न्यूरोरिहेबिलिटेशन के अंतर्राष्ट्रीय जर्नल

This study aimed to show that important fall risk measures among the elderly can be classified using multiple parameters obtained from wearable inertial sensors. The timed up-and-go (TUG) test, a well-known standard assessment test, was used to evaluate the risk of falling among elderly individuals. The use of wearable inertial sensors enables extraction of triaxial acceleration and angular velocity signals for offline analysis. Thirty-eight elderly patients from Fujimoto Hayasuzu Hospital participated in this study. Specific results were provided from the signals obtained from acceleration and angular velocity, and analysis was carried out in each phase of various activities, such as sit-to-stand, walking, etc. Seventy-eight parameters were obtained from the extracted acceleration and angular velocity signals in all phases to classify the risk of falling among the elderly. Using principle component analysis, the most important measures were selected from the gathered parameters. The most influential measure in differentiating subjects with high and low fall risks was the turning angular velocity signal.

We investigated spinal neuron function during relaxation imagery by analyzing F-waves generated from the left thenar muscles in response to stimulation of the left median nerve at the wrist in 10 healthy subjects. F-waves were recorded in a resting position and during, immediately after, and at 5, 10, and 15 min after a 2-min relaxation imagery period. Persistence, F/M amplitude ratio, and latency were analyzed from the recorded F-waves. The F/M amplitude ratio was lower in the relaxation imagery condition than in the resting condition, whereas it either recovered or continued to decrease after relaxation imagery. There were no significant differences in persistence and latency before, during, and after relaxation imagery. These results suggested that 2-min relaxation imagery can decrease spinal neural function in healthy subjects and may be useful as a new type of physical therapy for patients suffering from impaired motor control.

Introduction: Botulinum toxin is considered a first-line treatment for focal spasticity after stroke, and its peripheral effects have been well documented. We set out to demonstrate and describe any effects it may have in the central nervous system, using fMRI to record brain activation patterns before and after its administration.
Materials and Methods: 17 subjects comprising 7 ischemic stroke patients affected by upper limb spastic hemiplegia, and 10 healthy controls were recruited and underwent three fMRI scans while performing a motor imagery task (finger tapping). Test subjects underwent fMRI before botulinum toxin therapy (T0), 4 weeks later (T1), and after 8 weeks (T2), and untreated control subjects were tested at 0, 4 and 8 weeks. The finger-tapping task was performed twice each session in both groups. Both test and control subjects performed only daily passive muscle stretching exercises between T0, T1, and T2 MR scans.
Results: fMRI confirmed the technical feasibility of the “motor imagery” paradigm in activating the motor areas in healthy subjects. While second-level analysis of the control group showed no modification in the pattern of brain activation during the finger-tapping imagery task between T0, T1, and T2, increasing focalization of mean brain activation, accompanied by a gradual reduction in secondary motor area activation after treatment (SMA and Brodmann 6) in the test group.
Conclusions: This confirms the efficacy of motor imagery as an fMRI paradigm to open a “window” into the brain that enables us to study the processes of motor function recovery after stroke in vivo. Our data show that peripheral injection of botulinum toxin alone brings about a progressive alteration in the reorganization of cortical activation after stroke, thereby confirming its therapeutic and central effects. The progressive reduction and greater focalization of activation seen continued over time, in line with the latest “small world network” theories on cortical and subcortical reorganization of cerebral functions after stroke.

Favourable outcome after cerebrovascular stroke is associated with early admission to rehabilitation, small lesion size and minor cognitive impairment. The aim of the present study was to explore factors associated with the amelioration of neglect after right hemisphere stroke. Twenty-one consecutive eligible right hemisphere stroke patients in one rehabilitation center were assessed and followed for 6 months. The neglect syndrome was assessed by the conventional subtests of the Behavioural Inattention Test (BIT) and by the Catherine Bergego Scale (CBS) before and after the 3-week rehabilitation and at 6-month follow-up. The manifestations of extinction, pusher syndrome and depression were evaluated. Recovery from neglect was strongly associated with early rehabilitation and the initial severity of neglect. Intensive treatment yielded recovery in severe or moderate visual neglect long after the first two to three months after stroke. Even chronic patients with sufficient cognitive and psychological capacity improved with intensive rehabilitation. Tactile extinction was common in these patients but was not associated with recovery. Manifestations of pusher syndrome hampered amelioration of visual neglect in acute and sub-acute stroke patients, whereas depression did not prevent recovery from neglect. Intensive rehabilitation promotes recovery from neglect in the acute phase after right hemisphere stroke. A comprehensive program later, in sub-acute or chronic phase, may also be effective especially in those patients who have not received intensive multi-professional rehabilitation soon after the stroke.

Brain-machine interface techniques have been applied in a number of studies to control neuromotor prostheses and for neuro-rehabilitation in the hopes of providing a means to restore lost motor function. Electrocorticography has seen recent use in this regard because it offers a higher spatiotemporal resolution than non-invasive electroencephalography and is less invasive than intracortical microelectrodes. Despite lots of successful studies; none of study has dealt with the importance of both kinematic and kinetic information for the purpose of realizing an ECoG-based neuroprosthesis. Here, we review the decoding kinetic and kinematic information from electrocorticograms. First, we introduce our preprocessing method for decoding of muscle activities, hand trajectories, and joint angles with our previous works. Second, we review and discuss about three questions: which locations are most effective area for decoding, how different numbers of effective electrocorticography signals affect decoding performance, and which frequency band is most effective? We foresee the proposed method contributing to future advancements in neuro-prosthesis and neurorehabilitation technology.

Introduction: This research aimed to assess the accuracy of a portable multi-sensor device (SenseWear armband) measuring energy expenditure in people with stroke compared with indirect calorimetry at rest and during treadmill walking. Secondary aims were to determine if there was a difference depending on which arm the device was placed and to determine the accuracy of the armband step count.
Materials and Methods: Ten stroke survivors (mean age 64.3 SD 7.7 years; 70% male) wore an armband on each arm and metabolic facemask. Energy expenditure was measured at rest and during two 10-minute bouts of treadmill walking at different speeds separated with a seated rest.
Results: The armband was accurate for measuring energy expenditure at rest (Intraclass correlations (ICC) > 0.869), with poor to fair accuracy during treadmill walking (ICC>0.306). The non-hemiplegic arm provided more accurate energy expenditure measurement (ICC>0.409), underestimating with 10%-15% absolute percentage error. SenseWear armband was inaccurate for measuring step count (absolute percentage error approximately 30%).
Conclusion: These results suggest that SenseWear armband lacks accuracy for measuring energy expenditure during treadmill walking in people with stroke; with the non-hemiplegic arm the most accurate. The armband is inaccurate measuring step count. Revision of algorithms specific for people following stroke may improve accuracy.