Posts Tagged games

[Abstract] Application of Gamification Tool in Hand Rehabilitation Process

Abstract

Video games are constantly evolving and today they are one of the main types of entertainment. As we live in the digital age, the implementation of IT solutions in other areas of activity remains relevant. Today, almost all processes use IT technologies: calling a taxi, ordering food, education, shopping, and so on. The use of IT technologies in the field of medicine is not uncommon. But it’s not often that you see video games being used in this area. Video games and their development are an integral part of the IT sphere. The technologies that exist now allow us to create our own game products, which can then be implemented in other processes. This research is aimed at studying the term of “gamification”, its impact on rehabilitation processes, and the study of gamification tools and game products used in the field of medicine. In this research we propose a gamified solution for hand rehabilitation process which include 3D game that work in conjunction with the VR tool called Leap Motion. Since video games attract people with reward systems, goals and many other factors, why not to use it as a key element in process of rehabilitation? In some cases, it is more effective method rather than traditional therapy.

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[ARTICLE] An Evidence-Based Intelligent Method for Upper-Limb Motor Assessment via a VR Training System on Stroke Rehabilitation – Full Text

Abstract

Recently, virtual-reality (VR) has been an emerging technology, to this regard, it is widely employed by therapists to provide rich training tasks for the purpose of motor rehabilitation in clinics. Meanwhile, along with the progress of sensing technologies as means for the interaction with virtual environment, a large amount of data, such as motor trajectory, foot pressure or electromyography, is measured via VR-based motor training tasks and is considered as important clues for functional evaluations. However, very few study thoroughly applied the sensor-based data for motor assessment, instead, evaluation scales, such as TEMPA or Fugl-Meyer, were highly relied. In this study, a VR upper-limb motor training system was proposed for stroke rehabilitation. Clinical trials with 22 stroke patients were performed to exanimate the effectiveness of the propose VR system. Moreover, a variety of motor indicators derived via motion trajectory were proposed. Further, integrating multi-model data, such as motion trajectory, task performance and evaluation scales, machine-learning method was applied to develop evidence-based assessment models in order to evaluate upper-limb motor function. The results indicated that the proposed VR system was significantly effective for motor rehabilitation. Also, a few motor indicators were found significantly different between pre and post trials and were highly correlated with the evaluation scales. Finally, with the fusion of multi-model data, the accuracy rate of machine-learning assessment model was up to 92.72% which revealed its great potential for clinical use.

A graphical abstract for An Evidence-based Intelligent Method for Upper-limb Motor Assessment via a VR Training System on Stroke Rehabilitation.
A graphical abstract for An Evidence-based Intelligent Method for Upper-limb Motor Assessment via a VR Training System on Stroke Rehabilitation.

SECTION I.

Introduction

Stroke is one of the three leading causes of death in developed countries, accounting for about 10% of global death [1]. Stroke is the leading cause of death and adult disability in the country, and the main disability burden in middle- and high-income countries [2]. Traditional rehabilitation aims to stimulate the relevant nerve tissue of stroke patients through continuous motor training, thereby helping patients maintain the current strength of the body muscles, and restoring their ability for daily life as much as possible [3][4][5][6]. Moreover, it assesses the rehabilitation effects with evaluation scale. However, long-term motor training in regard to rehabilitation is boring and lacks real-time feedback. Further, mainstream evaluation scales, like FMA, WMFT, TEMPA, are subjective that require experienced therapists in assessing rehabilitation, which consumes a large amount of time and medical resources.

VR is a computer-based technology that allows users to interact with the simulated environments through multiple sensations and to have “real-time” feedback. Specifically, VR is able to generate a battery of training tasks targeting a variety of rehabilitation goals in the therapy. As a result, a large number of studies have been conducted on the impact of VR technology on motor rehabilitation [7][8][9][10][11][12][13]. Also, home-based VR motor training systems were proposed [14][15][16][17]. Further, a variety of gamed-based commercial devices, similar to VR characteristics, were promoted [18][19][20][21][22][23][24][25]. Results found that VR technology has significant effects on stroke rehabilitation training [26][27][28][29][30]. Moreover, the application of VR technology to stroke rehabilitation training can make the boring training process entertaining, thereby reducing the psychological burden of patients, and maintaining their long-term participation enthusiasm [31][32]. Also, it can highly handle the situation in which patients are unwilling to cooperate with traditional rehabilitation therapy [33]. The patient’s training goals can also be adjusted according to physical conditions [34].

