There are a certain number of arm dysfunction patients whose legs could move. Considering the neuronal coupling between arms and legs during locomotion, this paper proposes a novel human-robot cooperative method for upper extremity rehabilitation. Legs motion is considered at the passive rehabilitation training of disabled arm, and its traversed trajectory is represented by the patient trunk motion. A Kinect based vision module, two computers and a WAM robot construct the human-robot cooperative upper extremity rehabilitation system. The vision module is employed to track the position of the subject trunk in horizontal; the WAM robot is used to guide the arm of post-stroke patient to do passive training with the predefined trajectory, and meanwhile the robot follows the patient trunk movement which is tracked by Kinect in real-time. A hierarchical fuzzy control strategy is proposed to improve the position tracking performance and stability of the system, which consists of an external fuzzy dynamic interpolation strategy and an internal fuzzy PD position controller. Four experiments were conducted to test the proposed method and strategy. The experimental results show that the patient felt more natural and comfortable when the human-robot cooperative method was applied; the subject could walk as he/she wished in the visual range of Kinect. The hierarchical fuzzy control strategy performed well in the experiments. This indicates the high potential of the proposed human-robot cooperative method for upper extremity rehabilitation.
The work presented here suggests new ways to tackle exergames for physical rehabilitation and to improve the players’ immersion and involvement. The primary (but not exclusive) purpose is to increase the motivation of children and adolescents with severe physical impairments, for doing their required exercises while playing. The proposed gaming environment is based on the Kinect sensor and the Blender Game Engine. A middleware has been implemented that efficiently transmits the data from the sensor to the game. Inside the game, different newly proposed mechanisms have been developed to distinguish pure exercise-gestures from other movements used to control the game (e.g., opening a menu). The main contribution is the amplification of weak movements, which allows the physically impaired to have similar gaming experiences as the average population. To test the feasibility of the proposed methods, four mini-games were implemented and tested by a group of 11 volunteers with different disabilities, most of them bound to a wheelchair. Their performance has also been compared to that of a healthy control group. Results are generally positive and motivating, although there is much to do to improve the functionalities. There is a major demand for applications that help to include disabled people in society and to improve their life conditions. This work will contribute towards providing them with more fun during exercise.
For a number of years, the possibility of applying serious games for rehabilitation purposes has been thoroughly investigated [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28]. It is often claimed that serious games reduce health system costs and efforts as they enable in-home rehabilitation without loss of medical monitoring, and in so doing provide an additional fun factor for patients [22,23,24]. Multiple reviews have summarized the very powerful contributions and reveal that the systems are generally evaluated as feasible, but no state of general applicability has yet been reached [2,3,5,7,11,13].
Most studies are quite specialised and tend to cover the same groups of largely elderly patients (e.g., stroke and Parkinson’s), which do not constitute a credible target group per se for gaming among the population. In addition, the impression is that the same functionalities are being tested repeatedly, without any evolution. Above all, other groups like children and adolescents with chronic diseases are rarely addressed, even though they are an excellent target group and would probably benefit greatly from using exergames as they need to move like any other child but are mostly limited to performing their exercises with a physiotherapist. This is generally boring, time-consuming and prevents them from playing with friends during this time. If instead they could play games involving physical exercises, without it feeling like rehabilitation, due to proper immersion and motivation, they would possibly need fewer sessions with the therapist, which may in turn improve their social life. Commercially available games would be good enough for many children with physical disabilities, if only they were configurable and adaptive to their potential and needs. Remote controls (RC) are typically not sufficiently configurable (button functions cannot be changed or the RC cannot be used with one hand) and are only made for hands (why not for feet or the mouth?) Some RCs are not sufficiently precise in detection, and so the user ends up tired and loses motivation. Motion capture devices like the Kinect sensor seem to provide better prerequisites for exergaming purposes but feature important limitations too, (e.g., detection of fine movements and rotations) such that the needs of many people are still not be covered by commercial solutions.
However, this is not due to the sensors, but rather the software, which lacks configurability for special needs, such as simple adjustments of level difficulties or the option of playing while seated. For the latter, some Kinect games are available , but those are hardly the most liked ones, as has been stated by affected users . Therefore, more complex solutions are required to adapt a game to problems like muscle weaknesses (most games require wide or fast movements), spasticity (“strange” movements are not recognized) or the available limbs (for instance configuring a game to be controlled with the feet for players without full hand use).
