Dataset Information

Rapid changes in arousal states of healthy volunteers during robot-assisted gait training: a quantitative time-series electroencephalography study.

ABSTRACT:

Background

Robot-assisted gait training (RAGT) is expected to be an effective rehabilitative intervention for patients with gait disturbances. However, the monotonous gait pattern provided by robotic guidance tends to induce sleepiness, and the resultant decreased arousal during RAGT may negatively affect gait training progress. This study assessed electroencephalography (EEG)-based, objective sleepiness during RAGT and examined whether verbal or nonverbal warning sounds are effective stimuli for counteracting such sleepiness.

Methods

Twelve healthy men walked on a treadmill for 6 min, while being guided by a Gait-Assistance Robot, under 3 experimental conditions: with sine-wave sound stimulation (SS), verbal sound stimulation (VS), and no sound stimulation (NS). The volunteers were provided with warning sound stimulation at 4 min (ST1), 4 min 20 s (ST2), 4 min 40 s (ST3), and 5 min (ST4) after the start of RAGT. EEGs were recorded at the central (Cz) and occipital (O1 and O2) regions (International 10-20 system) before and during RAGT, and 4-s segments of EEG data were extracted from the filtered data during the 8 experimental periods: middle of the eyes-closed condition; middle of the eyes-open condition; beginning of RAGT; immediately before ST1; immediately after ST1, ST2, ST3, and ST4. According to the method used in the Karolinska drowsiness test, the power densities of the theta, alpha 1, and alpha 2 bands were calculated as indices of objective sleepiness.

Results

Comparisons of the findings between baseline and before ST showed that the power densities of the alpha 1 and 2 bands tended to increase, whereas the theta power density increased significantly (P?ConclusionsThis study is the first to demonstrate that EEG-measured arousal levels decrease within a short time during RAGT, but are restored and maintained by intermittent warning sound stimulation.

SUBMITTER: Nakanishi Y

PROVIDER: S-EPMC4022364 | biostudies-literature | 2014 Apr

REPOSITORIES: biostudies-literature

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Publications

Rapid changes in arousal states of healthy volunteers during robot-assisted gait training: a quantitative time-series electroencephalography study.

Nakanishi Yoshie Y Wada Futoshi F Saeki Satoru S Hachisuka Kenji K

Journal of neuroengineering and rehabilitation 20140412

<h4>Background</h4>Robot-assisted gait training (RAGT) is expected to be an effective rehabilitative intervention for patients with gait disturbances. However, the monotonous gait pattern provided by robotic guidance tends to induce sleepiness, and the resultant decreased arousal during RAGT may negatively affect gait training progress. This study assessed electroencephalography (EEG)-based, objective sleepiness during RAGT and examined whether verbal or nonverbal warning sounds are effective st ...[more]

PMID: 24725811

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Project description:Background: The limitation to the use of ElectroMyoGraphy (sEMG) in rehabilitation services is in contrast with its potential diagnostic capacity for rational planning and monitoring of the rehabilitation treatments, especially the overground Robot-Assisted Gait Training (o-RAGT). Objective: To assess the barriers to the implementation of a sEMG-based assessment protocol in a clinical context for evaluating the effects of o-RAGT in subacute stroke patients. Methods: An observational study was conducted in a rehabilitation hospital. The primary outcome was the success rate of the implementation of the sEMG-based assessment. The number of dropouts and the motivations have been registered. A detailed report on difficulties in implementing the sEMG protocol has been edited for each patient. The educational level and the working status of the staff have been registered. Each member of staff completed a brief survey indicating their level of knowledge of sEMG, using a five-point Likert scale. Results: The sEMG protocol was carried out by a multidisciplinary team composed of Physical Therapists (PTs) and Biomedical Engineers (BEs). Indeed, the educational level and the expertise of the members of staff influenced the fulfillment of the implementation of the study. The PTs involved in the study did not receive any formal education on sEMG during their course of study. The low success rate (22.7%) of the protocol was caused by several factors which could be grouped in: patient-related barriers; cultural barriers; technical barriers; and administrative barriers. Conclusions: Since a series of barriers limited the use of sEMG in the clinical rehabilitative environment, concrete actions are needed for disseminating sEMG in rehabilitation services. The sEMG assessment should be included in health systems regulations and specific education should be part of the rehabilitation professionals' curriculum. Clinical Trial Registration: www.ClinicalTrials.gov, identifier: NCT03395717.

