Relating Movement Control at 9 Upper Extremity Segments to Loss of Hand Function in People with Chronic Hemiparesis

Lang, Catherine E.; Beebe, Justin A.

doi:10.1177/1545968306296964

Cited by 101 publications

(114 citation statements)

References 55 publications

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“…Our sample included people with chronic stroke, whereas the sample of Beebe and Lang included people with hemiparesis early after stroke [16]. Despite low correlations between the NHPT and the MAL, our data of moderate correlations between the NHPT and the SIS hand function domain were similar to the published data [16][17]. This likely reflects the fact that self-perceived actual use (MAL-AOU) captured information that was not assessed by the NHPT scale and that fine manual dexterity is an important component that determines the hand function aspect of quality of life after stroke.…”

Section: Discussionsupporting

confidence: 77%

“…In our study, only 22 percent (13/59) of participants showed perfect scores on the ARAT. Moreover, fair correlations between the ARAT and the SIS hand function domain at pretreatment and posttreatment were somewhat lower than the correlations reported in previous studies (0.57-0.83) [16][17]. Variations in the magnitude of the correlations between studies may arise from differences in time elapsed since the stroke and the initiation of intervention protocols.…”

Section: Discussioncontrasting

confidence: 50%

“…Among the UL function tests, the BBT [7,[12][13][14][22][23], NHPT [5,12,14,17,[24][25][26], and ARAT [1,5,7,[16][17]27] are three commonly used clinical measures to assess hand dexterous function in patients with stroke. Limited research directly compared the clinimetric properties between pairs of the BBT, NHPT, and ARAT in patients with stroke [7,12,14,16].…”

Section: Introductionmentioning

confidence: 99%

“…In the past 5 years, a number of UL function tests have been examined for their psychometric and clinimetric properties in people with stroke, including the FuglMeyer Assessment (FMA) [6][7][8], Wolf Motor Function Test (WMFT) [6,[9][10][11], Box and Block Test (BBT) [7,[12][13][14], Nine-Hole Peg Test (NHPT) [12,[15][16][17], Action Research Arm Test (ARAT) [6][7][8]11,[16][17][18], and Stroke Impact Scale (SIS) [16,[19][20]. The comparisons of outcome measures of UL motor function have been investigated in patients with stroke [6][7]16,21].…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Responsiveness and validity of three dexterous function measures in stroke rehabilitation

Lin

Chuang²,

et al. 2010

JRRD

135

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Abstract-In this study, we compared the responsiveness and validity of the Box and Block Test (BBT), the Nine-Hole Peg Test (NHPT), and the Action Research Arm Test (ARAT). We randomized 59 patients with stroke into one of three rehabilitation treatments for 3 weeks. We administered six outcome measures (BBT, NHPT, ARAT, Fugl-Meyer Assessment [FMA], Motor Activity Log [MAL], and Stroke Impact Scale [SIS] hand function domain) pretreatment and posttreatment. We used the standardized response mean (SRM) to examine responsiveness and the Spearman rank correlation coefficient (rho) to examine concurrent validity. The BBT, NHPT, and ARAT were moderately responsive to change and not significantly different (SRM = 0.64-0.79). The correlations within the BBT, NHPT, and ARAT were moderate to good at pretreatment (rho = -0.55 to -0.80) and posttreatment (rho = -0.57 to -0.71). The BBT and ARAT showed fair to moderate correlations with the FMA, MAL, and SIS hand function domain at pretreatment and posttreatment (rho = 0.31-0.59), whereas the NHPT demonstrated low to fair correlations with the FMA and MAL (rho = -0.16 to -0.33) and moderate correlations with the SIS hand function domain (rho = -0.58 to -0.66). Our results indicate that the BBT, NHPT, and ARAT are suitable to detect changes over time. While simultaneously considering the responsiveness and validity attributes, the BBT and ARAT can be considered more appropriate for evaluating dexterous function than the NHPT. Further studies with larger samples are needed to validate these findings. Clinical

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Section: Discussionsupporting

confidence: 77%

Section: Discussioncontrasting

confidence: 50%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Responsiveness and validity of three dexterous function measures in stroke rehabilitation