However, the efficacy of previous VR training systems were mostly examined by evaluation scales [35][36][37][38], in spite that VR training systems were able to collect a huge amount of sensing data, such as motion trajectory, foot pressure or electromyography, which is considered as a kind of objective data. In a number of studies, the VR system was only used for motor training, and the objective training data collected by the system was not used as the basis for evaluation. The evaluation scale is mainly scored by the therapist, therefore, the data is considered as a kind of subjective data. Even though some studies [39][40][41][42][43] have intended to perform further analysis on sensing data in order to derive motor indicators to interpret the progress of motor functions, they did not discuss the correlation between proposed motor indicators and evaluation scales, lacking reliability and validity.

With the improvement of the computing power of computers, machine learning has been developed rapidly in recent years and is widely used in data mining, computer vision, natural language processing, etc. In medical diagnosis, some researchers use machine learning to analyze medical images and detect the patient’s status [44]; some researchers use supervised machine learning algorithms to classify patient movement data. Thereby judging the therapeutic effect of the diagnosis, with high accuracy [45][46][47][48][49]. However, these studies didn’t include evaluation scales in the machine learning model, instead, sensing data was solely used. Therefore, the proposed machine model lacked clinical references and wasn’t convincible from therapist perspective.

To address issues mentioned above, the research is composed of designing motor indicators based on VR data, exploring the scientific correlation between proposed motor indicators and evaluation scale, establishing evidence-based grading standards based on multi-dimensional evaluation scale data, and applying machine learning to establish a new data-driven assessment model.[…]

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[Abstract] Hand and Fingertip Detection for Game-Based Hand Rehabilitation

Abstract

Hand rehabilitation is the process of recovering hand movements to return to normal. For rehabilitation to be effective, it is necessary for patients to practice repetitive movements. During the process, the patients usually feel bored, lack motivation and enjoyable time. There is a growing interest in building games for rehabilitation to make it more interesting and motivating for patients. However, the major obstacle is that the devices are expensive, and the patients must go to use them in hospitals. This paper focuses on designing and implementing hand rehabilitation software by using hand and fingertip detection. The purpose of the project is to make the rehabilitation process more accessible, enjoyable, affordable, and can be made portable for patients to use at home. Deep learning techniques were utilized to perform hand and fingertip detection. The SuperFox game is developed; the game is controlled by commands associated with hand and fingertip movements. The system was tested with 10 participants to evaluate effectiveness of the game controls. The results showed that the system is feasible in controlling the game and able to be used to create motivation and enjoyable time for patients.

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[Abstract] Development of a Home-based Hand Rehabilitation Training and Compensation Feedback System

Abstract

Stroke survivors often show a limited recovery in the hand function even after the recovery period (3-6 months after stroke) and at-home hand rehabilitation is common due to the long-term nature of hand rehabilitation and the limited medical resources. We designed a home-based hand rehabilitation training and compensation feedback system. A low-cost simple orthosis glove, a set of hand rehabilitation training games and a compensation detection and feedback module were designed and developed in this system. A preliminary test was carried out on the system and the results showed that the training section (the orthosis glove and the hand rehabilitation training games) of the system was friendly to the subjects and the subjects were more receptive to the system and the compensation detection and feedback module had a promising performance. This system can not only provide high intensity and incentive hand rehabilitation training, but also guide the stroke patients to correct wrong upper body postures during the training process, which can achieve better rehabilitation results. The system has the potential to become an effective home-based hand rehabilitation training and compensation feedback system.

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[Abstract] Preliminary Results of Hand Rehabilitation for Post Stroke Patient using Leap Motion-based Virtual Reality

Abstract

This paper introduced a rehabilitation system for the upper limb function of the post stroke patients who involved virtual reality games. Post- stroke patient is needed to perform rehabilitation to improve their hand and finger motion, which were affected from the stroke. Thus a virtual reality hand rehabilitation using Leap Motion sensor integrated with Unity software was developed, which focuses on the hand and finger movement of the patient. There are three games created namely Space game, Cannon game and Piano games in order to evaluate the performance of the users. Data from 10 normal subjects playing each virtual game in one minute has been collected and analysed. The results show that average values of objects can be destroyed by the normal people in Space game, Cannon game and Piano game is 9,23 and 20 respectively. Feedback has been received and these virtual reality games hopefully could facilitate the recovery of motor functions in stroke patients.

