Arm impairment and walking speed explain real-life activity of the affected arm and leg after stroke

Abstract

Objective To determine to what extent accelerometer-based arm, leg and trunk activity is associated with sensorimotor impairments, walking capacity and other factors in subacute stroke. Design Cross-sectional study. Patients Twenty-six individuals with stroke (mean age 55.4 years, severe to mild motor impairment). Methods Data on daytime activity were collected over a period of 4 days from accelerometers placed on the wrists, ankles and trunk. A forward stepwise linear regression was used to determine associations between free-living activity, clinical and demographic variables. Results Arm motor impairment (Fugl-Meyer Assessment) and walking speed explained more than 60% of the variance in daytime activity of the more-affected arm, while walking speed alone explained 60% of the more-affected leg activity. Activity of the less-affected arm and leg was associated with arm motor impairment (R 2 = 0.40) and independence in walking (R 2 = 0.59). Arm activity ratio was associated with arm impairment (R 2 = 0.63) and leg activity ratio with leg impairment (R 2 = 0.38) and walking speed (R 2 = 0.27). Walking-related variables explained approximately 30% of the variance in trunk activity. Conclusion Accelerometer-based free-living activity is dependent on motor impairment and walking capacity. The most relevant activity data were obtained from more-affected limbs. Motor impairment and walking speed can provide some information about real-life daytime activity levels. LAY ABSTRACT Activity data from accelerometers can help clinicians to better understand factors limiting physical activity levels. This study aimed to determine to what degree arm, leg and trunk activity, measured with accelerometers, is associated with sensorimotor impairments, walking and other factors in people with stroke in the subacute stage of recovery. Real-life activity, measured by accelerometers, was primarily associated with motor impairment and walking speed. Spasticity, dependency in walking, and disability level also showed association with real-life activity, although to a lesser degree. Accelerometers, placed on the more-affected wrist and ankle, provided most relevant clinical information and are therefore recommended for research and clinical practice. The strong associations observed in this study suggest that when accelerometers are not available, clinical assessments of arm motor function and walking speed can provide some information on real-life activity levels in people with stroke.

Quantification of Movement in Stroke Patients under Free Living Conditions Using Wearable Sensors: A Systematic Review

“…One study was excluded due to poor methodological quality, scoring only four points ( Supplementary Materials ). Out of the remaining 32 studies that were included for data synthesis, 29 (91%) were of high quality [ 5 , 8 , 9 , 10 , 11 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 ] and three (9%) of moderate quality [ 43 , 44 , 45 ]. This inclusion process is described in Figure 1 .…”

“…Reported Time After Stroke (TAS) was highly different between studies: five studies took place during the acute phase of stroke [ 33 , 38 , 40 , 42 , 43 ]—less than a week, as defined by Bernhardt et al [ 46 ]—another eight included patients during the early sub-acute phase [ 5 , 10 , 21 , 22 , 25 , 30 , 34 , 39 ] and eleven focused on chronic stroke patients [ 8 , 9 , 11 , 20 , 26 , 27 , 28 , 29 , 36 , 41 , 44 ]. The remaining articles included patients which were in different phases after stroke onset: acute and early sub-acute [ 23 , 24 ], early-subacute and late subacute [ 19 ], late sub-acute and chronic [ 35 ] or early, late and chronic phase [ 31 , 32 , 37 , 45 ].…”

“…Accelerometers and activity monitors—with embedded accelerometer sensors—were used in all studies ( Figure 2 ). Five studies used inertial measurement units (IMUs) [ 19 , 31 , 32 , 34 , 45 ] that combine tri-axial accelerometers, gyroscopes and magnetometers, although three of them [ 19 , 34 , 45 ] did not include the data from the magnetometer in their analysis. The other two studies [ 31 , 32 ] used IMUs as part of a full body motion measuring system.…”

“…Except for the studies [ 29 , 44 ], in which the (electrohydraulic) sensors were placed along the arm, from shoulder to wrist, and [ 36 ] in which a magnetic ring was used as part of the setup, the information of the additional sensors was used to derive parameters for full body kinematic models [ 31 , 32 ], activity recognition or gait detection [ 10 , 19 , 20 , 26 , 35 , 39 ]. Four studies combined upper and lower body data [ 5 , 34 , 37 , 43 ], and three focused on walking only, in particular on the amount, number of walking bouts and gait characteristics [ 11 , 21 , 23 ]. While the wrists were clearly the preferred location of upper body studies, gait and lower body performance were evaluated by using single or a combination of sensors on the sternum, lower back, hips, thighs and ankles [ 11 , 21 , 23 ].…”

“…Several studies [ 5 , 8 , 9 , 10 , 19 , 20 , 22 , 24 , 25 , 28 , 30 , 35 , 36 , 39 , 40 , 41 , 42 , 43 ] integrated this value over a time window -ranging from a few seconds [ 8 ] to several hours [ 10 ]- to quantify the amount and intensity of upper limb movement. Studies that reported their findings using similar values, like the signal magnitude area [ 34 ], or ‘counts’ are also included in this category. Counts represent filtered and summed acceleration signals, created by the software of manufacturers of several commercially available activity trackers.…”

Quantification of Movement in Stroke Patients under Free Living Conditions Using Wearable Sensors: A Systematic Review

“…One study was excluded due to poor methodological quality, scoring only four points ( Supplementary Materials ). Out of the remaining 32 studies that were included for data synthesis, 29 (91%) were of high quality [ 5 , 8 , 9 , 10 , 11 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 ] and three (9%) of moderate quality [ 43 , 44 , 45 ]. This inclusion process is described in Figure 1 .…”

