scholarly journals Cognitive and motor deficits contribute to longer braking time in stroke

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Neha Lodha ◽  
Prakruti Patel ◽  
Joanna M. Shad ◽  
Agostina Casamento-Moran ◽  
Evangelos A. Christou
Keyword(s):  
Selective Attention ◽  
Driving Simulator ◽  
Maximum Voluntary Contraction ◽  
Driving Behavior ◽  
Motor Deficits ◽  
Control Group ◽  
Stroke Survivors ◽  
Safe Driving ◽  
Stroke Group ◽  
Motor Accuracy

Abstract Background Braking is a critical determinant of safe driving that depends on the integrity of cognitive and motor processes. Following stroke, both cognitive and motor capabilities are impaired to varying degrees. The current study examines the combined impact of cognitive and motor impairments on braking time in chronic stroke. Methods Twenty stroke survivors and 20 aged-matched healthy controls performed cognitive, motor, and simulator driving assessments. Cognitive abilities were assessed with processing speed, divided attention, and selective attention. Motor abilities were assessed with maximum voluntary contraction (MVC) and motor accuracy of the paretic ankle. Driving performance was examined with the braking time in a driving simulator and self-reported driving behavior. Results Braking time was 16% longer in the stroke group compared with the control group. The self-reported driving behavior in stroke group was correlated with braking time (r = − 0.53, p = 0.02). The stroke group required significantly longer time for divided and selective attention tasks and showed significant decrease in motor accuracy. Together, selective attention time and motor accuracy contributed to braking time (R2 = 0.40, p = 0.01) in stroke survivors. Conclusions This study provides novel evidence that decline in selective attention and motor accuracy together contribute to slowed braking in stroke survivors. Driving rehabilitation after stroke may benefit from the assessment and training of attentional and motor skills to improve braking during driving.

scholarly journals Cognitive and Motor Deficits Contribute to Longer Braking Time in Stroke

2020 ◽  
Author(s):  
Neha Lodha ◽  
Prakruti Patel ◽  
Joanna M Shad ◽  
Agostina Casamento-Moran ◽  
Evangelos A Christou
Keyword(s):  
Selective Attention ◽  
Driving Simulator ◽  
Maximum Voluntary Contraction ◽  
Driving Behavior ◽  
Motor Deficits ◽  
Control Group ◽  
Stroke Survivors ◽  
Safe Driving ◽  
Stroke Group ◽  
Motor Accuracy

Abstract Braking is a critical determinant of safe driving that depends on the integrity of cognitive and motor processes. Following stroke, both cognitive and motor capabilities are impaired to varying degrees. The current study examines the combined impact of cognitive and motor impairments on braking time in chronic stroke. METHODS: Twenty stroke survivors and 20 aged-matched healthy controls performed cognitive, motor, and simulator driving assessments. Cognitive abilities were assessed with processing speed, divided attention, and selective attention. Motor abilities were assessed with maximum voluntary contraction (MVC) and motor accuracy of the paretic ankle. Driving performance was examined with the braking time in a driving simulator and self-reported driving behavior. RESULTS: Braking time was 16% longer in stroke group compared with the control group. The self-reported driving behavior in stroke group was correlated with braking time (r = -0.53, p = 0.02). The stroke group required significantly longer time for divided and selective attention task and showed significant decrease in motor accuracy. Together, selective attention time and motor accuracy contributed to braking time (R2 = 0.40, p = 0.01) in stroke survivors. CONCLUSIONS: This study provides novel evidence that decline in selective attention and motor accuracy together contribute to slowed braking in stroke survivors. Driving rehabilitation after stroke may benefit from the assessment and training of attentional and motor skills to improve braking during driving.

scholarly journals Cognitive and Motor Deficits Contribute to Longer Braking Time in Stroke 

2020 ◽  
Author(s):  
Neha Lodha ◽  
Prakruti Patel ◽  
Joanna M Shad ◽  
Agostina Casamento-Moran ◽  
Evangelos A Christou
Keyword(s):  
Selective Attention ◽  
Driving Simulator ◽  
Maximum Voluntary Contraction ◽  
Driving Behavior ◽  
Motor Deficits ◽  
Control Group ◽  
Stroke Survivors ◽  
Safe Driving ◽  
Stroke Group ◽  
Motor Accuracy

