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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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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Powered exoskeletons for humans have long triggered the imagination. Merely two decades ago a role was envisaged for these devices in the assistance and rehabilitation of the impaired, and the number of powered exoskeletons for the upper and lower limbs has steadily grown ever since. Gait rehabilitation exoskeletons in particular were introduced to assist in the intensive and repetitive gait training of persons with gait impairment due to spinal cord injury, stroke and other neurological disorders. In this way physiotherapists could be relieved from the strenuous effort involved in gait assistance and patients could benefit from intensive and quantifiable assistive training.

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The clinical promise of deep brain stimulation (DBS) for neuropsychiatric conditions is coupled with the potential for ethical conflicts of interest because the work is so heavily reliant upon collaborations between academia, industry and the clinic. To foster transparency and public trust, we offer ethical guidance for the management of conflicts of interest in the conduct of DBS research and practice so that this nascent field can better balance competing goods and en-gineer new and better strategies for the amelioration of human suffering. We also hope that our ethical analysis will be of relevance to those working with other related neuroprosthetic devices, such brain- omputer interfaces and neural arrays, which naturally share many of the same concerns.

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