Aplikasi Deteksi Orang Jatuh Dengan Memanfaatkan Kinect

This paper describes method for fall detection, because fall is a serious problem and often resulting to injury, which can endanger the safety of the person. Therefore, falling detection is crucially needed. The device that being used is Kinect, which also could be used to detect people. The detection is using the help of Microsoft Kinect SDK. Kinect can detect a person in front of it and processing it to create a skeleton of the person. The method which being used is to get a set of data on the position of the person. Next, the rate of change in position would be calculated with the available formulae. The data obtained would be selected, in order to distinguish the activities undertaken. When fall is detected, the application can provide the alert

Design and implementation of an inductive-based human postures recognition system

This paper describes the design and implementation of an inductive-based human postures recognition system during Muslim prayers or ‘Solat’. Inductive sensors are preferred over contact sensors as they allow remote detection of postures. An array of inductive sensors are placed underneath a prayer mat to sense four different postures namely Woquf, Rokoo, Sojod and Qood. Each inductive proximity sensor comprises of a modified inductive loop, with inner and outer loops and three capacitors. The design of the sensing circuit was simulated using both MATLAB and Multisim. Nine identical sensors, with each sensor placed on a different zone on the prayer mat, are connected in parallel to a ChipKit Max32 development board. The sensors send analog signals that are digitized by the board and sent to a PC as frequency plots. Posture identification was done by analyzing the triggered zones. Experimental results are in agreement with both the analytical and simulation results and can successfully distinguish the different postures remotely

DEVELOPMENT OF A TELEREHABILITATION SOLUTION FOR REMOTE MONITORING AND CARE

Ph.DDOCTOR OF PHILOSOPH

Kires: a data-centric telerehabilitation system based on kinect

185 p.It is widely accepted that the worldwide demand for rehabilitation services. To meet these needs, there will have to be developed systems of telerehabilitation that will bring services to even the most remote locations, through Internet and related technologies.This thesis is addressing the area of remote health care delivery, in particular telerehabilitation. We present KiReS; a Kinect based telerehabilitation system which covers the needs of physiotherapists in the process of designing, managing and evaluating physiotherapy protocols and sessions and also covers the needs of the users providing them an intuitive and encouraging interface and giving useful feedback to enhance the rehabilitation process. As required for multi-disciplinary projects, physiotherapists were consulted and feedback from patients was incorporated at different development stages.KiReS aims to outcome limitations of other telerehabilitation systems and bring some novel features: 1) A friendly and helpful interaction with the system using Kinect and motivational interfaces based on avatars. 2) Provision of smart data that supports physiotherapists in the therapy design process by: assuring the maintenance of appropriate constraints and selecting for them a set of exercises that are recommended for the user. 3) Monitoring of rehabilitation sessions through an algorithm that evaluates online performed exercises and sets if they have been properly executed. 4) Extensibility, KiReS is designed to be loaded with a broad spectrum of exercises and protocols

KinectMotion: monitorização de actividades usando a Kinect

Mestrado em Engenharia de Computadores e TelemáticaCom o crescimento da população envelhecida numa escala global, todos os dias os meios de comunicação noticiam acidentes domésticos como quedas ou mesmo problemas de saúde que requerem atenção urgente. A população envelhecida a viver sozinha está inclinada para este tipo de emergências devido ao seu estatuto. Soluções como a Kinect da Microsoft oferecem características online avançadas que permitem a detecção automática de esqueletos entre outras. Embora a Kinect seja mais usada em aplicações de jogos/lazer é viável questionar se funciona como uma solução apropriada para monitorização doméstica de baixo custo. Nesta dissertação exploramos a utilização da extração de esqueleto automática que esta disponibiliza para suportar uma solução online de monitorização num ambiente de uma divisória que é capaz de detectar situações criticas e identificar situações típicas como quedas, sentar ou deitar. Usando técnicas simples de processamento de sinal (como filtros passa-baixo ou transformações de potencia) fomos capaz de conceber uma solução simples e fiável – KinectMotion. KinectMotion é capaz de alertar situações criticas e detectar alterações típicas de postura numa janela temporal de 3 segundos. Na nossa avaliação sobre uma população de 6 jovens voluntários o algoritmo exibiu valores de precisão sempre superiores a 80% com um número reduzido de falsos alarmes (i.e. falsos positivos). Embora o algoritmo encontrado seja promissor necessita ser adaptado para ser aplicada à monitorização de idosos pois existem diferenças nomeadamente no desempenho motor.With the growth of the elderly population in a global scale, every day the media reports home accidents like falls or even health problems that require urgent attention. The elderly population living alone is prone to these kinds of emergencies given their status. Solutions such as Microsoft’s Kinect’s offer advance online features that enable automated skeleton extraction among other things. Although Kinect is most commonly used in gamming/leisure applications it is reasonable to ask if it provides a suitable and cost effective solution for home monitoring scenario. In this dissertation we explore the use of Microsoft’s Kinect’s automated skeleton extraction to support an online monitoring solution that is able to detect critical situations in a room environment and identify typical events such as falls, sitting, lying down. Using a simple signal processing techniques (e.g. low pass filtering and power transforms) we were able to provide a simple and reliable solution – KinectMotion. KinectMotion is able to able to alert to critical situations and detect typical posture changes within a time window of less than 3 seconds. In our evaluation over a population of 6 healthy young volunteers the algorithm used showed always precisions above 80%, presenting always a very low number of false alarms (i.e. false positives). Although our algorithm is promising it must be adapted to be applied to elderly monitoring as there are differences namely on motor performance