Lin

Chuang²,

et al. 2010

JRRD

135

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show abstract

“…It is also one of the leading causes of disability with an estimated 50% of survivors suffering from permanent motor or cognitive impairments 2. Upper limb disability is particularly critical as it is highly prevalent and vastly reduces independence in activities of daily living (ADL) 3, 4. Currently, motor rehabilitation techniques for stroke patients with hemiplegia usually include physical therapy and constraint‐induced movement therapy (CIMT),5 which require some residual movement of the affected limb.…”

Section: Introductionmentioning

confidence: 99%

Brain‐computer interfaces for post‐stroke motor rehabilitation: a meta‐analysis

Cervera

Soekadar

Ushiba

et al. 2018

Ann Clin Transl Neurol

365

267

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Brain‐computer interfaces (BCIs) can provide sensory feedback of ongoing brain oscillations, enabling stroke survivors to modulate their sensorimotor rhythms purposefully. A number of recent clinical studies indicate that repeated use of such BCIs might trigger neurological recovery and hence improvement in motor function. Here, we provide a first meta‐analysis evaluating the clinical effectiveness of BCI‐based post‐stroke motor rehabilitation. Trials were identified using MEDLINE, CENTRAL, PEDro and by inspection of references in several review articles. We selected randomized controlled trials that used BCIs for post‐stroke motor rehabilitation and provided motor impairment scores before and after the intervention. A random‐effects inverse variance method was used to calculate the summary effect size. We initially identified 524 articles and, after removing duplicates, we screened titles and abstracts of 473 articles. We found 26 articles corresponding to BCI clinical trials, of these, there were nine studies that involved a total of 235 post‐stroke survivors that fulfilled the inclusion criterion (randomized controlled trials that examined motor performance as an outcome measure) for the meta‐analysis. Motor improvements, mostly quantified by the upper limb Fugl‐Meyer Assessment (FMA‐UE), exceeded the minimal clinically important difference (MCID=5.25) in six BCI studies, while such improvement was reached only in three control groups. Overall, the BCI training was associated with a standardized mean difference of 0.79 (95% CI: 0.37 to 1.20) in FMA‐UE compared to control conditions, which is in the range of medium to large summary effect size. In addition, several studies indicated BCI‐induced functional and structural neuroplasticity at a subclinical level. This suggests that BCI technology could be an effective intervention for post‐stroke upper limb rehabilitation. However, more studies with larger sample size are required to increase the reliability of these results.

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Selective BOLD responses to individual finger movement measured with fMRI at 3T

Olman¹,

Pickett²,

Schallmo³

et al. 2011

Human Brain Mapping

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Although the gross somatotopic organization of the posterior bank of the precentral gyrus is well established, a fine scale organization of the representations of the digits of the hand has not been fully characterized. Previous neuroimaging studies have failed to find clear evidence for a specificity of digit representations in motor cortex, but rather report a distributed network of control. Reported here are the results of two experiments; in Experiment 1 a sequential finger tapping task produced strong blood oxygen level dependent (BOLD) responses in the contralateral precentral gyrus, but there was a lack of specificity for distinguishing individual representations. A randomly ordered task did accomplish this goal. In the second experiment, a randomly ordered finger-tapping task was used and the findings demonstrated BOLD responses in clusters of voxels specific to movement of a single digit. The region of interest defined for each digit comprised several noncontiguous clusters. A “selectivity index” was developed to quantify the magnitude of the BOLD response to the movement of a specific digit, relative to BOLD response associated with movement of other digits. Strong evidence of BOLD selectivity (albeit not exclusivity) was found in the hemisphere contralateral to the cued digit; however, there was no evidence for an orderly spatial topography. These findings demonstrate that a selectivity of activation is quantifiable, supports a theory of noncontiguous distribution of control, and provides a method for comparing between healthy and impaired populations and investigating changes following training or intervention.

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Relating Movement Control at 9 Upper Extremity Segments to Loss of Hand Function in People with Chronic Hemiparesis

Abstract: These data support the idea that loss of movement control covaries across segments and that loss of hand function is due to loss of movement control at all segments, not just at distal ones.

Cited by 101 publications

References 55 publications

Responsiveness and validity of three dexterous function measures in stroke rehabilitation

Responsiveness and validity of three dexterous function measures in stroke rehabilitation

Brain‐computer interfaces for post‐stroke motor rehabilitation: a meta‐analysis

Selective BOLD responses to individual finger movement measured with fMRI at 3T

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