Asymmetries in force matching are related to side of stroke in right-handed individuals

Anderson, Charlie; Rajamani, Kumar; Pardo, Victoria Mazoteras; Adamo, Diane E.

doi:10.1016/j.neulet.2018.07.034

Cited by 5 publications

(4 citation statements)

References 44 publications

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“…Three patients scored better than agematched healthy controls, leaving 25 scoring at a lower level of performance. Of these 25 patients, 13 were within the RHD group and 12 were within the LHD group, providing supporting evidence that force production in both the contralesional and ipsilesional limb is affected following unilateral MCA stroke, as has been previously reported (Anderson, et al, 2018;Naik, et al, 2011;Nowak, et al, 2007). When examining performance deficits within the LHD group, difficulty performing the force matching task may arise from several sources resulting in paresis, including damage to both motor and premotor regions (in addition to the disruption of connections between these) (Cash, et al, 2015) and to the white matter pathways ultimately responsible for the innervation of lower motor neurons that allow for direct control of the fingertips (Dum & Strick, 1996;Lang & Schieber, 2003).…”

Section: Control Of Distal Fingertipsupporting

confidence: 83%

Sensorimotor control of object manipulation following middle cerebral artery (MCA) stroke

Fercho

Scholl

et al. 2023

Neuropsychologia

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Section: Control Of Distal Fingertipsupporting

confidence: 83%

Sensorimotor control of object manipulation following middle cerebral artery (MCA) stroke

Fercho

Scholl

et al. 2023

Neuropsychologia

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“…Twenty-six (26) Participants took part in this cross-sectional study. Inclusion criteria were: (a) first unilateral stroke (ischemic or hemorrhagic) ( Murphy et al, 2011 ), (b) age 18–85 years ( Kamper et al, 2002 ), (c) Mini-Mental State Examination (MMSE) score ≥ 24/30 ( Anderson et al, 2018 ) for participants >65, or MOCA score > 23 for participants <65, (d) Fugl-Meyer Upper Extremity assessment (FMA) score 16–60: a validated four-level classification of the FMA was used in order to include only patients who have at least some movement ability in the affected arm ( Woytowicz et al, 2016 ). Please see Table 1 for further description of the participants.…”

Section: Methodsmentioning

confidence: 99%

Correlation between kinetic and kinematic measures, clinical tests and subjective self-evaluation questionnaires of the affected upper limb in people after stroke

Baer,

Feingold-Polak,

Ostrovsky

et al. 2023

Front. Neurosci.

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IntroductionAssessment of stroke recovery should include multiple sources of information in order to obtain a complete understanding of the individual’s rehabilitation progress. Self-evaluation questionnaires’ scores do not always correspond to the scores of commonly used clinical evaluation tools. The purpose of this study was to assess the relationship between self-evaluation questionnaires, clinical tests, and kinematic and kinetic analyses of the affected upper limb after stroke, and to determine the correlation between these measures and self-reported general function 2–4 years after the stroke.MethodsTwenty-six subjects recovering from stroke were included in the study. Spearman’s correlation coefficient was used to measure the correlation between Stroke Impact Scale (SIS), Motor activity Log (MAL), Fugl-Meyer Assessment (FMA) and Action Reach Arm Test (ARAT) scores, and kinematic and kinetic analyses. A logistic regression was used to assess the extent to which these measures may predict the participants’ functional self-reported status 2–4 years post stroke.ResultsSections regarding hand function, hand force and general ADL of the self-evaluation questionnaires correlated with kinematic variables. However, only questionnaires that focus on hand function correlated with clinical tests. Mean and maximal hand velocity had the strongest correlations with self-evaluation questionnaires and with the clinical tests, more than other kinematic variables. Self-evaluation questionnaires and clinical tests were found to be correlated with hand kinetic metrics force-to-time ratio and number of force peaks. SIS hand force domain, mean velocity and maximal velocity predicted self-reported general function 2–4 years after the stroke.ConclusionSelf-evaluation questionnaires should be considered for wider use in the clinical evaluation of a patient’s stroke recovery, since they add important information on the individual’s functional status, which is not reflected in the clinical tests.

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“…Relaxation time was determined as the time duration from the rest cue to grip termination defined as when grip force returned to the baseline force level within 3 SD (Seo et al, 2009 ). Force magnitude control was quantified as the absolute difference between the target force and mean grip force during grip (Figure 1b ; Anderson et al, 2018 ; Quaney et al, 2005 ). Force direction control was quantified as the mean angular deviation of digit force from the direction normal to the grip surface during grip (Figure 1c ; Seo et al, 2010 , 2015 ).…”

Section: Methodsmentioning

confidence: 99%

Different aspects of hand grip performance associated with structural connectivity of distinct sensorimotor networks in chronic stroke

Schranz

Srivastava

Seamon

et al. 2023

Physiological Reports

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Knowledge regarding the neural origins of distinct upper extremity impairments may guide the choice of interventions to target neural structures responsible for specific impairments. This cross-sectional pilot study investigated whether different brain networks explain distinct aspects of hand grip performance in stroke survivors. In 22 chronic stroke survivors, hand grip performance was characterized as grip strength, reaction, relaxation times, and control of grip force magnitude and direction. In addition, their brain structural connectomes were constructed from diffusion tensor MRI. Prominent networks were identified based on a twostep factor analysis using the number of streamlines among brain regions relevant to sensorimotor function. We used regression models to estimate the predictive value of sensorimotor network connectivity for hand grip performance measures while controlling for stroke lesion volumes. Each hand grip performance measure correlated with the connectivity of distinct brain sensorimotor networks. These results suggest that different brain networks may be responsible for different aspects of hand grip performance, which leads to varying clinical presentations of upper extremity impairment following stroke. Understanding the brain network

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Asymmetries in force matching are related to side of stroke in right-handed individuals

Cited by 5 publications

References 44 publications

Sensorimotor control of object manipulation following middle cerebral artery (MCA) stroke

Sensorimotor control of object manipulation following middle cerebral artery (MCA) stroke

Correlation between kinetic and kinematic measures, clinical tests and subjective self-evaluation questionnaires of the affected upper limb in people after stroke

Different aspects of hand grip performance associated with structural connectivity of distinct sensorimotor networks in chronic stroke

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