scholarly journals Kinematic Parameters for Tracking Patient Progress during Upper Limb Robot-Assisted Rehabilitation: An Observational Study on Subacute Stroke Subjects

2019 ◽  
Vol 2019 ◽  
pp. 1-12
Author(s):  
Michela Goffredo ◽  
Stefano Mazzoleni ◽  
Annalisa Gison ◽  
Francesco Infarinato ◽  
Sanaz Pournajaf ◽  
...  
Keyword(s):  
Upper Limb ◽  
Motor Performance ◽  
Time Course ◽  
Motor Impairment ◽  
Kinematic Parameters ◽  
Kinematic Data ◽  
Subacute Stroke ◽  
Severe Motor ◽  
Severe Motor Impairment ◽  
Point To Point

Background. Upper limb robot-assisted therapy (RT) provides intensive, repetitive, and task-specific treatment, and its efficacy for stroke survivors is well established in literature. Biomechanical data from robotic devices has been widely employed for patient’s assessment, but rarely it has been analysed for tracking patient progress during RT. The goal of this retrospective study is to analyse built-in kinematic data registered by a planar end-effector robot for assessing the time course of motor recovery and patient’s workspace exploration skills. A comparison of subjects having mild and severe motor impairment has been also conducted. For that purpose, kinematic data recorded by a planar end-effector robot have been processed for investigating how motor performance in executing point-to-point trajectories with different directions changes during RT.Methods. Observational retrospective study of 68 subacute stroke patients who conducted 20 daily sessions of upper limb RT with the InMotion 2.0 (Bionik Laboratories, USA): planar point-to-point reaching tasks with an “assist as needed” strategy. The following kinematic parameters (KPs) were computed for each subject and for each point-to-point trajectory executed during RT: movement accuracy, movement speed, number of peak speed, and task completion time. The Wilcoxon signed-rank tests were used with clinical outcomes. the Friedman test and post hoc Conover’s test (Bonferroni’s correction) were applied to KPs. A secondary data analysis has been conducted by comparing patients having different severities of motor impairment. The level of significance was set atpvalue < 0.05.Results. At the RT onset, the movements were less accurate and smoothed, and showed higher times of execution than those executed at the end of treatment. The analysis of the time course of KPs highlighted that RT seems to improve the motor function mainly in the first sessions of treatment: most KPs show significant intersession differences during the first 5/10 sessions. Afterwards, no further significant variations occurred. The ability to perform movements away from the body and from the hemiparetic side remains more challenging. The results obtained from the data stratification show significant differences between subjects with mild and severe motor impairment.Conclusion. Significant improvements in motor performance were registered during the time course of upper limb RT in subacute stroke patients. The outcomes depend on movement direction and motor impairment and pave the way to optimize healthcare resources and to design patient-tailored rehabilitative protocols.

scholarly journals Retrospective Robot-Measured Upper Limb Kinematic Data From Stroke Patients Are Novel Biomarkers

2021 ◽  
Vol 12 ◽  
Author(s):  
Michela Goffredo ◽  
Sanaz Pournajaf ◽  
Stefania Proietti ◽  
Annalisa Gison ◽  
Federico Posteraro ◽  
...  
Keyword(s):  
Upper Limb ◽  
External Rotation ◽  
Predictive Biomarkers ◽  
Motor Recovery ◽  
Post Treatment ◽  
Kinematic Parameters ◽  
Kinematic Data ◽  
Subacute Stroke ◽  
Flexion Extension ◽  
Pre Treatment

Background: The efficacy of upper-limb Robot-assisted Therapy (ulRT) in stroke subjects is well-established. The robot-measured kinematic data can assess the biomechanical changes induced by ulRT and the progress of patient over time. However, literature on the analysis of pre-treatment kinematic parameters as predictive biomarkers of upper limb recovery is limited.Objective: The aim of this study was to calculate pre-treatment kinematic parameters from point-to-point reaching movements in different directions and to identify biomarkers of upper-limb motor recovery in subacute stroke subjects after ulRT.Methods: An observational retrospective study was conducted on 66 subacute stroke subjects who underwent ulRT with an end-effector robot. Kinematic parameters were calculated from the robot-measured trajectories during movements in different directions. A Generalized Linear Model (GLM) was applied considering the post-treatment Upper Limb Motricity Index and the kinematic parameters (from demanding directions of movement) as dependent variables, and the pre-treatment kinematic parameters as independent variables.Results: A subset of kinematic parameters significantly predicted the motor impairment after ulRT: the accuracy in adduction and internal rotation movements of the shoulder was the major predictor of post-treatment Upper Limb Motricity Index. The post-treatment kinematic parameters of the most demanding directions of movement significantly depended on the ability to execute elbow flexion-extension and abduction and external rotation movements of the shoulder at baseline.Conclusions: The multidirectional analysis of robot-measured kinematic data predicts motor recovery in subacute stroke survivors and paves the way in identifying subjects who may benefit more from ulRT.

