KinFit: A factual aerobic sport game with stimulation support

Overweight and obesity is a situation where a person has stacked too much fat that might affect negatively his/her health. Many people skip doing exercises due to several facts related to the encouragement, health-awareness, and time arrangement. Diverse aerobic video games have been proposed to help users in doing exercises. However, we observe some limitations in existing games. For instance, they don't give correct scores while wearing Arabic traditional suits, they don't consider showing immersive realistic scenes, and they don't stimulate users to do exercises and keeping them encouraged to play more. We propose in this paper an aerobic video game that displays real scenes of aerobic coaches and keeps the user notified about doing exercises. It is a kind of serious games that allows users to learn aerobic movements and practice with aerobic coaches. It contains several exercises in which each can be played on normal screen or in fully immersive virtual reality (VR). While the user is playing, he/she can see the playing score with the estimated amount of burned calories. It stores the time when the user plays to remind him/her about doing exercises again. The profound user studies demonstrated the usability and effectiveness of the proposed game. 2018 Kassel University Press GmbH.The authors would like to acknowledge that devices and equipment were provided by the Visual Computing Research Center, Department of Computer Science and Engineering, at Qatar University. This publication was supported by Qatar University Collaborative High Impact Grant QUHI-CENG-18/19-1. The content of this article and its quality are solely the responsibility of the authors and do not necessarily represent the official views of Qatar University.Scopu

Motion Capture for Telemedicine: A Review of Nintendo Wii, Microsoft Kinect, and PlayStation Move

Access to healthcare has been and continues to be difficult for many around the world. With the introduction of telemedicine, this impediment to attaining medical care has been lifted. Although many avenues of telemedicine exist (and have yet to exist), the use of home video game consoles such as the Nintendo Wii®, Microsoft Kinect®, and PlayStation Move® can be used to measure patient progress outside of the office. Due to the nature of each individual console/system, some unique characteristics exist that allow each system to provide its own clinical potential. A comparative analysis of the clinical implications of the Nintendo Wii®, Microsoft Kinect®, and PlayStation Move® showed that with its ease of use and dynamic accuracy, the Microsoft Kinect® offered the most benefit. With further exploration, using the Microsoft Kinect® for telemedicine will be able to improve medical efficiency and hopefully health outcomes

Remote Biofeedback Method for Biomedical Data Analysis

In recent years, the introduction of methods supported by technology has positively modified the traditional paradigm of rehabilitation. Interactive systems have been developed to facilitate patient involvement and to help therapist in patient\u2019s management. ReMoVES (REmote MOnitoring Validation Engineering System) platform addresses the problem of continuity of care in a smart and economical way. It can help patients with neurological, post-stroke and orthopedic impairments in recovering physical, psychological and social functions; such system will not only improve the quality of life and accelerate the recovery process for patients, but also aims at rationalizing and help the manpower required monitoring and coaching individual patients at rehabilitation centers. In order to help and support therapist work, the Remote Biofeedback Method is proposed as an instrument to understand how the patient has executed the rehabilitation exercises without seeing him directly. Therefore, the purpose of this method is to demonstrate that through the joint observation of data from simple sensors, it is possible to determine: time and method of execution of the exercises, performance and improvements during the rehabilitation session, pertinence of exercise and plan of care. The system, during the rehabilitation session, automatically transmits patient\u2019s biofeedback through three different channels: movement, physiological signals and a questionnaire. The therapist uses patient\u2019s data to determine whether the plan of care assigned is appropriate for the recovery of lost functionalities. He will then return a remote feedback to the patient who will not see any kind of graphical or verbal output, but you will see lighter rehabilitative session if it was too difficult or more intense if one assigned was too simple. The rehabilitation protocol proposed consists of the performance of different exercises, which begins with a breathing activity, designed to relax the patient before the \u201ceffective\u201d rehabilitation session. To make the subject comfortable, and to bring again the heartbeat to a basal value, before the rehabilitation session, the patient, in a sitting position, is leading to breathing with a regular rhythm by following a \u201cbreath ball\u201d. From the results obtained in the breathing exercise, it can be concluded that the negative trend of the regression line that approximates the heartbeat signal is an index of relaxation, principal goal for which the exercise was designed. The proposed activities include execution of reaching and grasping, balance and control posture functional exercises, masked through serious games to simulate some of the most common gestures of daily life. In some exercises, a cognitive component will also be involved in achieving the goal required by the activity. For each activity, heart rate, gameplay scores, and different motion parameters were captured and analyzed depending on the type of exercise performed. The heart rate was used as an indicator of motivation and involvement during the execution of several rehabilitative exercises. Others parameters analyzed are the score obtained during the execution of the task, and the time interval between the execution of one exercise and the following one. In addition to the analysis of the individual signals, a preliminary analysis of the correlation between the trend of the heart rate and the performance of the score was also carried out. The results showed that heartbeat in conjunction with score and inter-exercise time could be a high-quality indicator of a patient\u2019s status. The indicators extracted, in fact, in most cases, correspond to the information reported from the therapist who observed the patients during the rehabilitation session. A deep analysis of movement signal was carried on, with the extraction of several indicators for the different body segments involved in rehabilitation, such as the upper limb, the hand, the lower limbs and the posture, included the detection of compensation strategies to reach the targets proposed by the exercise. The results have been extracted by comparing the patient performance to a model extracted by a healthy subjects group. Of particular importance is the spatial map for patients with neglect, an innovative tool that traces the positions where the movement was performed and also provides the therapist with the spatial coordinates where the targets were proposed. Another innovative aspect is the analysis of Center of Pressure (CoP) without the use of a specific footboard, but only through the processing of data from the motion sensor. The results obtained by the application of the Remote Biofeedback Methods to the signals acquired during ReMoVES testing phase show interesting applications of the method to the clinical practice. In fact, the indicators extracted show a realistic correspondence between the disabilities affected the patients and the performance obtained during the execution of the exercises. From the study of the different exercises it can be concluded that the analysis of the signals and the parameters extracted individually, do not provide enough information to outline how the rehabilitation exercise has been executed. By combining the different indicators, it is possible to outline an accurate picture that allows the therapist to make decisions about the assigned plan of care. In conclusion, the Remote Biofeedback Method proposed is now ready to be tested on a wider dataset in order to be consolidated on a larger number of athologies and to associate, if necessary, particular indicators to a particular disease. The future steps will be, a creation of a model starting from patients signals, in order to have a better comparison term, and a testing phase on a larger number of patients, following a clinical protocol, subdividing subject by disease