Abstract BACKGROUND: Braking is a critical determinant of safe driving that depends on the integrity of cognitive and motor processes. Following stroke, both cognitive and motor capabilities are impaired to varying degrees. The current study examines the combined impact of cognitive and motor impairments on braking time in chronic stroke. METHODS: Twenty stroke survivors and 20 aged-matched healthy controls performed cognitive, motor, and simulator driving assessments. Cognitive abilities were assessed with processing speed, divided attention, and selective attention. Motor abilities were assessed with maximum voluntary contraction (MVC) and motor accuracy of the paretic ankle. Driving performance was examined with the braking time in a driving simulator and self-reported driving behavior. RESULTS: Braking time was 16% longer in stroke group compared with the control group. The self-reported driving behavior in stroke group was correlated with braking time (r = -0.53, p = 0.02). The stroke group required significantly longer time for divided and selective attention task and showed significant decrease in motor accuracy. Together, selective attention time and motor accuracy contributed to braking time (R2 = 0.40, p = 0.01) in stroke survivors. CONCLUSIONS: This study provides novel evidence that decline in selective attention and motor accuracy together contribute to slowed braking in stroke survivors. Driving rehabilitation after stroke may benefit from the assessment and training of attentional and motor skills to improve braking during driving.

scholarly journals A Driving Simulation to Analysis and Quantitative Comparison of Driving Behavior of Guide Signs at Intersections

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Tianzheng Wei ◽  
Tong Zhu ◽  
Chenxin Li ◽  
Haoxue Liu
Keyword(s):  
Quantitative Evaluation ◽  
Evaluation Method ◽  
Driving Simulator ◽  
Current System ◽  
Driving Behavior ◽  
Driving Simulation ◽  
Analysis Method ◽  
Safe Driving ◽  
Amount Of Information ◽  
Significant Difference

Guide signs are an important source for drivers to obtain road information. However, the evaluation methods for the effectiveness of guide signs are not unified. The quantitative model for evaluating guide signs needs to be constructed to unify the current system of guide signs. This study aims to take the commonly used guide signs in China as the research object to explore the evaluation method of guide signs at intersections. Eight kinds of guide signs were designed and made based on the common layout (layout 1 and layout 2) and the amount of information on signs (3–6). Thirty-four drivers were recruited to organize a driving simulation based on the visual cognitive tasks. Drivers’ legibility time and driver behavior were obtained by using the driving simulator and E-Prime program. A comprehensive quantitative evaluation model of guide signs was established based on the factor analysis method and grey correlation analysis method from the perspective of safe driving. The results show that there is no significant difference in the SD of speed and the SD of acceleration under the influence of various guide signs. The average vehicle speed and acceleration decrease, and the lateral offset distance of the vehicle increases with the amount of information on guide signs increasing. The quantitative evaluation results of guide signs show that the visual security decreases with the increase of the amount of information on guide signs. And layout 2 has better performance than layout 1 when the amount of information on guide signs is the same. This study not only explores the change rule of driving behavior under the influence of guide signs, but also provides a reference for the selection of guide signs.

scholarly journals Effects of a robot‐aided somatosensory training on proprioception and motor function in stroke survivors

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
I-Ling Yeh ◽  
Jessica Holst-Wolf ◽  
Naveen Elangovan ◽  
Anna Vera Cuppone ◽  
Kamakshi Lakshminarayan ◽  
...  
Keyword(s):  
Chronic Stroke ◽  
Tactile Feedback ◽  
Just Noticeable Difference ◽  
Current Evidence ◽  
Control Group ◽  
Stroke Survivors ◽  
Spatial Error ◽  
Stroke Group ◽  
Age Range ◽  
Proprioceptive Function

