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

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.

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Effects of a Robot-aided Somatosensory Training on Proprioception and Motor Function in Stroke Survivors

10.21203/rs.3.rs-89369/v1 ◽

2020 ◽

Author(s):

I-Ling Yeh ◽

Jessica Holst-Wolf ◽

Naveen Elangovan ◽

Anna Vera Cuppone ◽

Kamakshi Lakshminarayan ◽

...

Keyword(s):

Position Sense ◽

Chronic Stroke ◽

Tactile Feedback ◽

Just Noticeable Difference ◽

Current Evidence ◽

Stroke Survivors ◽

Spatial Error ◽

Upper Limb Function ◽

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 and 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 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 (F(2, 38) = 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.Conclusion - 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

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Development and Clinical Evaluation of a Web-Based Upper Limb Home Rehabilitation System Using a Smartwatch and Machine Learning Model for Chronic Stroke Survivors: Prospective Comparative Study (Preprint)

10.2196/preprints.17216 ◽

2019 ◽

Author(s):

Sang Hoon Chae ◽

Yushin Kim ◽

Kyoung-Soub Lee ◽

Hyung-Soon Park

Keyword(s):

Machine Learning ◽

Home Care ◽

Comparative Study ◽

Internal Rotation ◽

Chronic Stroke ◽

Control Group ◽

Stroke Survivors ◽

Home Based ◽

Rehabilitation System ◽

Prospective Comparative Study

BACKGROUND Recent advancements in wearable sensor technology have shown the feasibility of remote physical therapy at home. In particular, the current COVID-19 pandemic has revealed the need and opportunity of internet-based wearable technology in future health care systems. Previous research has shown the feasibility of human activity recognition technologies for monitoring rehabilitation activities in home environments; however, few comprehensive studies ranging from development to clinical evaluation exist. OBJECTIVE This study aimed to (1) develop a home-based rehabilitation (HBR) system that can recognize and record the type and frequency of rehabilitation exercises conducted by the user using a smartwatch and smartphone app equipped with a machine learning (ML) algorithm and (2) evaluate the efficacy of the home-based rehabilitation system through a prospective comparative study with chronic stroke survivors. METHODS The HBR system involves an off-the-shelf smartwatch, a smartphone, and custom-developed apps. A convolutional neural network was used to train the ML algorithm for detecting home exercises. To determine the most accurate way for detecting the type of home exercise, we compared accuracy results with the data sets of personal or total data and accelerometer, gyroscope, or accelerometer combined with gyroscope data. From March 2018 to February 2019, we conducted a clinical study with two groups of stroke survivors. In total, 17 and 6 participants were enrolled for statistical analysis in the HBR group and control group, respectively. To measure clinical outcomes, we performed the Wolf Motor Function Test (WMFT), Fugl-Meyer Assessment of Upper Extremity, grip power test, Beck Depression Inventory, and range of motion (ROM) assessment of the shoulder joint at 0, 6, and 12 months, and at a follow-up assessment 6 weeks after retrieving the HBR system. RESULTS The ML model created with personal data involving accelerometer combined with gyroscope data (5590/5601, 99.80%) was the most accurate compared with accelerometer (5496/5601, 98.13%) or gyroscope data (5381/5601, 96.07%). In the comparative study, the drop-out rates in the control and HBR groups were 40% (4/10) and 22% (5/22) at 12 weeks and 100% (10/10) and 45% (10/22) at 18 weeks, respectively. The HBR group (n=17) showed a significant improvement in the mean WMFT score (P=.02) and ROM of flexion (P=.004) and internal rotation (P=.001). The control group (n=6) showed a significant change only in shoulder internal rotation (P=.03). CONCLUSIONS This study found that a home care system using a commercial smartwatch and ML model can facilitate participation in home training and improve the functional score of the WMFT and shoulder ROM of flexion and internal rotation in the treatment of patients with chronic stroke. This strategy can possibly be a cost-effective tool for the home care treatment of stroke survivors in the future. CLINICALTRIAL Clinical Research Information Service KCT0004818; https://tinyurl.com/y92w978t

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The effects of anxiety and dual-task on upper limb motor control of chronic stroke survivors

Scientific Reports ◽

10.1038/s41598-020-71845-7 ◽

2020 ◽

Vol 10 (1) ◽

Author(s):

Mahnaz Hejazi-Shirmard ◽

Laleh Lajevardi ◽

Mehdi Rassafiani ◽

Ghorban Taghizadeh

Keyword(s):