Advanced background modeling with RGB-D sensors through classifiers combination and inter-frame foreground prediction

An innovative background modeling technique that is able to accurately segment foreground regions in RGB-D imagery (RGB plus depth) has been presented in this paper. The technique is based on a Bayesian framework that efficiently fuses different sources of information to segment the foreground. In particular, the final segmentation is obtained by considering a prediction of the foreground regions, carried out by a novel Bayesian Network with a depth-based dynamic model, and, by considering two independent depth and color-based mixture of Gaussians background models. The efficient Bayesian combination of all these data reduces the noise and uncertainties introduced by the color and depth features and the corresponding models. As a result, more compact segmentations, and refined foreground object silhouettes are obtained. Experimental results with different databases suggest that the proposed technique outperforms existing state-of-the-art algorithms

Computer-based application to assess gross motor skills using Microsoft Kinect sensor

The performance of a fundamental motor skill in early childhood can be investigated using diverse assessment tools. Although the classical tests are reliable and useful for motor skills assessment, they have some limitations. The launch of the Microsoft Kinect marked a revolutionary advancement for developers thanks to the depth camera and its affordable price. This work aims to develop a reliable computer-based application using the Microsoft Kinect sensor to implement the third version of the Test of Gross Motor Development (TGMD-3). The assessment consists of customized algorithms that verify if the 3D position of the most relevant joints for each subtest varies along time according to the respective performance criteria. The proposed system returns an immediate feedback to the participant, indicating if s/he passes or fails the selected subtest. The results revealed the computer-based application for assessing gross motor skills is accurate, although it is limited by the space requirements.Master of Applied Science (MASc) in Natural Resources Engineerin

Obstacle Avoidance in Intelligent Assisted Walking Devices for Improving Mobility Among Seniors with Cognitive and Visual Impairments

Current research in walkers and rollators with integrated intelligent computing and robotic components shows promise in treatment, management and rehabilitation of a variety of ailments and disorders such as stroke, Alzheimer disease and multiple sclerosis. In this thesis a novel intelligent walker is designed, constructed and tested for the purpose of examining whether we can increase mobility among individuals with vision and cognitive impairments hindering their ability to move collision free about their environments, by detecting obstacles and using brakes to guide the user around them. This walker consists of a support frame, front castor wheels and rear particle brakes. Obstacle detection and localization are sensed by an onboard 3D depth camera and RGB camera (The Microsoft Kinect) and encoders in the rear wheels. This data is processed by an onboard laptop, producing a 2-dimensional map of the environment. This map is inputted into the control algorithms to make braking decisions for obstacle avoidance. Two control algorithms are presented. The first is an open loop proportional gain control which determines necessary braking torque directly from the distance to the nearest obstacle. The second is a closed loop control which uses the systems dynamics and velocity data from the wheel encoders to estimate the forces being applied by the user and calculates the braking torque necessary to avoid obstacles. The walker moment of inertia and the viscous damping parameters of the system are estimated experimentally. The effect of varying three parameters in the closed loop algorithm and one parameter in the open loop algorithm are examined in a corner turning test. Observations support predictions made by the derived system dynamics. Lastly, the efficiency of the system at real world obstacle avoidance is tested in a controlled indoor obstacle course using goggles to impair the vision of otherwise able bodied test subjects. The open loop control algorithm was found to reduce the occurrence of collisions by 44% as compared to trials with no braking. The closed loop control algorithm was found to greatly reduce collisions with the front of the walker, however shows a tendency for over steering the user, producing a higher number of collisions with the walker's side. Possible causes and solutions to this problem are discussed. This thesis demonstrates promise in the approach of using braking to help walker users avoid collisions with their environments. Discussion is offered about necessary next steps towards testing with regular users of assisted walking devices, and eventually real world use

