Future Trends of Virtual, Augmented Reality, and Games for Health

Serious game is now a multi-billion dollar industry and is still growing steadily in many sectors. As a major subset of serious games, designing and developing Virtual Reality (VR), Augmented Reality (AR), and serious games or adopting off-the-shelf games to support medical education, rehabilitation, or promote health has become a promising frontier in the healthcare sector since 2004, because games technology is inexpensive, widely available, fun and entertaining for people of all ages, with various health conditions and different sensory, motor, and cognitive capabilities. In this chapter, we provide the reader an overview of the book with a perspective of future trends of VR, AR simulation and serious games for healthcare

NAOMOBBY, desarrollo de una herramienta software basada en visión por computador y robótica para apoyar la rehabilitación en terapias físicas de miembros superiores

Nowadays, 21% of Colombian population, and the 35% of the population in Cauca Valley have limited movement of body, arms, hands or legs. Then, the quality of life of these people is highly affected, since they have limitations in daily living activities. Physical rehabilitation therapies allow the restoration of movement and maximum functional capacity in people. Successful physical therapies depend on empathy and motivation with the rehabilitation process (RP), then the more empathy of patients with the RP, the more patient willingness regarding the rehabilitation therapy. Motivation is crucial in rehabilitation, and it is used as a fundamental rehabilitation out-come. This work has the aim to present the software tool called NAOMOBBY to support physical rehabilitation therapies of shoulder, elbow and wrist joints. NAOMOBBY includes a GUI for therapist, a Kinect sensor and an interactive humanoid robot NAO to increase the patient willingness regarding the RP. NAOMOBBY includes the following modules: configuration/management, movement reproduction, and results report using GAS methodology. NAOMOBBY was tested using quantitative and field tests. Quantitative tests measure the error in the Kinect sensor of the NAO robot joint motions to bring users a suitable feedback. Quantitative results were obtained using three basic functional motions. The mean square error for these three motions were 0,373%, 0,096%, and 1,129% respectively. Field tests were conducted at the SURGIR neuro-rehabilitation center using 3 physiotherapists who considered the NAOMOBBY software tool as a novel, easy to use, and that encourage patients to perform the physical therapy.Actualmente, el 21% de la población en Colombia y el 35% de la población del Valle del Cauca tiene limitaciones en el movimiento del cuerpo, brazos, manos o piernas. Entonces, la calidad de vida de estas personas está altamente afectado, ya que ellas tienen limitaciones al desarrollar actividades del diario vivir. La rehabilitación a través de la terapia física, permite la restauración del movimiento y la máxima capacidad funcional en las personas. Terapias físicas exitosas dependen de la empatía y motivación con el proceso de rehabilitación (PR), entonces entre más alta la empatía de los pacientes con el PR, más alta la disposición será de los pacientes en relación con la terapia de rehabilitación. Motivación es crucial en rehabilitación, y es usado como un resultado determinante de la rehabilitación. Este trabajo tiene el objetivo de presentar la herramienta software llamada NAOMOBBY para soportar las terapias de rehabilitación física de las articulaciones de hombro, codo y muñeca. NAOMOBBY incluye una GUI para terapeutas, un sensor Kinect y un robot interactivo humanoide NAO con el fin de incrementar la disposición del paciente hacia el PR. NAOMOBBY incluye los siguientes módulos: configuración y gestión, reproducción de movimiento y reporte de resultados usando la metodología GAS. NAOMOBBY fue probada usando pruebas cuantitativas y de campo. Las pruebas cuantitativas miden el error en el sensor Kinect de los movimientos de las articulaciones del robot NAO, con el fin de brindar a los usuarios una adecuada realimentación. Los resultados cuantitativos fueron obtenidos usando tres movimientos funcionales básicos. Los errores cuadráticos medios de estos tres movimientos fueron 0,373%, 0,096%, y 1,129% respectivamente. Las pruebas de campo fueron realizadas en el centro de neuro-rehabilitación SURGIR usando 3 fisioterapeutas quienes consideraron a la herramienta software NAOMOBBY como novedosos, fáciles de usar y que motiva a los pacientes a realizar la terapia física

