Posts Tagged fuzzy logic

[Abstract] Dynamic Difficulty Adjustment in Virtual Reality Applications for Upper Limb Rehabilitation – IEEE Conference Publication

Abstract

The objective of this paper was to compare the incidence of a rehabilitation game in motor ability with dynamic difficulty adjustment (ADD) in comparison to a manual configuration. To achieve that, a virtual tool called “Bug catcher” was developed, which is focused in upper limb rehabilitation. This tool uses a dynamic difficulty adjustment based in fuzzy logic. The population involved for the present study were made by 2 users, a 18-year-old patient with a hemiparesis that limits her motor ability in her left upper limb, and a 37-year-old patient with motor monoparesis in his right upper limb. This tool was used in both users, each one with a different configuration (automatic or manual), and the motor ability from both participants was objectively measured using Box and Blocks Test, applied before, during and after each session; additionally, a performance index (percentage of success) was defined in order to determine the progress of the participants in the virtual tool. As a result, it was obtained that user number one using the game with ADD, managed to obtain not only a better performance in the sessions but also an important advance in her motor skill in comparison to the user 2 with the manual configuration.

via Dynamic Difficulty Adjustment in Virtual Reality Applications for Upper Limb Rehabilitation – IEEE Conference Publication

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[Abstract] Fuzzy logic-based mobile computing system for hand rehabilitation after neurological injury.  

Abstract

BACKGROUND:

Effective neurological rehabilitation requires long term assessment and treatment. The rapid progress of virtual reality-based assistive technologies and tele-rehabilitation has increased the potential for self-rehabilitation of various neurological injuries under clinical supervision.

OBJECTIVE:

The objective of this study was to develop a fuzzy inference mechanism for a smart mobile computing system designed to support in-home rehabilitation of patients with neurological injury in the hand by providing an objective means of self-assessment.

METHODS:

A commercially available tablet computer equipped with a Bluetooth motion sensor was integrated in a splint to obtain a smart assistive device for collecting hand motion data, including writing performance and the corresponding grasp force. A virtual reality game was also embedded in the smart splint to support hand rehabilitation. Quantitative data obtained during the rehabilitation process were modeled by fuzzy logic. Finally, the improvement in hand function was quantified with a fuzzy rule database of expert opinion and experience.

RESULTS:

Experiments in chronic stroke patients showed that the proposed system is applicable for supporting in-home hand rehabilitation.

CONCLUSIONS:

The proposed virtual reality system can be customized for specific therapeutic purposes. Commercial development of the system could immediately provide stroke patients with an effective in-home rehabilitation therapy for improving hand problems.

Source: Fuzzy logic-based mobile computing system for hand rehabilitation after neurological injury. – PubMed – NCBI

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[Abstract] An adaptive self-organizing fuzzy logic controller in a serious game for motor impairment rehabilitation

Abstract:

Rehabiliation robotics combined with video game technology provides a means of assisting in the rehabilitation of patients with neuromuscular disorders by performing various facilitation movements. The current work presents ReHabGame, a serious game using a fusion of implemented technologies that can be easily used by patients and therapists to assess and enhance sensorimotor performance and also increase the activities in the daily lives of patients. The game allows a player to control avatar movements through a Kinect Xbox, Myo armband and rudder foot pedal, and involves a series of reach-grasp-collect tasks whose difficulty levels are learnt by a fuzzy interface. The orientation, angular velocity, head and spine tilts and other data generated by the player are monitored and saved, whilst the task completion is calculated by solving an inverse kinematics algorithm which orientates the upper limb joints of the avatar. The different values in upper body quantities of movement provide fuzzy input from which crisp output is determined and used to generate an appropriate subsequent rehabilitation game level. The system can thus provide personalised, autonomously-learnt rehabilitation programmes for patients with neuromuscular disorders with superior predictions to guide the development of improved clinical protocols compared to traditional theraputic activities.

Source: An adaptive self-organizing fuzzy logic controller in a serious game for motor impairment rehabilitation – IEEE Xplore Document

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[ARTICLE] Rehabilitation of hemineglect of the left arm using movement detection bracelets activating a visual and acoustic alarm – Full Text

Abstract

Background

Hemineglect is frequent after right hemisphere stroke and prevents functional independence, but effective rehabilitation interventions are lacking. Our objective was to determine if a visual-acoustic alarm in the hemineglect arm activated by a certain discrepancy in movement of both hands can enhance neglect arm use in five tasks of daily living.

Methods

In this pre-post intervention study 9 stroke patients with residual hemineglect of the arm were trained for 7 days in five bimanual tasks of daily living: carrying a tray, button fastening, cutting food with knife and fork, washing the face with both hands and arm sway while walking. This was done through motion sensors mounted in bracelets on both wrists that compared movement between them. When the neglect-hand movement was less than a limit established by two fuzzy logic based classifiers, a visual-acoustic alarm in the neglect-hand bracelet was activated to encourage its use in the task.