To fill these gaps, the authors of the work presented here are pursuing the overall aim (as part of a long-term project) of creating an entertaining exergaming environment for adventure games that immerses the players into a virtual world and makes them forget their physical impairments. Knowledge of the gaming industry is applied to create motivating challenges that the users have to solve, which are sufficiently addictive to make the exercises pass to an unconscious plane. The gaming environment is configurable to the user’s potential and requirements. Challenges will be programmable by a therapist and will also adapt themselves to the players automatically real-time, by observing their fatigue or emotional state (lowering the difficulty or switching to more relaxing exercises when needed)…
Figure 8. Different scenes while the volunteers were playing. (a) “The Paper-Bird”, (b) “The Ladder”, (c) “The Boat” and (d) “Whack-a-Mole”.
This paper investigates Kinect device application during rehabilitation of people with an ischemic stroke. There are many similar application using Kinect as a tool during rehabilitation. This paper is focused on measurement of Kinect’s spatial accuracy and proposition of body states and exercises according to the Motor assessment scale for stroke (MAS). The system observes the whole rehabilitation process and objectively compares ranges of movement during each exercise. Angles between limbs are computed in the skeletal body joints projection to three anatomical planes, which enables a better insight to subject performance. The system is easily implemented with a consumer-grade computer and a low-cost Kinect device. Selected exercises are presented together with the angles evolution, body states recognition and the MAS Scale after the stroke classification.
Neurological and chronic diseases have profound impacts on a person’s life. Rehabilitation is essential in order to maintain and promote maximal level of recovery by pushing the bounds of physical, emotional and cognitive impairments. However, due to the low physical mobility and poor overall condition of many patients, traveling back and forth to doctors, nurses and rehabilitation centers can be exhausting tasks. In this thesis a game-based rehabilitation platform for home usage, supporting stroke and COPD rehabilitation is presented. The main goal is to make rehabilitation more enjoyable, individualized and easily accessible for the patients.
The game-based rehabilitation tool consists of three systems with integrated components: the caregiver’s planning and follow-up system, the patient’s gaming system and the connecting server system. The server back end components allow the storage of patient specific information that can be transmitted between the patient and the caregiver system for planning, monitoring and feedback purposes. The planning and follow-up system is a server system accessed through a web-based front-end, where the caregiver schedules the rehabilitation program adjusted for each individual patient and follow up on the rehabilitation progression. The patient system is the game platform developed in this project, containing 16 different games and three assessment tests. The games are based on specific motion patterns produced in collaboration with rehabilitation specialists. Motion orientation and guidance functions is implemented specifically for each exercise to provide feedback to the user of the performed motion and to ensure proper execution of the desired motion pattern.
The developed system has been tested by several people and with three real patients. The participants feedback supported the use of the game-based platform for rehabilitation as an entertaining alternative for rehabilitation at home. Further implementation work and evaluation with real patients are necessary before the product can be used for commercial purpose.
Rehabilitation exercises are an important means for gaining mobility and strength after injuries or surgery. Self-exercising in between physio-therapy sessions is vital for effective rehabilitation. Yet, many people do not follow exercise regimes, which can hamper their recovery. This study proposes GEAR – a mobile GamE Assisted Rehabilitation system – to engage users in self-exercising and to improve adherence to their exercise regime. The system consists of a wearable wristband to monitor users’ movements, a mobile game that incorporates the exercises, and a dashboard to monitor and visualize users’ exercise performance. GEAR has advantages of portability and lower cost as compared to PC or Kinect-based rehabilitation systems. This study describes GEAR and reports on a pilot assessment of its interface and system. The pilot test demonstrates the feasibility of GEAR and provides feedback that is being used to enhance the system prior to full-scale evaluation.
The growing importance of Kinect as a tool for clinical assessment and rehabilitation is due to its portability, low cost and markerless system for human motion capture. However, the accuracy of Kinect in measuring three-dimensional body joint center locations often fails to meet clinical standards of accuracy when compared to marker-based motion capture systems such as Vicon. The length of the body segment connecting any two joints, measured as the distance between three-dimensional Kinect skeleton joint coordinates, has been observed to vary with time. The orientation of the line connecting adjoining Kinect skeletal coordinates has also been seen to differ from the actual orientation of the physical body segment. Hence we have proposed an optimization method that utilizes Kinect Depth and RGB information to search for the joint center location that satisfies constraints on body segment length and as well as orientation. An experimental study have been carried out on ten healthy participants performing upper body range of motion exercises. The results report 72% reduction in body segment length variance and 2° improvement in Range of Motion (ROM) angle hence enabling to more accurate measurements for upper limb exercises.