Abstract Background Proprioceptive deficits after stroke are associated with poor upper limb function, slower motor recovery, and decreased self-care ability. Improving proprioception should enhance motor control in stroke survivors, but current evidence is inconclusive. Thus, this study examined whether a robot-aided somatosensory-based training requiring increasingly accurate active wrist movements improves proprioceptive acuity as well as motor performance in chronic stroke. Methods Twelve adults with chronic stroke completed a 2-day training (age range: 42–74 years; median time-after-stroke: 12 months; median Fugl–Meyer UE: 65). Retention was assessed at Day 5. Grasping the handle of a wrist-robotic exoskeleton, participants trained to roll a virtual ball to a target through continuous wrist adduction/abduction movements. During training vision was occluded, but participants received real-time, vibro-tactile feedback on their forearm about ball position and speed. Primary outcome was the just-noticeable-difference (JND) wrist position sense threshold as a measure of proprioceptive acuity. Secondary outcomes were spatial error in an untrained wrist tracing task and somatosensory-evoked potentials (SEP) as a neural correlate of proprioceptive function. Ten neurologically-intact adults were recruited to serve as non-stroke controls for matched age, gender and hand dominance (age range: 44 to 79 years; 6 women, 4 men). Results Participants significantly reduced JND thresholds at posttest and retention (Stroke group: pretest: mean: 1.77° [SD: 0.54°] to posttest mean: 1.38° [0.34°]; Control group: 1.50° [0.46°] to posttest mean: 1.45° [SD: 0.54°]; F[2,37] = 4.54, p = 0.017, ηp2 = 0.20) in both groups. A higher pretest JND threshold was associated with a higher threshold reduction at posttest and retention (r = − 0.86, − 0.90, p ≤ 0.001) among the stroke participants. Error in the untrained tracing task was reduced by 22 % at posttest, yielding an effect size of w = 0.13. Stroke participants exhibited significantly reduced P27-N30 peak-to-peak SEP amplitude at pretest (U = 11, p = 0.03) compared to the non-stroke group. SEP measures did not change systematically with training. Conclusions This study provides proof-of-concept that non-visual, proprioceptive training can induce fast, measurable improvements in proprioceptive function in chronic stroke survivors. There is encouraging but inconclusive evidence that such somatosensory learning transfers to untrained motor tasks. Trial registration Clinicaltrials.gov; Registration ID: NCT02565407; Date of registration: 01/10/2015; URL: https://clinicaltrials.gov/ct2/show/NCT02565407.

The Validity of Three New Driving Simulator Scenarios: Detecting Differences in Driving Performance by Difficulty and Driver Gender and Age

2020 ◽  
pp. 001872082093752
Author(s):  
Hillary Maxwell ◽  
Bruce Weaver ◽  
Sylvain Gagnon ◽  
Shawn Marshall ◽  
Michel Bédard
Keyword(s):  
Discriminant Validity ◽  
Driving Simulator ◽  
Age Groups ◽  
Driving Behavior ◽  
Driving Simulation ◽  
Driving Simulators ◽  
Safe Driving ◽  
Convergent And Discriminant Validity ◽  
Gender And Age ◽  
Driver Assessment

Objective We explored the convergent and discriminant validity of three driving simulation scenarios by comparing behaviors across gender and age groups, considering what we know about on-road driving. Background Driving simulators offer a number of benefits, yet their use in real-world driver assessment is rare. More evidence is needed to support their use. Method A total of 104 participants completed a series of increasingly difficult driving simulation scenarios. Linear mixed models were estimated to determine if behaviors changed with increasing difficulty and whether outcomes varied by age and gender, thereby demonstrating convergent and discriminant validity, respectively. Results Drivers adapted velocity, steering, acceleration, and gap acceptance according to difficulty, and the degree of adaptation differed by gender and age for some outcomes. For example, in a construction zone scenario, drivers reduced their mean velocities as congestion increased; males drove an average of 2.30 km/hr faster than females, and older participants drove more slowly than young (5.26 km/hr) and middle-aged drivers (6.59 km/hr). There was also an interaction between age and difficulty; older drivers did not reduce their velocities with increased difficulty. Conclusion This study provides further support for the ability of driving simulators to elicit behaviors similar to those seen in on-road driving and to differentiate between groups, suggesting that simulators could serve a supportive role in fitness-to-drive evaluations. Application Simulators have the potential to support driver assessment. However, this depends on the development of valid scenarios to benchmark safe driving behavior, and thereby identify deviations from safe driving behavior. The information gained through simulation may supplement other forms of assessment and possibly eliminate the need for on-road testing in some situations.