Interaction for creative applications with the Kinect v2 device

Human-Computer Interaction (HCI) is a multidisciplinary field of research that designs, evaluates and implements interactive ways of communication between computer systems and people. The evolution of different technologies in the last decades has contributed to the expansion of HCI into other fields of study as computer vision, cognitive science, psychology, industrial design, and also into interactive art. The present document contains a case of HCI in the context of interactive art. In a first step we analyse what kind of interaction can be achieved with the available equipment: a range imaging camera, a computer and a video projector. Then, three range imaging techniques capable of fulfilling our objective are studied and some devices available for purchasing and based on these techniques are compared. Thereafter, we study and compare the two acquired range imaging devices: the Kinect for Windows v1 and the Kinect for Windows v2. In a later step we build our interaction system with the Kinect for Windows v2 and we test it. We use Processing as a programming environment in order to apply creative coding and to try the different types of interaction that this device allows. Finally, with the experience gained in the previous studies and in these test, we present three final interactive programs

The development and evaluation of virtual reality-based training on performance and rehabilitation outcomes

Sports injuries are types of injuries that usually occur during sports, training, or exercise. Sports injuries often result from poor training methods, inappropriate equipment, lack of fitness, insufficient warm-up, and trauma (Salerno, 2009). Knee injuries are considered one of the most common injuries in athletes and include a large part of the cost of medical care for sports injuries (Loes et al., 2000; Sancheti et al., 2010). The ACL is the most common knee ligament injury in rugby, soccer, ski, volleyball, gymnastics, and basketball players due to quick deceleration movements such as landing, pivoting, cutting, and changing direction in these sports. Despite increased knowledge of ACL injury mechanisms, rehabilitation programmes and surgical techniques, the rates of return-to-sport (RTS) and the subsequent ACL re-injury after ACL reconstruction (ACLR) are not optimal (Buckthorpe, 2019). Therefore, rehabilitation plays a significant role in helping athletes return to sports activities, and inappropriate rehabilitation can even devastate a satisfactory ACLR (Wright et al., 2015). This dissertation consists of two studies, including a systematic review in Chapter 2 that explores the research conducted on the application of immersive technologies for improving the outcome of the rehabilitation phases after ACL reconstruction and examines the correlation between virtual reality, rehabilitation, exercise therapy, and sport-related ACL injuries in patients. The second study in Chapter 3 validates the Microsoft Azure Kinect camera for body tracking of dynamic movements against the gold standard Qualisys system. The findings indicated that VR-based systems could be a considerable alternative to real-world training to improve certain aspects of athletic performance because immersive technologies effectively offer a tool to control virtual environmental features. Finally, immersive technologies and VR-based systems are still in their infancy and will need considerable improvements in the future. Therefore, further research needs to be conducted in a theoretical frame to acknowledge the profitability of VR interventions in sports performance and rehabilitation programmes. The triple Azure Kinect system provides a consistent track of the joint centres' displacements with good to excellent agreement in the vertical and AP direction during the squat exercise in all joints except the ankles, particularly in upper joints such elbow and shoulder. However, future investigations must be conducted to acknowledge the Azure Kinect's profitability in the assessment of abnormal clinical conditions and the limits of Kinect's accuracy in various movements and planes of motion. In conclusion, the markerless triple Azure Kinect motion capture system may be a considerable alternative to a gold standard Qualisys marker-based system for specific applications such as human activities in the frontal plane. However, future investigations must be conducted to acknowledge the Azure Kinect's profitability in the assessment of abnormal clinical conditions and the limits of Kinect's accuracy in various movements and planes of motion