A Survey of Applications and Human Motion Recognition with Microsoft Kinect

Microsoft Kinect, a low-cost motion sensing device, enables users to interact with computers or game consoles naturally through gestures and spoken commands without any other peripheral equipment. As such, it has commanded intense interests in research and development on the Kinect technology. In this paper, we present, a comprehensive survey on Kinect applications, and the latest research and development on motion recognition using data captured by the Kinect sensor. On the applications front, we review the applications of the Kinect technology in a variety of areas, including healthcare, education and performing arts, robotics, sign language recognition, retail services, workplace safety training, as well as 3D reconstructions. On the technology front, we provide an overview of the main features of both versions of the Kinect sensor together with the depth sensing technologies used, and review literatures on human motion recognition techniques used in Kinect applications. We provide a classification of motion recognition techniques to highlight the different approaches used in human motion recognition. Furthermore, we compile a list of publicly available Kinect datasets. These datasets are valuable resources for researchers to investigate better methods for human motion recognition and lower-level computer vision tasks such as segmentation, object detection and human pose estimation

HUMAN ACTIVITY TRACKING AND RECOGNITION USING KINECT SENSOR

The objective of this dissertation research is to use Kinect sensor, a motion sensing input device, to develop an integrated software system that can be used for tracking non-compliant activity postures of consented health-care workers for assisting the workers\u27 compliance to best practices, allowing individualized gestures for privacy-aware user registration, movement recognition using rule-based algorithm, real-time feedback, and exercises data collection. The research work also includes developing a graphical user interface and data visualization program for illustrating statistical information for administrator, as well as utilizing cloud based database system used for data resource

A Survey of Applications and Human Motion Recognition with Microsoft Kinect

Microsoft Kinect, a low-cost motion sensing device, enables users to interact with computers or game consoles naturally through gestures and spoken commands without any other peripheral equipment. As such, it has commanded intense interests in research and development on the Kinect technology. In this paper, we present, a comprehensive survey on Kinect applications, and the latest research and development on motion recognition using data captured by the Kinect sensor. On the applications front, we review the applications of the Kinect technology in a variety of areas, including healthcare, education and performing arts, robotics, sign language recognition, retail services, workplace safety training, as well as 3D reconstructions. On the technology front, we provide an overview of the main features of both versions of the Kinect sensor together with the depth sensing technologies used, and review literatures on human motion recognition techniques used in Kinect applications. We provide a classification of motion recognition techniques to highlight the different approaches used in human motion recognition. Furthermore, we compile a list of publicly available Kinect datasets. These datasets are valuable resources for researchers to investigate better methods for human motion recognition and lower-level computer vision tasks such as segmentation, object detection and human pose estimation

Rule Based Realtime Motion Assessment for Rehabilitation Exercises

In this paper, we describe a rule based approach to realtime motion assessment of rehabilitation exercises. We use three types of rules to define each exercise: (1) dynamic rules, with each rule specifying a sequence of monotonic segments of the moving joint or body segment, (2) static rules for stationary joints or body segments, and (3) invariance rules that dictate the requirements of moving joints or body segments. A finite state machine based approach is used in dynamic rule specification and realtime assessment. In addition to the typical advantages of the rule based approach, such as realtime motion assessment with specific feedback, our approach has the following advantages: (1) increased reusability of the defined rules as well as the rule assessment engine facilitated by a set of generic rule elements; (2) increased customizability of the rules for each exercise enabled by the use of a set of generic rule elements and the use of extensible rule encoding method; and (3) increased robustness without relying on expensive statistical algorithms to tolerate motion sensing errors and subtle patient errors

Rule Based Realtime Motion Assessment for Rehabilitation Exercises

In this paper, we describe a rule based approach to realtime motion assessment of rehabilitation exercises. We use three types of rules to define each exercise: (1) dynamic rules, with each rule specifying a sequence of monotonic segments of the moving joint or body segment, (2) static rules for stationary joints or body segments, and (3) invariance rules that dictate the requirements of moving joints or body segments. A finite state machine based approach is used in dynamic rule specification and realtime assessment. In addition to the typical advantages of the rule based approach, such as realtime motion assessment with specific feedback, our approach has the following advantages: (1) increased reusability of the defined rules as well as the rule assessment engine facilitated by a set of generic rule elements; (2) increased customizability of the rules for each exercise enabled by the use of a set of generic rule elements and the use of extensible rule encoding method; and (3) increased robustness without relying on expensive statistical algorithms to tolerate motion sensing errors and subtle patient errors

A Kinect-Based Rehabilitation Exercise Monitoring and Guidance System

In this paper, we describe the design and implementation of a Kinect-based system for rehabilitation exercises monitoring and guidance. We choose to use the Unity framework to implement our system because it enables us to use virtual reality techniques to demonstrate detailed movements to the patient, and to facilitate examination of the quality and quantity of the patient sessions by the clinician. The avatar-based rendering of motion also preserves the privacy of the patients, which is essential for healthcare systems. The key contribution of our research is a rule-based approach to realtime exercise quality assessment and feedback. We developed a set of basic rule elements that can be used to express the correctness rules for common rehabilitation exercises

A Kinect-Based Rehabilitation Exercise Monitoring and Guidance System

In this paper, we describe the design and implementation of a Kinect-based system for rehabilitation exercises monitoring and guidance. We choose to use the Unity framework to implement our system because it enables us to use virtual reality techniques to demonstrate detailed movements to the patient, and to facilitate examination of the quality and quantity of the patient sessions by the clinician. The avatar-based rendering of motion also preserves the privacy of the patients, which is essential for healthcare systems. The key contribution of our research is a rule-based approach to realtime exercise quality assessment and feedback. We developed a set of basic rule elements that can be used to express the correctness rules for common rehabilitation exercises

A Privacy-Aware Kinect-Based System for Healthcare Professionals

In this paper, we present a novel system for healthcare professionals to enhance their compliance with best practices and regulations using Microsoft Kinect sensors and smart watches while strictly protecting patient privacy. A core contribution of this study is a registration mechanism for a healthcare professional to explicitly give our system the permission to monitor his or her activities. Our system supports the use of multiple Kinect sensors for improved tracking accuracy and better coverage for large workplaces. Furthermore, we introduce a non-intrusive biometrics-based single sign-on mechanism to allow a user to register once for all Kinect sensors within each session. Finally, our system generates alerts reliably on detection of non-compliant activities and delivers the alerts discreetly to a consented healthcare professional via a designated smart watch according to his/her personal preference