Motor Control ◽

Upper Limb ◽

Dual Task ◽

Chronic Stroke ◽

Stroke Survivors ◽

High Anxiety ◽

Reach And Grasp ◽

Stroke Group ◽

Task Conditions ◽

Hand Opening

Abstract This study was designed to investigate the effects of anxiety and dual-task on reach and grasp motor control in chronic stroke survivors compared with age- and sex-matched healthy subjects (HC). Reach and grasp kinematic data of 68 participants (high-anxiety stroke (HA-stroke), n = 17; low-anxiety stroke (LA-stroke), n = 17; low-anxiety HC, n = 17; and high-anxiety HC, n = 17) were recorded under single- and dual-task conditions. Inefficient reach and grasp of stroke participants, especially HA-stroke were found compared with the control groups under single- and dual-task conditions as evidenced by longer movement time (MT), lower and earlier peak velocity (PV) as well as delayed and smaller hand opening. The effects of dual-task on reach and grasp kinematic measures were similar between HCs and stroke participants (i.e., increased MT, decreased PV that occurred earlier, and delayed and decreased hand opening), with greater effect in stroke groups than HCs, and in HA-stroke group than LA-stroke group. The results indicate that performing a well-learned upper limb movement with concurrent cognitive task leads to decreased efficiency of motor control in chronic stroke survivors compared with HCs. HA-stroke participants were more adversely affected by challenging dual-task conditions, underlying importance of assessing anxiety and designing effective interventions for it in chronic stroke survivors.

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Development and Clinical Evaluation of a Web-Based Upper Limb Home Rehabilitation System Using a Smartwatch and Machine Learning Model for Chronic Stroke Survivors: Prospective Comparative Study

JMIR mhealth and uhealth ◽

10.2196/17216 ◽

2020 ◽

Vol 8 (7) ◽

pp. e17216

Author(s):

Sang Hoon Chae ◽

Yushin Kim ◽

Kyoung-Soub Lee ◽

Hyung-Soon Park

Keyword(s):

Machine Learning ◽

Home Care ◽

Comparative Study ◽

Internal Rotation ◽

Chronic Stroke ◽

Control Group ◽

Stroke Survivors ◽

Home Based ◽

Rehabilitation System ◽

Prospective Comparative Study

Background Recent advancements in wearable sensor technology have shown the feasibility of remote physical therapy at home. In particular, the current COVID-19 pandemic has revealed the need and opportunity of internet-based wearable technology in future health care systems. Previous research has shown the feasibility of human activity recognition technologies for monitoring rehabilitation activities in home environments; however, few comprehensive studies ranging from development to clinical evaluation exist. Objective This study aimed to (1) develop a home-based rehabilitation (HBR) system that can recognize and record the type and frequency of rehabilitation exercises conducted by the user using a smartwatch and smartphone app equipped with a machine learning (ML) algorithm and (2) evaluate the efficacy of the home-based rehabilitation system through a prospective comparative study with chronic stroke survivors. Methods The HBR system involves an off-the-shelf smartwatch, a smartphone, and custom-developed apps. A convolutional neural network was used to train the ML algorithm for detecting home exercises. To determine the most accurate way for detecting the type of home exercise, we compared accuracy results with the data sets of personal or total data and accelerometer, gyroscope, or accelerometer combined with gyroscope data. From March 2018 to February 2019, we conducted a clinical study with two groups of stroke survivors. In total, 17 and 6 participants were enrolled for statistical analysis in the HBR group and control group, respectively. To measure clinical outcomes, we performed the Wolf Motor Function Test (WMFT), Fugl-Meyer Assessment of Upper Extremity, grip power test, Beck Depression Inventory, and range of motion (ROM) assessment of the shoulder joint at 0, 6, and 12 months, and at a follow-up assessment 6 weeks after retrieving the HBR system. Results The ML model created with personal data involving accelerometer combined with gyroscope data (5590/5601, 99.80%) was the most accurate compared with accelerometer (5496/5601, 98.13%) or gyroscope data (5381/5601, 96.07%). In the comparative study, the drop-out rates in the control and HBR groups were 40% (4/10) and 22% (5/22) at 12 weeks and 100% (10/10) and 45% (10/22) at 18 weeks, respectively. The HBR group (n=17) showed a significant improvement in the mean WMFT score (P=.02) and ROM of flexion (P=.004) and internal rotation (P=.001). The control group (n=6) showed a significant change only in shoulder internal rotation (P=.03). Conclusions This study found that a home care system using a commercial smartwatch and ML model can facilitate participation in home training and improve the functional score of the WMFT and shoulder ROM of flexion and internal rotation in the treatment of patients with chronic stroke. This strategy can possibly be a cost-effective tool for the home care treatment of stroke survivors in the future. Trial Registration Clinical Research Information Service KCT0004818; https://tinyurl.com/y92w978t

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Cognitive and motor deficits contribute to longer braking time in stroke

Journal of NeuroEngineering and Rehabilitation ◽

10.1186/s12984-020-00802-2 ◽

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.

