ObjectivesSelf-management is a concept frequently used within healthcare but lacks consensus. It is the aim of this study to clarify the concept.DesignConcept analysis according to Walker and Avant, comprises eight steps: select concept, determine purpose, identify uses, determine defining attributes, identify model case, identify additional cases, identify antecedents and consequences and define empirical referents. Sources used: PubMed, Scopus and Web of Science.ResultsTen attributes delineating the concept have been identified and organised into three groups. Group (a): person-oriented attributes: the person must (1) actively take part in the care process, (2) take responsibility for the care process and (3) have a positive way of coping with adversity. Group (b): person-environment-oriented attributes: (4) the person must be informed about the condition, disease and treatment and self-management, (5) should be individualised, which entails expressing needs, values and priorities, (6) requires openness to ensure a reciprocal partnership with healthcare providers and (7) demands openness to social support. Finally, Group (c): summarising attributes: self-management (8) is a lifetime task, (9) assumes personal skills and (10) encompasses the medical, role and emotional management.ConclusionsThe findings of this study recognise the complexity of the concept, but also show the need for further investigation to make the concept more measurable. Clarity about the concept will enhance understanding and facilitate implementation in self-management programmes for chronic conditions.

Objective:To assess the effect of high-frequency repetitive transcranial magnetic stimulation (rTMS) on lower extremities motor score (LEMS) and gait in patients with motor incomplete spinal cord injury (SCI). Method: The prospective longitudinal randomized, double-blind study assessed 17 SCI patients ASIA D. We assessed LEMS, modified Ashworth Scale (MAS), 10-m walking test (10MWT), Walking Index for SCI (WISCI II) scale, step length, cadence, and Timed Up and Go (TUG) test at baseline, after the last of 15 daily sessions of rTMS and 2 weeks later. Patients were randomized to active rTMS or sham stimulation. Three patients from the initial group of 10 randomized to sham stimulation entered the active rTMS group after a 3-week washout period. Therefore a total of 10 patients completed each study condition. Both groups were homogeneous for age, gender, time since injury, etiology, and ASIA scale. Active rTMS consisted of 15 days of daily sessions of 20 trains of 40 pulses at 20 Hz and an intensity of 90% of resting motor threshold. rTMS was applied with a double cone coil to the leg motor area. Results: There was a significant improvement in LEMS in the active group (28.4 at baseline and 33.2 after stimulation; P = .004) but not in the sham group (29.6 at baseline, and 30.9 after stimulation; P = .6). The active group also showed significant improvements in the MAS, 10MWT, cadence, step length, and TUG, and these improvements were maintained 2 weeks later. Following sham stimulation, significant improvement was found only for step length and TUG. No significant changes were observed in the WISCI II scale in either group. Conclusion: High-frequency rTMS over the leg motor area can improve LEMS, spasticity, and gait in patients with motor incomplete SCI.

Here an inertial sensor-based monitoring system for measuring and analyzing upper limb movements is presented. The final goal is the integration of this motion-tracking device within a portable rehabilitation system for brain injury patients. A set of four inertial sensors mounted on a special garment worn by the patient provides the quaternions representing the patient upper limb’s orientation in space. A kinematic model is built to estimate 3D upper limb motion for accurate therapeutic evaluation. The human upper limb is represented as a kinematic chain of rigid bodies with three joints and six degrees of freedom. Validation of the system has been performed by co-registration of movements with a commercial optoelectronic tracking system. Successful results are shown that exhibit a high correlation among signals provided by both devices and obtained at the Institut Guttmann Neurorehabilitation Hospital.

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Exploring clients' priorities, the meanings they attributed to activities in daily life, and their underlying motives for goals should be part of therapeutic intervention. Children and their caregivers are valid and important sources for therapeutic goal setting. Basic human needs, e.g., for relatedness, competence (self-efficacy), autonomy, and meaningful personal orientation, should be considered when prioritizing goals for intervention. Implications for Rehabilitation Children are a valid and important source for therapeutic goal setting. Children's goals focused on activities and participation in all life areas, and half of the parents' goals on activities as relevant for productivity (followed by self-care and leisure), while teachers tended to prioritize goals at the body functions and structures level. The experience of their task performance affecting participation, and the basic needs for independence, relatedness (belonging to and being accepted by others), competence (self-efficacy), and joy through engagement in personally meaningful activities are main motives for children with developmental disabilities to choose their goals for intervention. A client-centred approach in working with children with developmental disabilities requires time and attention for exploring meaning-attributed activities for children and their proxies when collaboratively setting goals.