Body joint movement analysis is extremely essential for health monitoring and treatment of patients with neurological disorders and stroke. Chronic hemiparesis of the upper extremity following a stroke causes major hand movement limitations. There is possibility of permanent reduction in muscle coactivation and corresponding joint torque patterns due to stroke . Several studies suggest that abnormal coupling of shoulder adductors with elbow extensors and shoulder abductors with elbow flexors often leads to some stereotypical movement characteristics exhibited by severe stroke patients . Therefore continuous and effective rehabilitation therapy is absolutely essential to monitor and control such abnormalities. There is a substantial need for home-based rehabilitation post-clinical therapy.
Stroke patients usually have difficulties to conduct rehabilitation training themselves, due to no rehabilitation evaluation in time and dependence on doctors. In order to solve this problem, this paper proposes a motion rehabilitation and evaluation system based on the Kinect gesture measuring technology combining VR technology as well as traditional method of stroke rehabilitation. Real-time rehabilitation motion feedback is achieved by using Kinect motion capturing, customized skeleton modeling, and virtual characters constructed in Unity3D. The jitter problem of virtual characters following motion using Kinect is solved. Fidelity and interactivity of virtual rehabilitation training is improved. Our experiment validated the feasibility of this system preliminarily.
With an ageing population problem increasingly prominent, the number of hemiplegia patients is growing caused by stroke, which has a high morbidity and high mortality rate . Stroke can lead to the dysfunction of the brain central nervous, often characterized by language, cognitive or motor dysfunction , . The medical rehabilitation mechanism of stroke is based on neural plasticity theory and the theory of mirror neurons .
The FysioGaming is the first Dutch Kinect driven exercising platform registered as a Medical Device (CE Marked). Installed in hospitals and clinics across Europe, in China, Australia and the USA. We’re proudly encouraging all patients towards more intense exercising.
Abstract—Upper-limb robotic rehabilitation systems should inform the therapists for their patients status. Such therapy systems must be developed carefully by taking into consideration real life uncertainties that associate with sensor error. In our paper, we describe a system which is composed of a depth camera that tracks the motion of the patients upper limb, and a robotic manipulator that challenges the patient with repetitive exercises. The goal of this study is to propose a motion analysis system that improves the readings of the depth camera, through the use of a kinematic model that describes the motion of the human arm. In our current experimental set-up we are using the Kinect v2 to capture a participant who performs rehabilitation exercises with the Barrett WAM robotic manipulator. Finally, we provide a numerical comparison among the stand alone measurements from the Kinect v2, the estimated motion parameters of our system and the VICON, which we consider as an error-free ground truth apparatus.
It is generally accepted that the role of modern physical rehabilitation is essential for the enhancement or restoration of inherent or incidental motor skills disorders. Such disorders may result from a variety of different causes such as amputation, spinal cord injury, musculoskeletal impairment and even brain injury. In light of this phenomenon, robotic rehabilitation augments classical rehabilitation techniques, from the scope that adaptable robotic devices, such as mechanical manipulators, can be used to complement the training routines of a physiatrist or occupational therapist. In this paper we describe and evaluate a novel system that can be used by physicians and therapists to monitor the state of the upper limbs of a patient who performs exercises. The system emphasizes the use of the Microsoft Kinect v2 as opposed to wearable sensors, such as embedded accelerometers, gyroscopes and EMGs. In the following sections we present, analyze and evaluate the proposed system. Speciﬁcally, in section 2 we discuss how related studies manage to tackle the problem of pose estimation with vision based or wearable sensors. Furthermore, we discuss how our system exploits the kinematic formulas that originate from the area of robotic mechanics and describe the motion or rigid bodies that can be abstracted via a kinematic chain. We also illustrate an overview of the system, address its core processes and state certain assumptionsthatleadtothesystemsrealization.Asexpected, in the last sections of the paper we detail the physical experimental setup for the assessment of the system and we consider possible avenues for future work.
The emergence of lower-cost motion tracking devices enables home-based virtual reality rehabilitation activities and increased accessibility to patients. Currently, little documentation on patients’ expectations for virtual reality rehabilitation is available.
This study surveyed 10 people with stroke for their expectations of virtual reality rehabilitation games. This study also evaluated the usability of three lowercost virtual reality rehabilitation games using a survey and House of Quality analysis. The games (kitchen, archery, and puzzle) were developed in the laboratory to encourage coordinated finger and arm movements.
Lower-cost motion tracking devices, the P5 Glove and Microsoft Kinect, were used to record the movements. People with stroke were found to desire motivating and easy-to-use games with clinical insights and encouragement from therapists. The House of Quality analysis revealed that the games should be improved by obtaining evidence for clinical effectiveness, including clinical feedback regarding improving functional abilities, adapting the games to the user’s changing functional ability, and improving usability of the motion-tracking devices.
This study reports the expectations of people with stroke for rehabilitation games and usability analysis that can help guide development of future games.