait analysis, such as optical systems and inertial measurement units (IMUs). Each technology has its drawbacks and advantages, fitting best to particular applications. The presented multi-sensor…
Human identification is one of the most common and critical tasks for condition monitoring, human-machine interaction, and providing assistive services in smart environments. Recently, human gait has gained new attention as a biometric for…
Gait recognition is a term commonly referred to as an identification problem within the Computer Science field. There are a variety of methods and models capable of identifying an individual based on their pattern of ambulatory locomotion.…
Objective: In this paper, we demonstrate the applicability of radar for gait classification with application to home security, medical diagnosis, rehabilitation and assisted living. Aiming at identifying changes in gait patterns based on…
Gait recognition is the characterization of unique biometric patterns associated with each individual which can be utilized to identify a person without direct contact. A public gait database with a relatively large number of subjects can…
Current gait analysis faces challenges in various aspects, including limited and poorly labeled data within existing wearable electronics databases, difficulties in collecting patient data due to privacy concerns, and the inadequacy of the…
Gait recognition is an important biometric technique for video surveillance tasks, due to the advantage of using it at distance. In this paper, we present a persistent homology-based method to extract topological features (the so-called…
Accelerometer signals generated through gait present a new frontier of human interface with mobile devices. Gait cycle detection based on these signals has applications in various areas, including authentication, health monitoring, and…
Walking is one of the most common modes of terrestrial locomotion for humans. Walking is essential for humans to perform most kinds of daily activities. When a person walks, there is a pattern in it, and it is known as gait. Gait analysis…
Gait recognition is a biometric technology that recognizes the identity of humans through their walking patterns. Compared with other biometric technologies, gait recognition is more difficult to disguise and can be applied to the condition…
Wearable inertial measurement units (IMUs) provide a cost-effective approach to assessing human movement in clinical and everyday environments. However, developing the associated classification models for robust assessment of…
Gait as a biometric property for person identification plays a key role in video surveillance and security applications. In gait recognition, normally, gait feature such as Gait Energy Image (GEI) is extracted from one full gait cycle.…
In this study, a gait phase classification method based on SVM multiclass classification is introduced, with a focus on the precise identification of the stance and swing phases, which are further subdivided into seven phases. Data from…
Human gait refers to a daily motion that represents not only mobility, but it can also be used to identify the walker by either human observers or computers. Recent studies reveal that gait even conveys information about the walker's…
Get-Up-and-Go Test is commonly used for assessing the physical mobility of the elderly by physicians. This paper presents a method for automatic analysis and classification of human gait in the Get-Up-and-Go Test using a Microsoft Kinect…
We introduce a novel approach to user authentication called Motion ID. The method employs motion sensing provided by inertial measurement units (IMUs), using it to verify the persons identity via short time series of IMU data captured by…
In this paper, we propose a novel gait recognition method based on a bag-of-words feature representation method. The algorithm is trained, tested and evaluated on a unique human gait data consisting of 93 individuals who walked with…
Gait based biometric aims to discriminate among people by the way or manner they walk. It represents a biometric at distance which has many advantages over other biometric modalities. State-of-the-art methods require a limited cooperation…
Human motion analysis is used in many different fields and applications. Currently, existing systems either focus on one single limb or one single class of movements. Many proposed systems are designed to be used in an indoor controlled…