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Feasibility and effect of interactive telerehabilitation on balance in individuals with chronic stroke: a pilot study

Journal of NeuroEngineering and Rehabilitation ◽

10.1186/s12984-021-00866-8 ◽

2021 ◽

Vol 18 (1) ◽

Author(s):

Shih-Ching Chen ◽

Chueh-Ho Lin ◽

Sheng-Wen Su ◽

Yu-Tai Chang ◽

Chien-Hung Lai

Keyword(s):

Pilot Study ◽

Effect Size ◽

Exercise Intervention ◽

Chronic Stroke ◽

Control Group ◽

Stroke Survivors ◽

Post Intervention ◽

Timed Up And Go ◽

Kinect Camera ◽

Experimental Group

Abstract Background Stroke survivors need continuing exercise intervention to maintain functional status. This study assessed the feasibility and efficacy of an interactive telerehabilitation exergaming system to improve balance in individuals with chronic stroke, compared to conventional one-on-one rehabilitation. Methods In this prospective case–control pilot study, 30 Taiwanese individuals with chronic stroke were enrolled and randomly allocated to an experimental group and a control group. All participants received intervention 3 times per week for 4 weeks in the study hospital. The experiment group underwent telerehabilitation using a Kinect camera-based interactive telerehabilitation system in an independent room to simulate home environment. In contrast, the control group received conventional one-on-one physiotherapy in a dedicated rehabilitation area. The effectiveness of interactive telerehabilitation in improving balance in stroke survivors was evaluated by comparing outcomes between the two groups. The primary outcome was Berg Balance Scale (BBS) scores. Secondary outcomes were performance of the Timed Up and Go (TUG) test, Modified Falls Efficacy Scale, Motricity Index, and Functional Ambulation Category. Results Comparison of outcomes between experimental and control groups revealed no significant differences between groups at baseline and post-intervention for all outcome measures. However, BBS scores improved significantly in both groups (control group: p = 0.01, effect size = 0.49; experimental group: p = 0.01, effect size = 0.70). Completion times of TUG tests also improved significantly in the experimental group (p = 0.005, effect size = 0.70). Conclusion The Kinect camera-based interactive telerehabilitation system demonstrates superior or equal efficacy compared to conventional one-on-one physiotherapy for improving balance in individuals with chronic stroke. Trial registration ClinicalTrials.gov. NCT03698357. Registered October 4, 2018, retrospectively registered.

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Robotic-based ACTive somatoSENSory (Act.Sens) retraining on upper limb functions with chronic stroke survivors: study protocol for a pilot randomised controlled trial

Pilot and Feasibility Studies ◽

10.1186/s40814-021-00948-3 ◽

2021 ◽

Vol 7 (1) ◽

Author(s):

Ananda Sidarta ◽

Yu Chin Lim ◽

Christopher Wee Keong Kuah ◽

Yong Joo Loh ◽

Wei Tech Ang

Keyword(s):

Randomised Controlled Trial ◽

Study Protocol ◽

Upper Limb ◽

Controlled Trial ◽

Chronic Stroke ◽

Community Dwelling ◽

Control Group ◽

Stroke Survivors ◽

Pilot Randomised Controlled Trial ◽

Randomised Controlled

Abstract Background Prior studies have established that senses of the limb position in space (proprioception and kinaesthesia) are important for motor control and learning. Although nearly one-half of stroke patients have impairment in the ability to sense their movements, somatosensory retraining focusing on proprioception and kinaesthesia is often overlooked. Interventions that simultaneously target motor and somatosensory components are thought to be useful for relearning somatosensory functions while increasing mobility of the affected limb. For over a decade, robotic technology has been incorporated in stroke rehabilitation for more controlled therapy intensity, duration, and frequency. This pilot randomised controlled trial introduces a compact robotic-based upper-limb reaching task that retrains proprioception and kinaesthesia concurrently. Methods Thirty first-ever chronic stroke survivors (> 6-month post-stroke) will be randomly assigned to either a treatment or a control group. Over a 5-week period, the treatment group will receive 15 training sessions for about an hour per session. Robot-generated haptic guidance will be provided along the movement path as somatosensory cues while moving. Audio-visual feedback will appear following every successful movement as a reward. For the same duration, the control group will complete similar robotic training but without the vision occluded and robot-generated cues. Baseline, post-day 1, and post-day 30 assessments will be performed, where the last two sessions will be conducted after the last training session. Robotic-based performance indices and clinical assessments of upper limb functions after stroke will be used to acquire primary and secondary outcome measures respectively. This work will provide insights into the feasibility of such robot-assisted training clinically. Discussion The current work presents a study protocol to retrain upper-limb somatosensory and motor functions using robot-based rehabilitation for community-dwelling stroke survivors. The training promotes active use of the affected arm while at the same time enhances somatosensory input through augmented feedback. The outcomes of this study will provide preliminary data and help inform the clinicians on the feasibility and practicality of the proposed exercise. Trial registration ClinicalTrials.gov NCT04490655. Registered 29 July 2020.