NAOMOBBY, desarrollo de una herramienta software basada en visión por computador y robótica para apoyar la rehabilitación en terapias físicas de miembros superiores

Nowadays, 21% of Colombian population, and the 35% of the population in Cauca Valley have limited movement of body, arms, hands or legs. Then, the quality of life of these people is highly affected, since they have limitations in daily living activities. Physical rehabilitation therapies allow the restoration of movement and maximum functional capacity in people. Successful physical therapies depend on empathy and motivation with the rehabilitation process (RP), then the more empathy of patients with the RP, the more patient willingness regarding the rehabilitation therapy. Motivation is crucial in rehabilitation, and it is used as a fundamental rehabilitation out-come. This work has the aim to present the software tool called NAOMOBBY to support physical rehabilitation therapies of shoulder, elbow and wrist joints. NAOMOBBY includes a GUI for therapist, a Kinect sensor and an interactive humanoid robot NAO to increase the patient willingness regarding the RP. NAOMOBBY includes the following modules: configuration/management, movement reproduction, and results report using GAS methodology. NAOMOBBY was tested using quantitative and field tests. Quantitative tests measure the error in the Kinect sensor of the NAO robot joint motions to bring users a suitable feedback. Quantitative results were obtained using three basic functional motions. The mean square error for these three motions were 0,373%, 0,096%, and 1,129% respectively. Field tests were conducted at the SURGIR neuro-rehabilitation center using 3 physiotherapists who considered the NAOMOBBY software tool as a novel, easy to use, and that encourage patients to perform the physical therapy.Actualmente, el 21% de la población en Colombia y el 35% de la población del Valle del Cauca tiene limitaciones en el movimiento del cuerpo, brazos, manos o piernas. Entonces, la calidad de vida de estas personas está altamente afectado, ya que ellas tienen limitaciones al desarrollar actividades del diario vivir. La rehabilitación a través de la terapia física, permite la restauración del movimiento y la máxima capacidad funcional en las personas. Terapias físicas exitosas dependen de la empatía y motivación con el proceso de rehabilitación (PR), entonces entre más alta la empatía de los pacientes con el PR, más alta la disposición será de los pacientes en relación con la terapia de rehabilitación. Motivación es crucial en rehabilitación, y es usado como un resultado determinante de la rehabilitación. Este trabajo tiene el objetivo de presentar la herramienta software llamada NAOMOBBY para soportar las terapias de rehabilitación física de las articulaciones de hombro, codo y muñeca. NAOMOBBY incluye una GUI para terapeutas, un sensor Kinect y un robot interactivo humanoide NAO con el fin de incrementar la disposición del paciente hacia el PR. NAOMOBBY incluye los siguientes módulos: configuración y gestión, reproducción de movimiento y reporte de resultados usando la metodología GAS. NAOMOBBY fue probada usando pruebas cuantitativas y de campo. Las pruebas cuantitativas miden el error en el sensor Kinect de los movimientos de las articulaciones del robot NAO, con el fin de brindar a los usuarios una adecuada realimentación. Los resultados cuantitativos fueron obtenidos usando tres movimientos funcionales básicos. Los errores cuadráticos medios de estos tres movimientos fueron 0,373%, 0,096%, y 1,129% respectivamente. Las pruebas de campo fueron realizadas en el centro de neuro-rehabilitación SURGIR usando 3 fisioterapeutas quienes consideraron a la herramienta software NAOMOBBY como novedosos, fáciles de usar y que motiva a los pacientes a realizar la terapia física

NAOMOBBY, desarrollo de una herramienta software basada en visión por computador y robótica para apoyar la rehabilitación en terapias físicas de miembros superiores