Impaired Regulation of Submaximal Force after ACL Reconstruction: Role of Muscle Spindles

2020 ◽  
Author(s):  
David Rice ◽  
Gwyn Lewis ◽  
Peter McNair
Keyword(s):  
Acl Reconstruction ◽  
Muscle Spindle ◽  
Muscle Force ◽  
Cruciate Ligament ◽  
Maximum Voluntary Contraction ◽  
Muscle Spindles ◽  
Voluntary Contraction ◽  
Motor Deficits ◽  
Control Group ◽  
Force Matching

AbstractOngoing motor deficits are routinely present following anterior cruciate ligament (ACL) reconstruction, including the ability to regulate muscle force. While such deficits are known, it is unclear why this occurs. The goal of the current study was to investigate the potential influence of muscle spindle input on submaximal force regulation and muscle activity at the knee in people following ACL reconstruction. Fourteen participants (8 female) who were 6−24 months post-ACL reconstruction and 15 control participants (8 female) undertook submaximal force matching and force modulation tasks before and after 20 min of vibration applied to the patella tendon. Across all tasks, the ACL reconstruction participants were poorer at force matching (P=0.007). The effect of vibration was not significant in either group for the force matching tasks (P=0.06), although there was a reduction in maximum voluntary contraction post-vibration in the control group (P<0.001). The ACL reconstruction group also showed evidence of greater activation of the medial hamstring muscles in comparison to controls (P=0.04). Individuals who have undergone ACL reconstruction have a diminished ability to accurately match and regulate submaximal muscle force, but this does not appear to be related to impaired muscle spindle input. Neuromuscular retraining programs that involve force regulation tasks may be necessary to optimize rehabilitation after ACL reconstruction.

Cloning Safe Driving Behavior for Self-Driving Cars using Convolutional Neural Networks

2019 ◽  
Vol 12 (2) ◽  
pp. 120-127 ◽  
Author(s):  
Wael Farag
Keyword(s):  
Gradient Descent ◽  
Autonomous Driving ◽  
Driving Behavior ◽  
Training Data ◽  
Stochastic Gradient Descent ◽  
Data Set ◽  
Safe Driving ◽  
Processing Pipeline ◽  
Self Driving Cars ◽  
And Training

Background: In this paper, a Convolutional Neural Network (CNN) to learn safe driving behavior and smooth steering manoeuvring, is proposed as an empowerment of autonomous driving technologies. The training data is collected from a front-facing camera and the steering commands issued by an experienced driver driving in traffic as well as urban roads. Methods: This data is then used to train the proposed CNN to facilitate what it is called “Behavioral Cloning”. The proposed Behavior Cloning CNN is named as “BCNet”, and its deep seventeen-layer architecture has been selected after extensive trials. The BCNet got trained using Adam’s optimization algorithm as a variant of the Stochastic Gradient Descent (SGD) technique. Results: The paper goes through the development and training process in details and shows the image processing pipeline harnessed in the development. Conclusion: The proposed approach proved successful in cloning the driving behavior embedded in the training data set after extensive simulations.

scholarly journals The surface electromyography analysis of the non-plegic upper limb of hemiplegic subjects

2010 ◽  
Vol 68 (4) ◽  
pp. 562-566 ◽  
Author(s):  
Heloyse U Kuriki ◽  
Raquel N. de Azevedo ◽  
Augusto C. de Carvalho ◽  
Fábio Mícolis de Azevedo ◽  
Rúben F Negrão-Filho ◽  
...  
Keyword(s):  
Control Group ◽  
Electromyographic Activity ◽  
Healthy Individuals ◽  
Wrist Flexion ◽  
Functional Changes ◽  
Normal Individuals ◽  
Flexor Muscles ◽  
Stroke Group ◽  
Dominant Member ◽  
Flexion And Extension

Many authors have studied physical and functional changes in individuals post-stroke, but there are few studies that assess changes in the non-plegic side of hemiplegic subjects. This study aimed to compare the electromyographic activity in the forearm muscles of spastic patients and clinically healthy individuals, to determine if there is difference between the non-plegic side of hemiplegics and the dominant member of normal individuals. 22 hemiplegic subjects and 15 clinically healthy subjects were submitted to electromyography of the flexor and extensor carpi ulnaris muscles during wrist flexion and extension. The flexor muscles activation of stroke group (average 464.6 u.n) was significantly higher than the same muscles in control group (mean: 106.3 u.n.) during the wrist flexion, what shows that the non affected side does not present activation in the standart of normality found in the control group.

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