Co-adaptive training paradigms for event-related desynchronization (ERD) based brain-computer interfaces (BCI) have proven effective for healthy users. As of yet, it is not clear whether co-adaptive training paradigms can also benefit users with severe motor impairment. The primary goal of our paper was to evaluate a novel cue-guided, co-adaptive BCI training paradigm with severely impaired volunteers. The co-adaptive BCI supports a non-control state, which is an important step toward intuitive, self-paced control. A secondary aim was to have the same participants operate a specifically designed self-paced BCI training paradigm based on the auto-calibrated classifier. The co-adaptive BCI analyzed the electroencephalogram from three bipolar derivations (C3, Cz, and C4) online, while the 22 end users alternately performed right hand movement imagery (MI), left hand MI and relax with eyes open (non-control state). After less than five minutes, the BCI auto-calibrated and proceeded to provide visual feedback for the MI task that could be classified better against the non-control state. The BCI continued to regularly recalibrate. In every calibration step, the system performed trial-based outlier rejection and trained a linear discriminant analysis classifier based on one auto-selected logarithmic band-power feature. In 24 minutes of training, the co-adaptive BCI worked significantly (p = 0.01) better than chance for 18 of 22 end users. The self-paced BCI training paradigm worked significantly (p = 0.01) better than chance in 11 of 20 end users. The presented co-adaptive BCI complements existing approaches in that it supports a non-control state, requires very little setup time, requires no BCI expert and works online based on only two electrodes. The preliminary results from the self-paced BCI paradigm compare favorably to previous studies and the collected data will allow to further improve self-paced BCI systems for disabled users.

Brain-computer interfaces (BCIs) translate oscillatory electroencephalogram (EEG) patterns into action. Different mental activities modulate spontaneous EEG rhythms in various ways. Non-stationarity and inherent variability of EEG signals, however, make reliable recognition of modulated EEG patterns challenging. Able-bodied individuals who use a BCI for the first time achieve - on average - binary classification performance of about 75%. Performance in users with central nervous system (CNS) tissue damage is typically lower. User training generally enhances reliability of EEG pattern generation and thus also robustness of pattern recognition. In this study, we investigated the impact of mental tasks on binary classification performance in BCI users with central nervous system (CNS) tissue damage such as persons with stroke or spinal cord injury (SCI). Motor imagery (MI), that is the kinesthetic imagination of movement (e.g. squeezing a rubber ball with the right hand), is the "gold standard" and mainly used to modulate EEG patterns. Based on our recent results in able-bodied users, we hypothesized that pair-wise combination of "brain-teaser" (e.g. mental subtraction and mental word association) and "dynamic imagery" (e.g. hand and feet MI) tasks significantly increases classification performance of induced EEG patterns in the selected end-user group. Within-day (How stable is the classification within a day?) and between-day (How well does a model trained on day one perform on unseen data of day two?) analysis of variability of mental task pair classification in nine individuals confirmed the hypothesis. We found that the use of the classical MI task pair hand vs. feed leads to significantly lower classification accuracy - in average up to 15% less - in most users with stroke or SCI. User-specific selection of task pairs was again essential to enhance performance. We expect that the gained evidence will significantly contribute to make imagery-based BCI technology become accessible to a larger population of users including individuals with special needs due to CNS damage.

A Brain-Computer Interface (BCI) provides a completely new output pathway that can provide an additional option for a person to express himself/herself if he/she suffers a disorder like amyotrophic lateral sclerosis (ALS), brainstem stroke, brain or spinal cord injury or other diseases which impair the function of the common output pathways which are responsible for the control of muscles. For a P300 based BCI a matrix of randomly flashing characters is presented to the participant. To spell a character the person has to attend to it and to count how many times the character flashes. Although most BCIs are designed to help people with disabilities, they are mainly tested on healthy, young subjects who may achieve better results than people with impairments. In this study we compare measurements, performed on people suffering motor impairments, such as stroke or ALS, to measurements performed on healthy people. The overall accuracy of the persons with motor impairments reached 70.1% in comparison to 91% obtained for the group of healthy subjects. When looking at single subjects, one interesting example shows that under certain circumstances, when it is difficult for a patient to concentrate on one character for a longer period of time, the accuracy is higher when fewer flashes (i.e., stimuli) are presented. Furthermore, the influence of several tuning parameters is discussed as it shows that for some participants adaptations for achieving valuable spelling results are required. Finally, exclusion criteria for people who are not able to use the device are defined.