Nowadays, 21% of Colombian population, and the 35% of the population in Cauca Valley have limited movement of body, arms, hands or legs. Then, the quality of life of these people is highly affected, since they have limitations in daily living activities. Physical rehabilitation therapies allow the restoration of movement and maximum functional capacity in people. Successful physical therapies depend on empathy and motivation with the rehabilitation process (RP), then the more empathy of patients with the RP, the more patient willingness regarding the rehabilitation therapy. Motivation is crucial in rehabilitation, and it is used as a fundamental rehabilitation out-come. This work has the aim to present the software tool called NAOMOBBY to support physical rehabilitation therapies of shoulder, elbow and wrist joints. NAOMOBBY includes a GUI for therapist, a Kinect sensor and an interactive humanoid robot NAO to increase the patient willingness regarding the RP. NAOMOBBY includes the following modules: configuration/management, movement reproduction, and results report using GAS methodology. NAOMOBBY was tested using quantitative and field tests. Quantitative tests measure the error in the Kinect sensor of the NAO robot joint motions to bring users a suitable feedback. Quantitative results were obtained using three basic functional motions. The mean square error for these three motions were 0,373%, 0,096%, and 1,129% respectively. Field tests were conducted at the SURGIR neuro-rehabilitation center using 3 physiotherapists who considered the NAOMOBBY software tool as a novel, easy to use, and that encourage patients to perform the physical therapy.Actualmente, el 21% de la población en Colombia y el 35% de la población del Valle del Cauca tiene limitaciones en el movimiento del cuerpo, brazos, manos o piernas. Entonces, la calidad de vida de estas personas está altamente afectado, ya que ellas tienen limitaciones al desarrollar actividades del diario vivir. La rehabilitación a través de la terapia física, permite la restauración del movimiento y la máxima capacidad funcional en las personas. Terapias físicas exitosas dependen de la empatía y motivación con el proceso de rehabilitación (PR), entonces entre más alta la empatía de los pacientes con el PR, más alta la disposición será de los pacientes en relación con la terapia de rehabilitación. Motivación es crucial en rehabilitación, y es usado como un resultado determinante de la rehabilitación. Este trabajo tiene el objetivo de presentar la herramienta software llamada NAOMOBBY para soportar las terapias de rehabilitación física de las articulaciones de hombro, codo y muñeca. NAOMOBBY incluye una GUI para terapeutas, un sensor Kinect y un robot interactivo humanoide NAO con el fin de incrementar la disposición del paciente hacia el PR. NAOMOBBY incluye los siguientes módulos: configuración y gestión, reproducción de movimiento y reporte de resultados usando la metodología GAS. NAOMOBBY fue probada usando pruebas cuantitativas y de campo. Las pruebas cuantitativas miden el error en el sensor Kinect de los movimientos de las articulaciones del robot NAO, con el fin de brindar a los usuarios una adecuada realimentación. Los resultados cuantitativos fueron obtenidos usando tres movimientos funcionales básicos. Los errores cuadráticos medios de estos tres movimientos fueron 0,373%, 0,096%, y 1,129% respectivamente. Las pruebas de campo fueron realizadas en el centro de neuro-rehabilitación SURGIR usando 3 fisioterapeutas quienes consideraron a la herramienta software NAOMOBBY como novedosos, fáciles de usar y que motiva a los pacientes a realizar la terapia física

An intelligent assistive tool using exergaming and response surface methodology for patients with brain disorders

Intelligent assistive technologies represent a concept that refers to products and services that can offset functional limitations, facilitate independent life, improve their quality of life, and enable people with disabilities to reach their own potential. This paper presents a medical recovery exergaming that includes a Microsoft Kinect Motion Sensor, designed for upper limb rehabilitation, especially for old people with brain disorders. The game is 3D and during the game, the user has to pick up the red or green apples according to a level, and different angles of inclination of the neck, hand, shoulder, and so on are measured and then a total score is generated. To know if the patient has progressed in his medical recovery, the final score should be increased. In order to find the score that a subject without a locomotor system disorder can achieve, we have optimized the game with mathematical modeling and canonical analysis by applying response surface methodology and multiple nonlinear regression. The exergaming based on VR active games represents a useful tool in physical and cognitive rehabilitation for people with motor impairments or brain disorders, considering the advantage of home-training.info:eu-repo/semantics/publishedVersio