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

Coaching or gaming? Implications of strategy choice for home based stroke rehabilitation

Background: The enduring aging of the world population and prospective increase of age-related chronic diseases urge the implementation of new models for healthcare delivery. One strategy relies on ICT (Information and Communications Technology) home-based solutions allowing clients to pursue their treatments without institutionalization. Stroke survivors are a particular population that could strongly benefit from such solutions, but is not yet clear what the best approach is for bringing forth an adequate and sustainable usage of home-based rehabilitation systems. Here we explore two possible approaches: coaching and gaming. Methods: We performed trials with 20 healthy participants and 5 chronic stroke survivors to study and compare execution of an elbow flexion and extension task when performed within a coaching mode that provides encouragement or within a gaming mode. For each mode we analyzed compliance, arm movement kinematics and task scores. In addition, we assessed the usability and acceptance of the proposed modes through a customized self-report questionnaire. Results: In the healthy participants sample, 13/20 preferred the gaming mode and rated it as being significantly more fun (p < .05), but the feedback delivered by the coaching mode was subjectively perceived as being more useful (p < .01). In addition, the activity level (number of repetitions and total movement of the end effector) was significantly higher (p <.001) during coaching. However, the quality of movements was superior in gaming with a trend towards shorter movement duration (p=.074), significantly shorter travel distance (p <.001), higher movement efficiency (p <.001) and higher performance scores (p <.001). Stroke survivors also showed a trend towards higher activity levels in coaching, but with more movement quality during gaming. Finally, both training modes showed overall high acceptance. Conclusions: Gaming led to higher enjoyment and increased quality in movement execution in healthy participants. However, we observed that game mechanics strongly determined user behavior and limited activity levels. In contrast, coaching generated higher activity levels. Hence, the purpose of treatment and profile of end-users has to be considered when deciding on the most adequate approach for home based stroke rehabilitation

Assessing Self-Rehabilitation Strategies for the Visually Impaired in Denmark

Self-rehabilitation technology has been developed to reduce healthcare costs and provide a convenient, reliable method for patients to recover from a physical injury. Sponsored by the Danish Association of the Blind, the following report summarizes a project exploring self-rehabilitation technologies that can accommodate blind or visually impaired patients. Potential strategies to increase awareness of such devices throughout municipalities in Denmark were evaluated as well. The data collected in this project were used to recommend that the Danish Association of the Blind advocates for further development of several rehabilitation technologies and the education of healthcare professionals about these technologies throughout Danish municipalities

Quasi-Monte and Data-Driven Monte Carlo Methods for Efficient Human Joint Model Fitting

Fitting a kinematic model of the human body to an image withoutthe use of markers is a method of pose estimation that is usefulfor tracking and posture evaluation. This model-fitting is challengingdue to the variation in human physique and the large numberof possible poses. One type of modeling is to represent the humanbody as a set of rigid body volumes. These volumes can beregistered to a target point cloud acquired from a depth camerausing the Iterative Closest Point (ICP) algorithm. The speed of ICPregistration is inversely proportional to the number of points in themodel and the target point clouds, and using the entire target pointcloud in this registration is too slow for real-time applications. Thiswork proposes the use of data-driven Monte Carlo methods to selecta subset of points from the target point cloud that maintains orimproves the accuracy of the point cloud registration for joint localizationin real time. For this application, we investigate curvature ofthe depth image as the driving variable to guide the sampling, andcompare it with benchmark random sampling techniques