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[Abstract] Attention Enhancement and Motion Assistance for Virtual Reality-Mediated Upper-limb Rehabilitation

Abstract

Dysfunctions of upper limbs caused by diseases such as stroke result in difficulties in conducting day-to-day activities. Studies show that rehabilitation training using virtual reality games is helpful for patients to restore arm functions. It has been found that ensuring active patient participation and effort devoting in the process is very important to obtain better training results. This paper introduces a method to help patients increase their engagement and provide motion assistance in virtual reali-ty-mediated upper-limb rehabilitation training. Attention en-hancement and motion assistance is achieved through an illusion of virtual forces created by altering the drag speed between the cursor and the object presented on a screen to the patient as the only feedback. We present two game forms using the proposed method, including a target-approaching game and a maze-following game. The results of evaluation experiments with human participants showed that the proposed method could provide path guidance that significantly improved path-following performance of users and required more involvement of the users when compared to playing the game without attention enhance-ment and motion assistance.

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[Abstract] Design and Implementation of An Interactive Hand Rehabilitation Training System Based on LabVIEW

Abstract

With the development of science and technology in multidisciplinary fields of automation control, rehabilitation medicine and robotics and the improvement of people’s living standards, medical rehabilitation robots are playing an increasingly important role in life. The traditional hand rehabilitation robots are exoskeleton rigid robots with complex structure and small fault tolerance. It is dangerous for the rehabilitation of human finger joints, while soft wearable hand rehabilitation robots have better safety and flexibility. For the rehabilitation needs of stroke fingers, a virtual online game of human-computer interaction is developed using LabVIEW and a soft wearable hand rehabilitation robot, in order to improve the initiative of patients in the process of active rehabilitation training and to increase the interest of patients in active rehabilitation training, which also improves the initiative of patients to participate in active rehabilitation training.

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[Abstract] Remote Monitoring of Physical Rehabilitation of Stroke Patients using IoT and Virtual Reality

Abstract

The statistics highlights that physical rehabilitation are required nowadays by increased number of people that are affected by motor impairments caused by accidents or aging. Among the most common causes of disability in adults are strokes or cerebral palsy. To reduce the costs preserving the quality of services new solutions based on current technologies in the area of physiotherapy are emerging. The remote monitoring of physical training sessions could facilitate for physicians and physical therapists’ information about training outcome that may be useful to personalize the exercises helping the patients to achieve better rehabilitation results in short period of time process. This research work aims to apply physical rehabilitation monitoring combining Virtual Reality serious games and Wearable Sensor Network to improve the patient engagement during physical rehabilitation and evaluate their evolution. Serious games based on different scenarios of Virtual Reality, allows a patient with motor difficulties to perform exercises in a highly interactive and non-intrusive way, using a set of wearable devices, contributing to their motivational process of rehabilitation. The system implementation, system validation and experimental results are included in the paper.

Source: https://ieeexplore.ieee.org/abstract/document/9183980

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[Abstract + References] A Virtual Reality Serious Game for Hand Rehabilitation Therapy – IEEE Conference Publication

Abstract

The human hand is the body part most frequently injured in occupational accidents, accounting for one out of five emergency cases and often requiring surgery with subsequently long periods of rehabilitation. This paper proposes a Virtual Reality game to improve conventional physiotherapy in hand rehabilitation, focusing on resolving recurring limitations reported in most technological solutions to the problem, namely the limited diversity support of movements and exercises, complicated calibrations and exclusion of patients with open wounds or other disfigurements of the hand. The system was assessed by seven able-bodied participants using a semistructured interview targeting three evaluation categories: hardware usability, software usability and suggestions for improvement. A System Usability Score (SUS) of 84.3 and participants’ disposition to play the game confirm the potential of both the conceptual and technological approaches taken for the improvement of hand rehabilitation therapy.

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Source: https://ieeexplore.ieee.org/abstract/document/9201789

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[Abstract] RehabFork: An Interactive Game-assisted Upper Limb Stroke Rehabilitation System – IEEE Conference Publication

Abstract

In this paper, we present the design and development of a game-assisted stroke rehabilitation system RehabFork that allows a user to train their upper-limb to perform certain functions related to the task of eating.

The task of eating is divided into several components: (i) grasping the eating utensils such as a fork and knife; (ii) lifting the eating utensils; (iii) using the eating utensils to cut a piece of food; (iv) transferring the food to the mouth; and (v) chewing the food. The RehabFork supports the user through sub-tasks (i)–(iii).

The hardware components of RehabFork consist of an instrumented fork and knife, and a 3D printed pressure pad, that measure and communicate information on user performance to a gaming environment to render an integrated rehabilitation system.

The gaming environment consists of an interactive game that utilizes sensory data as well as user information about the severity of their disability and current level of progress to adjust the difficulty levels of the game to maintain user motivation. Information pertaining to the user, including performance data, is stored and can be shared with care providers for ongoing oversight.

Source: https://ieeexplore.ieee.org/abstract/document/9176168

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