A large proportion of patients with spinal cord injury (SCI) regain ambulatory function. However, during the first 3 months most of the patients are not able to walk unsupported. To enable ambulatory training at such an early stage the body weight is partially relieved and the leg movements are assisted by two therapists. A more recent approach is the application of robotic based assis-tance which allows for longer training duration. From motor learning science and studies including patients with stroke, it is known
that training effects depend on the duration of the training. Longer trainings result in a better walking function. The aim of the present study is to evaluate if prolonged robot assisted walking training leads to a better walking outcome in patients with in-complete SCI and whether such training is feasible or has undesirable effects. Methods/Design: Patients from multiple sites with a subacute incomplete SCI and who are not able to walk independently will be randomized to either standard training (3-5 sessions per week, session duration maximum 25 minutes) or an intensive training (3-5 sessions per week, session duration minimum 50 minutes). After 8 weeks of training and 4 months later the walking ability, the occurrence of adverse events and the perceived rate of exer-tion as well as the patients’ impression of change will be compared between groups

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Movement-assist devices such as neuromuscular stimula-tion systems can be used to generate movements in people with chronic hand paralysis due to stroke. If de-tectable, motor planning activity in the cortex could be used in real time to trigger a movement-assist device and restore a person’s ability to perform many of the activities of daily living. Additionally, re-coupling motor planning in the cortex with assisted movement generation in the periphery may provide an even greater benefit—strengthening relevant synaptic connections over time to promote natural motor recove-ry. This study examined the potential for using electroencepha-lograms (EEGs) as a means of rapidly detec-ting the intent to open the hand during movement planning in individuals with moderate chronic hand paraly-sis following a subcortical ischemic stroke. On average, attempts to open the hand could be detected from EEGs approximately 100–500 ms prior to the first signs of movement onset. This earlier detection would mi-nimize device activation delays and allow for tighter coupling between initial formation of the motor plan in the cortex and augmentation of that plan in the periphery by a movement-assist device. This tight tempo-ral coupling may be important or even essential for strengthening synaptic connections and enhancing natu-ral motor recovery.

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A lower extremity exoskeleton, configurable to be coupled to a person, comprises two leg supports configurable to be coupled to the person’s lower limbs and configured to rest on the ground during their stance phases. Each leg support comprises a thigh link, a shank link, and two knee joints. Each knee joint is configured to allow flexion and extension between the respective shank link and the respective thigh link. The lower extremity exoskeleton also comprises an exoskeleton trunk configurable to be coupled to the person’s upper body. The exoskeleton trunk is rotatably connectable to the thigh links of the leg supports allowing for the flexion and extension between the leg supports and the exoskeleton trunk. In this exemplary embodiment, the energy required for flexion and extension movement between the shank link and the respective thigh link of a leg support over a cyclic knee motion is provided by the person.

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Tremor constitutes the most common motor disorder, and poses a functional problem to a large number of patients. Despite of the considerable experience in tremor management, current treatment based on drugs or surgery does not attain an effective attenuation in 25 % of patients, motivating the need for research in new therapeutic alternatives. In this context, this paper presents the concept design, development, and preliminary validation of a soft wearable robot for tremor assessment and suppression. The TREMOR neurorobot comprises a Brain Neural Computer Interface that monitors the whole neuromusculo-skeletal system, aiming at characteri-zing both voluntary movement and tremor, and a Functional Electrical Stimulation system that compensates for tremulous movements without impeding the user perform functional tasks. First results demonstrate the performance of the TREMOR neurorobot as a novel means of assessing and attenuating pathological tremors.

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In recent years, gait robots have become increasingly common for gait rehabilitation in non-ambulatory stroke patients. Cardiovascular treadmill training, which has been shown to provide great benefit to stroke survivors, cannot be performed with non-ambulatory patients. We there-fore integrated cardiovascular training in robot-assisted gait therapy to combine the benefits of both training modi. We developed a model of human heart rate as a function of exercise parameters during robot-assisted gait training and applied it for automatic control purposes. This structural model of the physio-logical processes describes the change in heart rate caused by treadmill speed and the power exchanged bet-ween robot and subject. We performed physiological parameter estimation for each tested individual and de-signed a model-based feedback controller to guide heart rate to a desired time profile. Five healthy sub-jects and eight stroke patients were recorded for model parameter identification, which was successfully used for heart rate control of three healthy subjects.We showed that a model-based control approach can take into account patient-specific limitations of treadmill speed as well as individual power expenditure.

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