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Project description:BACKGROUND:Gait disorders are major symptoms of neurological diseases affecting the quality of life. Interventions that restore walking and allow patients to maintain safe and independent mobility are essential. Robot-assisted gait training (RAGT) proved to be a promising treatment for restoring and improving the ability to walk. Due to heterogenuous study designs and fragmentary knowlegde about the neural correlates associated with RAGT and the relation to motor recovery, guidelines for an individually optimized therapy can hardly be derived. To optimize robotic rehabilitation, it is crucial to understand how robotic assistance affect locomotor control and its underlying brain activity. Thus, this study aimed to investigate the effects of robotic assistance (RA) during treadmill walking (TW) on cortical activity and the relationship between RA-related changes of cortical activity and biomechanical gait characteristics. METHODS:Twelve healthy, right-handed volunteers (9 females; M?=?25?±?4?years) performed unassisted walking (UAW) and robot-assisted walking (RAW) trials on a treadmill, at 2.8?km/h, in a randomized, within-subject design. Ground reaction forces (GRFs) provided information regarding the individual gait patterns, while brain activity was examined by measuring cerebral hemodynamic changes in brain regions associated with the cortical locomotor network, including the sensorimotor cortex (SMC), premotor cortex (PMC) and supplementary motor area (SMA), using functional near-infrared spectroscopy (fNIRS). RESULTS:A statistically significant increase in brain activity was observed in the SMC compared with the PMC and SMA (p?<?0.05), and a classical double bump in the vertical GRF was observed during both UAW and RAW throughout the stance phase. However, intraindividual gait variability increased significantly with RA and was correlated with increased brain activity in the SMC (p?=?0.05; r?=?0.57). CONCLUSIONS:On the one hand, robotic guidance could generate sensory feedback that promotes active participation, leading to increased gait variability and somatosensory brain activity. On the other hand, changes in brain activity and biomechanical gait characteristics may also be due to the sensory feedback of the robot, which disrupts the cortical network of automated walking in healthy individuals. More comprehensive neurophysiological studies both in laboratory and in clinical settings are necessary to investigate the entire brain network associated with RAW.

Project description:BackgroundRobot-assisted gait training (RAGT) was developed to restore gait function by promoting neuroplasticity through repetitive locomotor training and has been utilized in gait training. However, contradictory outcomes of RAGT have been reported for patients with Parkinson's disease (PD). In addition, the mechanism of the RAGT treatment effect is still unknown. This study aims to investigate the effects of RAGT on gait velocity in patients with PD and to unveil the mechanisms of these effects.MethodsThis is a prospective, single-blind, single-center, randomized controlled trial. Eligible participants will be randomly allocated to: 1) a Walkbot-S™ RAGT group or 2) a treadmill training group. The participants will receive three 45-min sessions of each intervention per week for 4?weeks. Gait speed during RAGT will be targeted to the maximal speed depending on the participant's height; the same principle will be applied to the treadmill training group to match the training intensity. The primary outcome measure is gait speed measured by the 10-Meter Walk Test at a comfortable pace under single-task conditions. Secondary outcomes include dual-task interference, the Berg Balance Scale, Timed Up and Go test, the Korean version of the Falls Efficacy Scale-International, New Freezing of Gait Questionnaire, Movement Disorder Society-sponsored revision of the Unified Parkinson's Disease Rating Scale, and functional connectivity measured by resting-state functional magnetic resonance imaging. Baseline assessments (T0) will be conducted to acquire clinical characteristics and outcome measure values before the intervention. Postintervention assessments (T1) will compare immediate efficacies within 3 days after the intervention. Follow-up assessments (T2) will be conducted 1 month after the intervention. Considering an alpha of 0.05 and a power of 80%, the total number of participants to be recruited is 44.DiscussionThis study will reveal the effect of RAGT using an exoskeletal robot, not only on gait speed, but also on gait automaticity, balance function, fall risk, quality of life, and disease severity. In addition, the study will shed new light on the mechanism of the RAGT effect by evaluating changes in gait automaticity and brain functional networks.Trial registrationClinicalTrials.gov, NCT03490578 . Registered on 21 March 2018.

Dataset Information

Rapid changes in arousal states of healthy volunteers during robot-assisted gait training: a quantitative time-series electroencephalography study.

Background

Methods

Results

Publications

Rapid changes in arousal states of healthy volunteers during robot-assisted gait training: a quantitative time-series electroencephalography study.

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