A Fuzzy Logic Architecture for Rehabilitation Robotic Systems

Robots are highly incorporated in rehabilitation in the last decade to compensate lost functions in disabled individuals. By controlling the rehabilitation robots from far, many benefits are achieved. These benefits include but not restricted to minimum hospital stays, decreasing cost, and increasing the level of care. The main goal of this work is to have an effective solution to take care of patients from far. Tackling the problem of the remote control of rehabilitation robots is undergoing and highly challenging. In this paper, a remote wrist rehabilitation system is presented. The developed system is a sophisticated robot ensuring the two wrist movements (Flexion /extension and abduction/adduction). Additionally, the proposed system provides a software interface enabling the physiotherapists to control the rehabilitation process remotely. The patient’s safety during the therapy is achieved through the integration of a fuzzy controller in the system control architecture. The fuzzy controller is employed to control the robot action according to the pain felt by the patient. By using fuzzy logic approach, the system can adapt effectively according to the patients’ conditions. The Queue Telemetry Transport Protocol (MQTT) is considered to overcome the latency during the human robot interaction. Based on a Kinect camera, the control technique is made gestural. The physiotherapist gestures are detected and transmitted to the software interface to be processed and be sent to the robot. The acquired measurements are recorded in a database that can be used later to monitor patient progress during the treatment protocol. The obtained experimental results show the effectiveness of the developed remote rehabilitation system

A review of computer vision-based approaches for physical rehabilitation and assessment

The computer vision community has extensively researched the area of human motion analysis, which primarily focuses on pose estimation, activity recognition, pose or gesture recognition and so on. However for many applications, like monitoring of functional rehabilitation of patients with musculo skeletal or physical impairments, the requirement is to comparatively evaluate human motion. In this survey, we capture important literature on vision-based monitoring and physical rehabilitation that focuses on comparative evaluation of human motion during the past two decades and discuss the state of current research in this area. Unlike other reviews in this area, which are written from a clinical objective, this article presents research in this area from a computer vision application perspective. We propose our own taxonomy of computer vision-based rehabilitation and assessment research which are further divided into sub-categories to capture novelties of each research. The review discusses the challenges of this domain due to the wide ranging human motion abnormalities and difficulty in automatically assessing those abnormalities. Finally, suggestions on the future direction of research are offered

Assessment of joint parameters in a Kinect sensor based rehabilitation game

Copyright © 2019 ASME. A Kinect sensor based basketball game is developed for delivering post-stroke exercises in association with a newly developed elbow exoskeleton. Few interesting features such as audio-visual feedback and scoring have been added to the game platform to enhance patient’s engagement during exercises. After playing the game, the performance score has been calculated based on their reachable points and reaching time to measure their current health conditions. During exercises, joint parameters are measured using the motion capture technique of Kinect sensor. The measurement accuracy of Kinect sensor is validated by two comparative studies where two healthy subjects were asked to move elbow joint in front of Kinect sensor wearing the developed elbow exoskeleton. In the first study, the joint information collected from Kinect sensor was compared with the exoskeleton based sensor. In the next study, the length of upperarm and forearm measured by Kinect were compared with the standard anthropometric data. The measurement errors between Kinect and exoskeleton are turned out to be in the acceptable range; 1% for subject 1 and 0.44% for subject 2 in case of joint angle; 5.55% and 3.58% for subject 1 and subject 2 respectively in case of joint torque. The average errors of Kinect measurement as compared to the anthropometric data of the two subjects are 16.52% for upperarm length and 9.87% for forearm length. It shows that Kinect sensor can measure the activity of joint movement with a minimum margin of error