Monitoring of Physical Activity After Stroke: A Systematic Review of Accelerometry-Based Measures

Gebruers, Nick; Vanroy, Christel; Truijen, Steven; Engelborghs, Sebastiaan; Deyn, Peter Paul De

doi:10.1016/j.apmr.2009.10.025

Cited by 245 publications

(188 citation statements)

References 42 publications

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“…The clinometric properties of accelerometry to measure activity in patients with stroke are promising, especially the validity and reliability of accelerometry to measure the activity of patients with stroke in the different stages, demonstrated by means of various protocols [3]. In this study, we were particularly interested in measuring the activity of the upper limbs.…”

Section: Introductionmentioning

confidence: 99%

“…Uswatte et al provided significant evidence about the validity and reliability of accelerometry to measure upper-limb activity in stroke [4][5][6][7][8]. Details about the clinometric properties of upper-limb accelerometrybased measurements are published elsewhere [3]. Additional information for the validity of accelerometry-based measurements taken in the acute phase of stroke came from one of our own studies [9].…”

Section: Introductionmentioning

confidence: 99%

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Predictive value of upper-limb accelerometry in acute stroke with hemiparesis

et al. 2013

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Abstract-Few studies have investigated how well early activity measurements by accelerometers predict recovery after stroke. First, we assessed the predictive value of accelerometer-based measurements of upper-limb activity in patients with acute stroke with a hemiplegic arm. Second, we established the difference in arm activity between hospitalized stroke and nonstroke patients. In total, 129 patients with acute stroke and 19 controls participated. Activity of the upper limbs was monitored for 48 h, and these data were used to determine the predictive value of the activity variables compared with the modified Rankin Scale (mRS), which was assessed at 3 mo poststroke onset. The sensitivity and specificity in relation to the mRS were 0.80 and 0.77, respectively, for the activity of impaired arm (AIA) and 0.85 and 0.75, respectively, for the ratio variable calculated by dividing the AIA by the activity of the nonimpaired arm. The corresponding cutoff values were 597,546 counts for AIA and 0.33 for the ratio. The predictive value of AIA combined with age was 85% to the disability status defined as an mRS score of 2 or less.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Predictive value of upper-limb accelerometry in acute stroke with hemiparesis

et al. 2013

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“…If physical activity and exercise were found to affect the cognitive function of patients with CVD, it would be possible to design effective interventions for daily life and rehabilitation. On the other hand, although quantitative data are available for the amount of physical activity undertaken by subjects living at home after the onset of stroke (Field et al, 2013), and some studies have investigated physical activity in CVD patients (Gebruers et al, 2010) and compared the physical activity of hospitalized patients with that of patients at home after discharge (Hosoi et al, 2011), little is known about physical activity in CVD patients during the period of recovery. In the present study, therefore, we evaluated the physical activity of convalescent CVD patients, and assessed its relationship with cognitive function.…”

Section: Introductionmentioning

confidence: 99%

The Association between Total Energy Expenditure and Cognitive Function in Convalescent Patients with Cerebrovascular Disease*

Kojima

Nagano

2018

Int. J. Sport Health Sci.

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(Abstract) [Objective] It has been reported that everyday physical activity, exercise, and physical fitness in older adults can affect their cognitive function. However, to our knowledge, no empirical evidence of this effect has yet been reported in convalescent patients with cognitive impairment resulting from cerebrovascular disease. Therefore, for such patients, it is important to investigate this issue to ensure optimal amelioration of their cognitive impairment during rehabilitation.The aim of this study was to estimate the amount of total energy expenditure during hospitalization, and to investigate the association between total energy expenditure and cognitive function in convalescent patients with cerebrovascular [Results] Both total energy expenditure and cognitive items on the FIM increased significantly (p<0.001) during the five-month period. A significant correlation was found between them (r=0.294, p=0.001), and the two showed a significant partial correlation (r=0.221, p=0.016) when weight was used as a control variable. There was also a significant partial correlation between the gain in total energy expenditure and the gain in the cognitive items on the FIM when the baseline score for cognitive function was used as a control variable (3 months: r=0.466, p=0.044; 5 months: r=0.485, p=0.035).[Discussion] We conclude that there is a relationship between total energy expenditure and cognitive function in convalescent patients with cerebrovascular disease.

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“…The ability to walk is essential to execute the full range of activities of daily living. 6) In ad-dition to rehabilitation treatment, therapists often instruct patients to walk for the purpose of self-training to improve their ability to perform the activities of daily living.…”

Section: Introductionmentioning

confidence: 99%

Optimal Conditions for Obtaining Valid Step Count Measurements in Hospitalized Patients with Abnormal Gait

Oba

Iwase

Oshima

et al. 2017

PRM

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Objective: This study investigated the optimum conditions for obtaining valid step-count measurements for patients with abnormal gait. Methods: Subjects comprised 61 hospitalized patients with abnormal gait. Four different devices were tested: Active Style Pro (AS), Walking Style (WS), Lifecorder PLUS, and Steps. The same device type was attached to the waist on both the affected and the unaffected side. Patients then walked 25 m at a comfortable speed. This test was repeated four times, once for each device. The measurement error (ME) and walking parameters (gait velocity, step length, and cadence) were calculated from the test data. ME scores smaller than 3% and 10% were classified as valid: scores above these standards were classified as invalid.Walking parameter values that identified the invalid group with a specificity of 0.95 were set as the cut-off velocity (COV), the cut-off step length (COS), and the cut-off cadence. Sensitivity values >0.40 and positive predictive values >80% were then set as necessary conditions. Results: COV values were 0.90 m/s (AS on the unaffected side at 3% ME and AS on the affected side or the unaffected side at 10% ME), 0.92 m/s (WS on the unaffected side at 10% ME), and 0.98 m/s (WS on the affected side at 3% ME). COS values were 0.50 m (AS on the affected side at 10% ME) and 0.52 m (AS on the unaffected side at 3% ME). Conclusion: The most accurate measurements were obtained using AS attached to the unaffected side with a gait velocity of >0.90 m/s.

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Monitoring of Physical Activity After Stroke: A Systematic Review of Accelerometry-Based Measures

Cited by 245 publications

References 42 publications

Predictive value of upper-limb accelerometry in acute stroke with hemiparesis

Predictive value of upper-limb accelerometry in acute stroke with hemiparesis

The Association between Total Energy Expenditure and Cognitive Function in Convalescent Patients with Cerebrovascular Disease*

Optimal Conditions for Obtaining Valid Step Count Measurements in Hospitalized Patients with Abnormal Gait

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