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Robot-assisted vs. sensory integration training in treating gait and balance dysfunctions in patients with multiple sclerosis: a randomized controlled trial.

ABSTRACT: BACKGROUND:Extensive research on both healthy subjects and patients with central nervous damage has elucidated a crucial role of postural adjustment reactions and central sensory integration processes in generating and "shaping" locomotor function, respectively. Whether robotic-assisted gait devices might improve these functions in Multiple sclerosis (MS) patients is not fully investigated in literature. PURPOSE:The aim of this study was to compare the effectiveness of end-effector robot-assisted gait training (RAGT) and sensory integration balance training (SIBT) in improving walking and balance performance in patients with MS. METHODS:Twenty-two patients with MS (EDSS: 1.5-6.5) were randomly assigned to two groups. The RAGT group (n = 12) underwent end-effector system training. The SIBT group (n = 10) underwent specific balance exercises. Each patient received twelve 50-min treatment sessions (2 days/week). A blinded rater evaluated patients before and after treatment as well as 1 month post treatment. Primary outcomes were walking speed and Berg Balance Scale. Secondary outcomes were the Activities-specific Balance Confidence Scale, Sensory Organization Balance Test, Stabilometric Assessment, Fatigue Severity Scale, cadence, step length, single and double support time, Multiple Sclerosis Quality of Life-54. RESULTS:Between groups comparisons showed no significant differences on primary and secondary outcome measures over time. Within group comparisons showed significant improvements in both groups on the Berg Balance Scale (P = 0.001). Changes approaching significance were found on gait speed (P = 0.07) only in the RAGT group. Significant changes in balance task-related domains during standing and walking conditions were found in the SIBT group. CONCLUSION:Balance disorders in patients with MS may be ameliorated by RAGT and by SIBT.

SUBMITTER: Gandolfi M

PROVIDER: S-EPMC4033226 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Robot-assisted vs. sensory integration training in treating gait and balance dysfunctions in patients with multiple sclerosis: a randomized controlled trial.

Gandolfi Marialuisa M Geroin Christian C Picelli Alessandro A Munari Daniele D Waldner Andreas A Tamburin Stefano S Marchioretto Fabio F Smania Nicola N

Frontiers in human neuroscience 20140522

<h4>Background</h4>Extensive research on both healthy subjects and patients with central nervous damage has elucidated a crucial role of postural adjustment reactions and central sensory integration processes in generating and "shaping" locomotor function, respectively. Whether robotic-assisted gait devices might improve these functions in Multiple sclerosis (MS) patients is not fully investigated in literature.<h4>Purpose</h4>The aim of this study was to compare the effectiveness of end-effecto ...[more]

PMID: 24904361

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Project description:Background and Objectives: Gait disorders represent one of the most disabling aspects in multiple sclerosis (MS) that strongly influence patient quality of life. The improvement of walking ability is a primary goal for rehabilitation treatment. The aim of this study is to evaluate the effectiveness of robot-assisted gait training (RAGT) in association with physiotherapy treatment in patients affected by MS in comparison with ground conventional gait training. Study design: Randomized controlled crossover trial. Materials and Methods: Twenty-seven participants affected by MS with EDSS scores between 3.5 and 7 were enrolled, of whom seventeen completed the study. They received five training sessions per week over five weeks of conventional gait training with (experimental group) or without (control group) the inclusion of RAGT. The patients were prospectively evaluated before and after the first treatment session and, after the crossover phase, before and after the second treatment session. The evaluation was based on the 25-foot walk test (25FW, main outcome), 6 min walk test (6MWT), Tinetti Test, Modified Ashworth Scale, and modified Motricity Index for lower limbs. We also measured disability parameters using Functional Independence Measure and Quality of Life Index, and instrumental kinematic and gait parameters: knee extensor strength, double-time support, step length ratio; 17 patients reached the final evaluation. Results: Both groups significantly improved on gait parameters, motor abilities, and autonomy recovery in daily living activities with generally better results of RAGT over control treatment. In particular, the RAGT group improved more than control group in the 25FW (p = 0.004) and the 6MWT (p = 0.022). Conclusions: RAGT is a valid treatment option that in association with physiotherapy could induce positive effects in MS-correlated gait disorders. Our results showed greater effectiveness in recovering gait speed and resistance than conventional gait training.