Implementation of an SSVEP-based intelligent home service robot system

2020 ◽  
pp. 1-16
Author(s):  
Yuxin Zhang ◽  
Qiang Gao ◽  
Yu Song ◽  
Zhe Wang
Keyword(s):  
Brain Activity ◽  
Neuromuscular Disorders ◽  
Motor Impairment ◽  
Service Robot ◽  
Task Completion ◽  
Home Service Robot ◽  
Home Service ◽  
Severe Motor ◽  
Severe Motor Impairment ◽  
The Subject

BACKGROUND: People with severe neuromuscular disorders caused by an accident or congenital disease cannot normally interact with the physical environment. The intelligent robot technology offers the possibility to solve this problem. However, the robot can hardly carry out the task without understanding the subject’s intention as it relays on speech or gestures. Brain-computer interface (BCI), a communication system that operates external devices by directly converting brain activity into digital signals, provides a solution for this. OBJECTIVE: In this study, a noninvasive BCI-based humanoid robotic system was designed and implemented for home service. METHODS: A humanoid robot that is equipped with multi-sensors navigates to the object placement area under the guidance of a specific symbol “Naomark”, which has a unique ID, and then sends the information of the scanned object back to the user interface. Based on this information, the subject gives commands to the robot to grab the wanted object and give it to the subject. To identify the subject’s intention, the channel projection-based canonical correlation analysis (CP-CCA) method was utilized for the steady state visual evoked potential-based BCI system. RESULTS: The offline results showed that the average classification accuracy of all subjects reached 90%, and the online task completion rate was over 95%. CONCLUSION: Users can complete the grab task with minimum commands, avoiding the control burden caused by complex commands. This would provide a useful assistance means for people with severe motor impairment in their daily life.

scholarly journals Combined Brain and Peripheral Nerve Stimulation in Chronic Stroke Patients With Moderate to Severe Motor Impairment

2017 ◽  
Vol 21 (2) ◽  
pp. 176-183 ◽  
Author(s):  
Isabella S. Menezes ◽  
Leonardo G. Cohen ◽  
Eduardo A. Mello ◽  
André G. Machado ◽  
Paul Hunter Peckham ◽  
...  
Keyword(s):  
Peripheral Nerve ◽  
Nerve Stimulation ◽  
Motor Impairment ◽  
Chronic Stroke ◽  
Peripheral Nerve Stimulation ◽  
Stroke Patients ◽  
Severe Motor ◽  
Severe Motor Impairment

scholarly journals Movement Kinematics of the Ipsilesional Upper Extremity in Persons With Moderate or Mild Stroke

2017 ◽  
Vol 31 (4) ◽  
pp. 376-386 ◽  
Author(s):  
Eva-Lena Bustrén ◽  
Katharina Stibrant Sunnerhagen ◽  
Margit Alt Murphy
Keyword(s):  
Upper Extremity ◽  
Movement Time ◽  
Motor Impairment ◽  
Stroke Severity ◽  
Movement Kinematics ◽  
Movement Performance ◽  
Severe Motor ◽  
Daily Task ◽  
Severe Motor Impairment ◽  
Mild Stroke

Background. An increasing number of studies have indicated that the ipsilesional arm may be impaired after stroke. There is, however, a lack of knowledge whether ipsilesional deficits influence movement performance during purposeful daily tasks. Objective. The aim of this study was to investigate whether, and to what extent, movement impairments are present while performing an ipsilesional upper extremity task during the first 3 months after stroke. Methods. Movement kinematics describing movement time, smoothness, velocity, strategy, and pattern were captured during a standardized drinking task in 40 persons with first-ever stroke and 20 controls. Kinematics were measured early and at 3 months poststroke, and sensorimotor impairment was assessed with Fugl-Meyer Assessment in stroke. Results. Half of the ipsilesional kinematics showed significant deficits early after stroke compared to controls, and the stroke severity had a significant impact on the kinematics. Movements of the ipsilesional arm were slower, less smooth, demonstrated prolonged relative time in deceleration, and increased arm abduction during drinking. Kinematics improved over time and reached a level comparable with controls at 3 months, except for angular velocity of the elbow and deceleration time in reaching for those with more severe motor impairment. Conclusions. This study demonstrates that movements of the ipsilesional arm, during a purposeful daily task, are impaired after stroke. These deficits are more prominent early after stroke and when the motor impairment is more severe. In clinical studies and praxis, the use of less-affected arm as a reference may underestimate the level of impairment and extent of recovery.

scholarly journals Development of Smart Wheelchair System for a User with Severe Motor Impairment

2012 ◽  
Vol 41 ◽  
pp. 538-546 ◽  
Author(s):  
Mohd Razali Md Tomari ◽  
Yoshinori Kobayashi ◽  
Yoshinori Kuno
Keyword(s):  
Motor Impairment ◽  
Severe Motor ◽  
Severe Motor Impairment ◽  
Smart Wheelchair

scholarly journals In-Bed Sensorimotor Rehabilitation in Early and Late Subacute Stroke Using a Wearable Elbow Robot: A Pilot Study