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Mindfulness Meditation Effects on Poststroke Spasticity: A Feasibility Study

Journal of Evidence-Based Integrative Medicine ◽

10.1177/2515690x19855941 ◽

2019 ◽

Vol 24 ◽

pp. 2515690X1985594 ◽

Cited By ~ 1

Author(s):

Melanie Wathugala ◽

David Saldana ◽

Julia M. Juliano ◽

Jennifer Chan ◽

Sook-Lei Liew

Keyword(s):

Quality Of Life ◽

Feasibility Study ◽

Repeated Measures ◽

Mindfulness Meditation ◽

Chronic Stroke ◽

Future Research ◽

Control Group ◽

Stroke Survivors ◽

Repeated Measures Design

This study examined the feasibility of an adapted 2-week mindfulness meditation protocol for chronic stroke survivors. In addition, preliminary effects of this adapted intervention on spasticity and quality of life in individuals after stroke were explored. Ten chronic stroke survivors with spasticity listened to 2 weeks of short mindfulness meditation recordings, adapted from Jon Kabat-Zinn’s Mindfulness-Based Stress Reduction course, in a pre/post repeated measures design. Measures of spasticity, quality of life, mindfulness, and anxiety, along with qualitative data from participants’ daily journals, were assessed. On average, participants reported meditating 12.5 days of the full 15 days (mean 12.5 days, SD 0.94, range 8-15 days). Seven of the 10 participants wrote comments in their journals. In addition, there were no adverse effects due to the intervention. Exploratory preliminary analyses also showed statistically significant improvements in spasticity in both the elbow ( P = .032) and wrist ( P = .023) after 2 weeks of meditation, along with improvements in quality of life measures for Energy ( P = .013), Personality ( P = .026), and Work/Productivity ( P = .032). This feasibility study suggests that individuals with spasticity following stroke are able to adhere to a 2-week home-based mindfulness meditation program. In addition, preliminary results also suggest that this adapted, short mindfulness meditation program might be a promising approach for individuals with spasticity following stroke. Future research should expand on these preliminary findings with a larger sample size and control group.

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Abstract T P115: Sarcopenia and Physical Function in Chronic Stroke

Stroke ◽

10.1161/str.46.suppl_1.tp115 ◽

2015 ◽

Vol 46 (suppl_1) ◽

Author(s):

Alice S Ryan ◽

Joseph Hartstein ◽

Charlene Hafer-Macko ◽

Frederick Ivey

Keyword(s):

Skeletal Muscle ◽

Muscle Mass ◽

Large Population ◽

Chronic Stroke ◽

Whole Body ◽

Matched Pair ◽

Control Group ◽

Stroke Survivors ◽

Skeletal Muscle Index ◽

European Working

Sarcopenia is defined as an age-related loss in skeletal lean muscle mass and strength and is as a leading contributor to the development of frailty. Stroke survivors have muscle atrophy in paretic (P) vs. nonparetic (P) legs that could contribute to whole body sarcopenia. The purpose of this study was to determine the sarcopenic index in a large population of chronic stroke survivors and compare this group to age, gender, and BMI-matched non-stroke controls. Chronic stroke survivors aged 40 to 84 yrs (n=180, 61% female, 59% African American, BMI: 29±1 kg/m 2 , X±SEM) with mild to moderate gait deficits underwent whole body DXA scans to assess sarcopenic index (appendicular lean mass/ht 2 ). The cutoffs for sarcopenia, by the European Working Group on Sarcopenia, were used and defined as a skeletal muscle index of <7.23 kg/m 2 in men and <5.67 kg/m 2 in women. In the entire group, the prevalence of sarcopenia in stroke survivors (13%) did not differ significantly from that of populations reported previously in the literature. In 61-70 year olds, 87% (n=63) had normal muscle mass and 13% (n=9) were sarcopenic. In 71-80 year olds, 79% (n=30) had normal skeletal muscle index and 21% (n=8) were sarcopenic. Stroke survivors (n=39) were matched with 39 controls on the basis of race, gender, age ±4 years and BMI±2.5 units. After matched pair analysis, 5.1% of the controls had sarcopenia while 12.8% of the control group were sarcopenic (P<0.0001). Sarcopenic index was related to six-minute walking speed (r=0.28, P<0.01). In conclusion, stroke survivors may be at an elevated risk for sarcopenia when considering age, gender, and race to non-stroke individuals which is related to functional mobility in this population.

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Cognitive and Motor Deficits Contribute to Longer Braking Time in Stroke

10.21203/rs.3.rs-42277/v1 ◽

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.

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