Project description:BACKGROUND:A robotic exoskeleton device is an intelligent system designed to improve gait performance and quality of life for the wearer. Robotic technology has developed rapidly in recent years, and several robot-assisted gait devices were developed to enhance gait function and activities of daily living in elderly adults and patients with gait disorders. In this study, we investigated the effects of the Gait-enhancing Mechatronic System (GEMS), a new wearable robotic hip-assist device developed by Samsung Electronics Co, Ltd., Korea, on gait performance and foot pressure distribution in elderly adults. METHODS:Thirty elderly adults who had no neurological or musculoskeletal abnormalities affecting gait participated in this study. A three-dimensional (3D) motion capture system, surface electromyography and the F-Scan system were used to collect data on spatiotemporal gait parameters, muscle activity and foot pressure distribution under three conditions: free gait without robot assistance (FG), robot-assisted gait with zero torque (RAG-Z) and robot-assisted gait (RAG). RESULTS:We found increased gait speed, cadence, stride length and single support time in the RAG condition. Reduced rectus femoris and medial gastrocnemius muscle activity throughout the terminal stance phase and reduced effort of the medial gastrocnemius muscle throughout the pre-swing phase were also observed in the RAG condition. In addition, walking with the assistance of GEMS resulted in a significant increase in foot pressure distribution, specifically in maximum force and peak pressure of the total foot, medial masks, anterior masks and posterior masks. CONCLUSION:The results of the present study reveal that GEMS may present an alternative way of restoring age-related changes in gait such as gait instability with muscle weakness, reduced step force and lower foot pressure in elderly adults. In addition, GEMS improved gait performance by improving push-off power and walking speed and reducing muscle activity in the lower extremities. TRIAL REGISTRATION:NCT02843828 .

Project description:BackgroundMany patients with neurological movement disorders fear to fall while performing postural transitions without assistance, which prevents them from participating in daily life. To overcome this limitation, multi-directional Body Weight Support (BWS) systems have been developed allowing them to perform training in a safe environment. In addition to overground walking, these innovative/novel systems can assist patients to train many more gait-related tasks needed for daily life under very realistic conditions. The necessary assistance during the users' movements can be provided via task-dependent support designs. One remaining challenge is the manual switching between task-dependent supports. It is error-prone, cumbersome, distracts therapists and patients, and interrupts the training workflow. Hence, we propose a real-time motion onset recognition model that performs automatic support switching between standing-up and sitting-down transitions and other gait-related tasks (8 classes in total).MethodsTo predict the onsets of the gait-related tasks, three Inertial Measurement Units (IMUs) were attached to the sternum and middle of outer thighs of 19 controls without neurological movement disorders and two individuals with incomplete Spinal Cord Injury (iSCI). The data of IMUs obtained from different gait tasks was sent synchronously to a real-time data acquisition system through a custom-made Bluetooth-EtherCAT gateway. In the first step, data was applied offline for training five different classifiers. The best classifier was chosen based on F1-score results of a Leave-One-Participant-Out Cross-Validation (LOPOCV), which is an unbiased way of testing. In a final step, the chosen classifier was tested in real time with an additional control participant to demonstrate feasibility for real-time classification.ResultsTesting five different classifiers, the best performance was obtained in a single-layer neural network with 25 neurons. The F1-score of [Formula: see text] and [Formula: see text] are achieved on testing using LOPOCV and test data ([Formula: see text], participants = 20), respectively. Furthermore, the results from the implemented real-time classifier were compared with the offline classifier and revealed nearly identical performance (difference = [Formula: see text]).ConclusionsA neural network classifier was trained for identifying the onset of gait-related tasks in real time. Test data showed convincing performance for offline and real-time classification. This demonstrates the feasibility and potential for implementing real-time onset recognition in rehabilitation devices in future.

Project description:BackgroundBalance impairments are common in patients with infratentorial stroke. Although robot-assisted gait training (RAGT) exerts positive effects on balance among patients with stroke, it remains unclear whether such training is superior to conventional physical therapy (CPT). Therefore, we aimed to investigate the effects of RAGT combined with CPT and compared them with the effects of CPT only on balance and lower extremity function among survivors of infratentorial stroke.MethodsThis study was a single-blinded, randomized controlled trial with a crossover design conducted at a single rehabilitation hospital. Patients (n = 19; 16 men, three women; mean age: 47.4 ± 11.6 years) with infratentorial stroke were randomly allocated to either group A (4 weeks of RAGT+CPT, followed by 4 weeks of CPT+CPT) or group B (4 weeks of CPT+CPT followed by 4 weeks of RAGT+CPT). Changes in dynamic and static balance as indicated by Berg Balance Scale scores were regarded as the primary outcome measure. Outcome measures were evaluated for each participant at baseline and after each 4-week intervention period.ResultsNo significant differences in outcome-related variables were observed between group A and B at baseline. In addition, no significant time-by-group interactions were observed for any variables, indicating that intervention order had no effect on lower extremity function or balance. Significantly greater improvements in secondary functional outcomes such as lower extremity Fugl-Meyer assessment (FMA-LE) and scale for the assessment and rating of ataxia (SARA) were observed following the RAGT+CPT intervention than following the CPT+CPT intervention.ConclusionRAGT produces clinically significant improvements in balance and lower extremity function in individuals with infratentorial stroke. Thus, RAGT may be useful for patients with balance impairments secondary to other pathologies.Trial registrationClinicalTrials.gov Identifier NCT02680691. Registered 09 February 2016; retrospectively registered.

Dataset Information

Robot-assisted vs. sensory integration training in treating gait and balance dysfunctions in patients with multiple sclerosis: a randomized controlled trial.

Publications

Robot-assisted vs. sensory integration training in treating gait and balance dysfunctions in patients with multiple sclerosis: a randomized controlled trial.

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