Results

Both motion and function of the neglect hand improved during the seven days of training when visual-acoustic alarms were active but a worsening to baseline values occurred on day 8 and day 30 when alarms where switched off. Improvement was limited to vision-dependent tasks.

Conclusions

Neglect-hand improvement with this approach is limited to bimanual activities in which an object is manipulated under vision control, but no short or long term learning happens.

Background

In visual-spatial hemineglect (also known as hemi-inattention) patients with a lesion of the right cerebral hemisphere are not aware of objects in the left visual field despite not having a visual deficit. When it encompasses left limbs, as well as lacking awareness of them, the patient does not use the left arm in spite of not having paralysis. Neglect predicts not regaining functional independence [1]. In more than 85 % of patients with right hemispheric stroke, hemineglect is found in at least one pencil and paper tests such as cancellation of lines and marking lines in their middle point, copy of superimposed shapes or of a figurative drawing. But in 36 % of cases, neglect in activities of daily living cannot be detected by these tests [2]. Among the 28 standardized tests for hemineglect [3], the Catherine Bergego scale is one of the most used and asks about performance of the patient in activities of daily living but does not measure the performance itself. Several rehabilitation strategies for hemineglect have been used [4, 5] including forced visual sweep scanning, trunk rotation, application of muscle vibration in the neck, mental images, visual prisms, sensory activation of the left arm [6], vestibular stimulation on the left side, and transcranial magnetic stimulation [7]. Currently, there is insufficient evidence to recommend a particular rehabilitation strategy for neglect as shown by a Cochrane review that found no efficacy of rehabilitation interventions in reducing disability [8, 9]. In this pre-post intervention pilot study, we studied if a visual-acoustic alarm in the hemineglect arm activated by its reduced movement relative to the contralateral arm could increase neglect arm use in five tasks of daily living. To monitor arm movement, we used triaxial accelerometers, previously employed to measure upper limb movement after stroke [10, 11].

Continue —> Rehabilitation of hemineglect of the left arm using movement detection bracelets activating a visual and acoustic alarm | Journal of NeuroEngineering and Rehabilitation | Full Text

Fig. 1 Asymmetry of motion of the 9 subjects between the right and left hands without visual-acoustic alarms [baseline (B), day 8 and day 30] and days 1 to 7 of exercise of activities (E1-E7) with visual-acoustic alarms active

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[ARTICLE] A Fuzzy-based Adaptive Rehabilitation Framework for Home-based Wrist Training – Full Text PDF

Abstract

Computer-based rehabilitation systems have emerged as promising assistive tools for effective training and diagnosis and gained popularity in clinical settings.

For many patients, home-based rehabilitation can be really beneficial in their therapy journeys since it can eliminate the obstacles encountered by many of them in clinics, such as travel distance and cost. However, an effective home-training system requires a good adaptation mechanism that conforms to both the patient’s abilities and the therapist’s performance requirements.

This paper introduces a web-enabled wrist rehabilitation framework that adopts the fuzzy logic approach to provide adaptive tasks for the patient while taking into account the therapist training guidance.

We also assess the effectiveness of the framework while coping with different training parameters by simulating a number of performance scenarios and experimenting with normal subjects. Simulation results, as well as experimental analysis, demonstrated the ability of the proposed framework to adapt to patient’s performance and therapist’s feedback.

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[ARTICLE] A proposal for patient-tailored supervision of movement performance during end-effector-based robot-assisted rehabilitation of the upper extremities

Abstract

Millions of people worldwide suffer from stroke each year. One way to assist patients cost-effectively during their rehabilitation process is using end-effector-based robot-assisted rehabilitation. Such systems allow patients to use their own movement strategies to perform a movement task, which encourages them to do self-motivated training but also allow compensation movements if they have problems executing the movement tasks.

Therefore, a patient supervision system was developed on the basis of inertial measurement units and a patient-tailored movement interpretation system. Very light and small inertial measurement units were developed to record the patients’ movements during a teaching phase in which the desired movement is shown to the patient by a physiotherapist. During a following exercise phase, the patient is training the previously shown movement alone with the help of an end-effector-based robot-assisted rehabilitation system, and the patient’s movement is recorded again. The data from the teaching and exercise phases are compared with each other and evaluated by using fuzzy logic tailored to each patient. Experimental tests with one healthy subject and one stroke patient showed the capability of the system to supervise patient movements during the robot-assisted end-effector-based rehabilitation.

via A proposal for patient-tailored supervision of movement performance during end-effector-based robot-assisted rehabilitation of the upper extremities : Biomedical Engineering / Biomedizinische Technik.

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