Background and Purpose-The success of gait rehabilitation after stroke depends on active walking exercises. However, the disabling after-effects of stroke often make such exercises impossible at the onset of therapy. To facilitate treadmill training of paraparetic patients, a robot-driven gait orthosis (Lokomat) was developed. We investigated the effects of the Lokomat when used with hemiparetic patients. Methods-The authors conducted a randomized, controlled pilot study of 30 acute stroke survivors. The treatment group received 30 minutes of robotic training daily and the control group 30 minutes of conventional physiotherapy daily in addition to 30 minutes of conventional physiotherapy for each group. Outcome measures were independence of gait, gait speed, gait parameters, and body tissue composition. Results-After 4 weeks of therapy, the walking ability of the Lokomat group and the control group expressed as the functional ambulation classification was significantly improved. The functional ambulation category (medianϮ interquartile range) was at baseline 0Ϯ0 in control and 0Ϯ1 in the therapy group and increased after therapy to 1Ϯ3 in both groups significantly (Pϭ0.01). There was no significant difference in gain of these parameters between the groups. The Lokomat group had a significantly longer single stance phase (sec; meanϮSEM) on the paretic leg when walking on the floor. At baseline, it was 0.19Ϯ0.17 and after therapy 0.49Ϯ0.07 (Pϭ0.014). The control group had increased their body weight approximately 1.33Ϯ1.40 kg (meanϮSEM; Pϭ0.046), mostly as fat mass, whereas the Lokomat group had lost fat mass approximately Ϫ2.9Ϯ1.0 kg (meanϮSEM; Pϭ0.016) and increased their muscle mass approximately 3.36Ϯ1.4 kg (meanϮ SEM; Pϭ0.031). Conclusions-This pilot study indicates that Lokomat therapy is a promising intervention for gait rehabilitation. Although there was no difference between groups in gain of functional scores, the Lokomat group showed an advantage of robotic training over conventional physiotherapy in improvement of gait abnormality and body tissue composition. (Stroke.

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Patients tolerate greater degrees of head-up tilt better with simultaneous leg movement.

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One major aim of the neurological rehabilitation of patients with severe disorders of consciousness (DOC) is to enhance patients’ arousal and ability to communicate. Mobilization into a standing position by means of a tilt table has been shown to improve their arousal and awareness. However, due to the frequent occurrence of syncopes on a tilt table, it is easier to accomplish verticalization using a tilt table with an integrated stepping device. The objective of this randomized controlled clinical trial was to evaluate the effectiveness of a tilt table therapy with or without an integrated stepping device on the level of consciousness. A total of 50 participants in vegetative or minimally conscious states 4 weeks to 6 month after injury were treated with verticalization during this randomized controlled trial. Interventions involved ten 1-hour sessions of the specific treatment over a 3-week period. Blinded assessors made measurements before and after the intervention period, as well as after a 3-week follow-up period. The coma recovery scale-revised (CRS-R) showed an improvement by a median of 2 points for the group receiving tilt table with integrated stepping (Erigo). The rate of recovery of the group receiving the conventional tilt table therapy significantly increased by 5 points during treatment and by an additional 2 points during the 3-week follow-up period. Changes in spasticity did not significantly differ between the two intervention groups. Compared to the conventional tilt table, the tilt table with integrated stepping device failed to have any additional benefit for DOC patients. Verticalization itself seems to be beneficial though and should be administered to patients in DOC in early rehabilitation. Trial Registration: Current Controlled Trials Ltd (www.controlled-trials.com), identifier number ISRCTN72853718

Abstract-Robot-assisted treadmill training is an established intervention used to improve walking ability in patients with neurological disorders. Although it has been shown that attention to the task is a key factor for successful rehabilitation, the psychological state of patients during robot-assisted gait therapy is often neglected. We presented 17 nondisabled subjects and 10 patients with neurological disorders a virtual-reality task with varying difficulty levels to induce feelings of being bored, excited, and overstressed. We developed an approach to automatically estimate and classify a patient's psychological state, i.e., his or her mental engagement, in real time during gait training. We used psychophysiological measurements to obtain an objective measure of the current psychological state. Automatic classification was performed by a neural network. We found that heart rate, skin conductance responses, and skin temperature can be used as markers for psychological states in the presence of physical effort induced by walking. The classifier achieved a classification error of 1.4% for nondisabled subjects and 2.1% for patients with neurological disorders. Using our new method, we processed the psychological state data in real time. Our method is a first step toward real-time auto-adaptive gait training with potential to improve rehabilitation results by optimally challenging patients at all times during exercise.