929 resultados para upper limb, neck


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This paper proposes a first approach to Objective Motor Assessment (OMA) methodology. Also, it introduces the Dysfunctional profile (DP) concept. DP consists of a data matrix characterizing the Upper Limb (UL) physical alterations of a patient with Acquired Brain Injury (ABI) during the rehabilitation process. This research is based on the comparison methology of UL movement between subjects with ABI and healthy subjects as part of OMA. The purpose of this comparison is to classify subjects according to their motor control and subsequently issue a functional assessment of the movement. For this purpose Artificial Neural Networks (ANN) have been used to classify patients. Different network structures are tested. The obtained classification accuracy was 95.65%. This result allows the use of ANNs as a viable option for dysfunctional assessment. This work can be considered a pilot study for further research to corroborate these results.

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While a number of virtual data-gloves have been used in stroke, there is little evidence about their use in spinal cord injury (SCI). A pilot clinical experience with nine SCI subjects was performed comparing two groups: one carried out a virtual rehabilitation training based on the use of a data glove, CyberTouch combined with traditional rehabilitation, during 30 minutes a day twice a week along two weeks; while the other made only conventional rehabilitation. Furthermore, two functional indexes were developed in order to assess the patient’s performance of the sessions: normalized trajectory lengths and repeatability. While differences between groups were not statistically significant, the data-glove group seemed to obtain better results in the muscle balance and functional parameters, and in the dexterity, coordination and fine grip tests. Related to the indexes that we implemented, normalized trajectory lengths and repeatability, every patient showed an improvement in at least one of the indexes, either along Y-axis trajectory or Z-axis trajectory. This study might be a step in investigating new ways of treatments and objective measures in order to obtain more accurate data about the patient’s evolution, allowing the clinicians to develop rehabilitation treatments, adapted to the abilities and needs of the patients.

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Three-dimensional kinematic analysis provides quantitative assessment of upper limb motion and is used as an outcome measure to evaluate movement disorders. The aim of the present study is to present a set of kinematic metrics for quantifying characteristics of movement performance and the functional status of the subject during the execution of the activity of daily living (ADL) of drinking from a glass. Then, the objective is to apply these metrics in healthy people and a population with cervical spinal cord injury (SCI), and to analyze the metrics ability to discriminate between healthy and pathologic people. 19 people participated in the study: 7 subjects with metameric level C6 tetraplegia, 4 subjects with metameric level C7 tetraplegia and 8 healthy subjects. The movement was recorded with a photogrammetry system. The ADL of drinking was divided into a series of clearly identifiable phases to facilitate analysis. Metrics describing the time of the reaching phase, the range of motion of the joints analyzed, and characteristics of movement performance such as the efficiency, accuracy and smoothness of the distal segment and inter-joint coordination were obtained. The performance of the drinking task was more variable in people with SCI compared to the control group in relation to the metrics measured. Reaching time was longer in SCI groups. The proposed metrics showed capability to discriminate between healthy and pathologic people. Relative deficits in efficiency were larger in SCI people than in controls. These metrics can provide useful information in a clinical setting about the quality of the movement performed by healthy and SCI people during functional activities.

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Purpose. This study investigated stroke survivors' perspective of upper limb recovery after stroke. The aim was to determine factors other than medical diagnosis and co-morbidities that contribute to recovery. The objectives were to explore how stroke survivors define recovery, identify factors they believe influence recovery and determine strategies used to maximize upper limb recovery. Method. A qualitative study consisting of three focus groups and two in-depth interviews was conducted with stroke survivors (n = 19) and spouses ( n = 9) in metropolitan, regional and rural Queensland, Australia. Data were analysed using principles of grounded theory. Results. Stroke survivors maximize upper limb recovery by 'keeping the door open' a process of continuing to hope for and work towards improvement amidst adjusting to life with stroke. They achieve this by 'hanging in there', 'drawing on support from others', 'getting going and keeping going with exercise', and 'finding out how to keep moving ahead'. Conclusions. This study provides valuable insight into the personal experience of upper limb recovery after stroke. It highlights the need to develop training strategies that match the needs and aspirations of stroke survivors and that place no time limits on recovery. It reinforces the benefits of stroke support groups and advocates their incorporation into stroke recovery services. These findings can be used to guide both the development and evaluation of stroke survivor centred upper limb training programmes.

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Peer reviewed

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New motor rehabilitation therapies include virtual reality (VR) and robotic technologies. In limb rehabilitation, limb posture is required to (1) provide a limb realistic representation in VR games and (2) assess the patient improvement. When exoskeleton devices are used in the therapy, the measurements of their joint angles cannot be directly used to represent the posture of the patient limb, since the human and exoskeleton kinematic models differ. In response to this shortcoming, we propose a method to estimate the posture of the human limb attached to the exoskeleton. We use the exoskeleton joint angles measurements and the constraints of the exoskeleton on the limb to estimate the human limb joints angles. This paper presents (a) the mathematical formulation and solution to the problem, (b) the implementation of the proposed solution on a commercial exoskeleton system for the upper limb rehabilitation, (c) its integration into a rehabilitation VR game platform, and (d) the quantitative assessment of the method during elbow and wrist analytic training. Results show that this method properly estimates the limb posture to (i) animate avatars that represent the patient in VR games and (ii) obtain kinematic data for the patient assessment during elbow and wrist analytic rehabilitation.