2021 ◽  
Vol 15 ◽  
Author(s):  
Mei Zhen Huang ◽  
Yong-Soon Yoon ◽  
Jisu Yang ◽  
Chung-Yong Yang ◽  
Li-Qun Zhang
Keyword(s):  
Pilot Study ◽  
Muscle Strength ◽  
Upper Limb ◽  
Training Session ◽  
Motor Impairment ◽  
Elbow Flexors ◽  
Recovery Curve ◽  
Strength Recovery ◽  
Subacute Stroke

Objects: To evaluate the feasibility and effectiveness of in-bed wearable elbow robot training for motor recovery in patients with early and late subacute stroke.Methods: Eleven in-patient stroke survivors (male/female: 7/4, age: 50.7 ± 10.6 years, post-stroke duration: 2.6 ± 1.9 months) received 15 sessions of training over about 4 weeks of hospital stay. During each hourly training, participants received passive stretching and active movement training with motivating games using a wearable elbow rehabilitation robot. Isometric maximum muscle strength (MVC) of elbow flexors and extensors was evaluated using the robot at the beginning and end of each training session. Clinical measures including Fugl-Meyer Assessment of upper extremity (FMA-UE), Motricity Index (MI) for upper extremities, Modified Ashworth Scale (MAS) were measured at baseline, after the 4-week training program, and at a 1-month follow-up. The muscle strength recovery curve over the training period was characterized as a logarithmic learning curve with three parameters (i.e., initial muscle strength, rate of improvement, and number of the training session).Results: At the baseline, participants had moderate to severe upper limb motor impairment {FMA-UE [median (interquartile range)]: 28 (18–45)} and mild spasticity in elbow flexors {MAS [median (interquartile range)]: 0 (0–1)}. After about 4 weeks of training, significant improvements were observed in FMA-UE (p = 0.003) and MI (p = 0.005), and the improvements were sustained at the follow-up. The elbow flexors MVC significantly increased by 1.93 Nm (95% CI: 0.93 to 2.93 Nm, p = 0.017) and the elbow extensor MVC increased by 0.68 Nm (95% CI: 0.05 to 1.98 Nm, p = 0.036). Muscle strength recovery curve showed that patients with severe upper limb motor impairment had a greater improvement rate in elbow flexor strength than those with moderate motor impairment.Conclusion: In-bed wearable elbow robotic rehabilitation is feasible and effective in improving biomechanical and clinical outcomes for early and late subacute stroke in-patients. Results from the pilot study suggested that patients with severe upper limb motor impairment may benefit more from the robot training compared to those with moderate impairment.

scholarly journals Motoric impairment versus iron deposition gradient in the subthalamic nucleus in Parkinson’s disease

2020 ◽  
pp. 1-7
Author(s):  
Weiyuan Huang ◽  
Richard Ogbuji ◽  
Liangdong Zhou ◽  
Lingfei Guo ◽  
Yi Wang ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Subthalamic Nucleus ◽  
Rating Scale ◽  
Statistical Tests ◽  
Motor Impairment ◽  
Iron Deposition ◽  
Severe Motor ◽  
Severe Motor Impairment ◽  
The Right

OBJECTIVEThe objective of this study was to investigate the correlation between the quantitative susceptibility mapping (QSM) signal gradient of the subthalamic nucleus (STN) and motor impairment in patients with Parkinson’s disease (PD).METHODSAll PD patients who had undergone QSM MRI for presurgical deep brain stimulation (DBS) planning were eligible for inclusion in this study. The entire STN and its three functional subdivisions, as well as the adjacent white matter (WM), were segmented and measured. The QSM value difference between the entire STN and adjacent WM (STN-WM), between the limbic and associative regions of the STN (L-A), and between the associative and motor regions of the STN (A-M) were obtained as measures of gradient and were input into an unsupervised k-means clustering algorithm to automatically categorize the overall boundary distinctness between the STN and adjacent WM and between STN subdivisions (gradient blur [GB] and gradient sharp [GS] groups). Statistical tests were performed to compare clinical and image measurements for discrimination between GB and GS groups.RESULTSOf the 39 study patients, 19 were categorized into the GB group and 20 into the GS group, based on quantitative cluster analysis. The GB group had a significantly higher presurgical off-medication Unified Parkinson’s Disease Rating Scale Part III score (51.289 ± 20.741) than the GS group (38.5 ± 16.028; p = 0.037). The GB group had significantly higher QSM values for the STN and its three subdivisions and adjacent WM than those for the GS group (p < 0.01). The GB group also demonstrated a significantly higher STN-WM gradient in the right STN (p = 0.01). The GB group demonstrated a significantly lower L-A gradient in both the left and the right STN (p < 0.02).CONCLUSIONSAdvancing PD with more severe motor impairment leads to more iron deposition in the STN and adjacent WM, as shown in the QSM signal. Loss of the STN inner QSM signal gradient should be considered as an image marker for more severe motor impairment in PD patients.

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