“…Reported Time After Stroke (TAS) was highly different between studies: five studies took place during the acute phase of stroke [ 33 , 38 , 40 , 42 , 43 ]—less than a week, as defined by Bernhardt et al [ 46 ]—another eight included patients during the early sub-acute phase [ 5 , 10 , 21 , 22 , 25 , 30 , 34 , 39 ] and eleven focused on chronic stroke patients [ 8 , 9 , 11 , 20 , 26 , 27 , 28 , 29 , 36 , 41 , 44 ]. The remaining articles included patients which were in different phases after stroke onset: acute and early sub-acute [ 23 , 24 ], early-subacute and late subacute [ 19 ], late sub-acute and chronic [ 35 ] or early, late and chronic phase [ 31 , 32 , 37 , 45 ].…”

“…Accelerometers and activity monitors—with embedded accelerometer sensors—were used in all studies ( Figure 2 ). Five studies used inertial measurement units (IMUs) [ 19 , 31 , 32 , 34 , 45 ] that combine tri-axial accelerometers, gyroscopes and magnetometers, although three of them [ 19 , 34 , 45 ] did not include the data from the magnetometer in their analysis. The other two studies [ 31 , 32 ] used IMUs as part of a full body motion measuring system.…”

“…Except for the studies [ 29 , 44 ], in which the (electrohydraulic) sensors were placed along the arm, from shoulder to wrist, and [ 36 ] in which a magnetic ring was used as part of the setup, the information of the additional sensors was used to derive parameters for full body kinematic models [ 31 , 32 ], activity recognition or gait detection [ 10 , 19 , 20 , 26 , 35 , 39 ]. Four studies combined upper and lower body data [ 5 , 34 , 37 , 43 ], and three focused on walking only, in particular on the amount, number of walking bouts and gait characteristics [ 11 , 21 , 23 ]. While the wrists were clearly the preferred location of upper body studies, gait and lower body performance were evaluated by using single or a combination of sensors on the sternum, lower back, hips, thighs and ankles [ 11 , 21 , 23 ].…”

“…Several studies [ 5 , 8 , 9 , 10 , 19 , 20 , 22 , 24 , 25 , 28 , 30 , 35 , 36 , 39 , 40 , 41 , 42 , 43 ] integrated this value over a time window -ranging from a few seconds [ 8 ] to several hours [ 10 ]- to quantify the amount and intensity of upper limb movement. Studies that reported their findings using similar values, like the signal magnitude area [ 34 ], or ‘counts’ are also included in this category. Counts represent filtered and summed acceleration signals, created by the software of manufacturers of several commercially available activity trackers.…”

Quantification of Movement in Stroke Patients under Free Living Conditions Using Wearable Sensors: A Systematic Review

“…One study was excluded due to poor methodological quality, scoring only four points ( Supplementary Materials ). Out of the remaining 32 studies that were included for data synthesis, 29 (91%) were of high quality [ 5 , 8 , 9 , 10 , 11 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 ] and three (9%) of moderate quality [ 43 , 44 , 45 ]. This inclusion process is described in Figure 1 .…”

“…Reported Time After Stroke (TAS) was highly different between studies: five studies took place during the acute phase of stroke [ 33 , 38 , 40 , 42 , 43 ]—less than a week, as defined by Bernhardt et al [ 46 ]—another eight included patients during the early sub-acute phase [ 5 , 10 , 21 , 22 , 25 , 30 , 34 , 39 ] and eleven focused on chronic stroke patients [ 8 , 9 , 11 , 20 , 26 , 27 , 28 , 29 , 36 , 41 , 44 ]. The remaining articles included patients which were in different phases after stroke onset: acute and early sub-acute [ 23 , 24 ], early-subacute and late subacute [ 19 ], late sub-acute and chronic [ 35 ] or early, late and chronic phase [ 31 , 32 , 37 , 45 ].…”

“…Accelerometers and activity monitors—with embedded accelerometer sensors—were used in all studies ( Figure 2 ). Five studies used inertial measurement units (IMUs) [ 19 , 31 , 32 , 34 , 45 ] that combine tri-axial accelerometers, gyroscopes and magnetometers, although three of them [ 19 , 34 , 45 ] did not include the data from the magnetometer in their analysis. The other two studies [ 31 , 32 ] used IMUs as part of a full body motion measuring system.…”

“…Except for the studies [ 29 , 44 ], in which the (electrohydraulic) sensors were placed along the arm, from shoulder to wrist, and [ 36 ] in which a magnetic ring was used as part of the setup, the information of the additional sensors was used to derive parameters for full body kinematic models [ 31 , 32 ], activity recognition or gait detection [ 10 , 19 , 20 , 26 , 35 , 39 ]. Four studies combined upper and lower body data [ 5 , 34 , 37 , 43 ], and three focused on walking only, in particular on the amount, number of walking bouts and gait characteristics [ 11 , 21 , 23 ]. While the wrists were clearly the preferred location of upper body studies, gait and lower body performance were evaluated by using single or a combination of sensors on the sternum, lower back, hips, thighs and ankles [ 11 , 21 , 23 ].…”

“…Several studies [ 5 , 8 , 9 , 10 , 19 , 20 , 22 , 24 , 25 , 28 , 30 , 35 , 36 , 39 , 40 , 41 , 42 , 43 ] integrated this value over a time window -ranging from a few seconds [ 8 ] to several hours [ 10 ]- to quantify the amount and intensity of upper limb movement. Studies that reported their findings using similar values, like the signal magnitude area [ 34 ], or ‘counts’ are also included in this category. Counts represent filtered and summed acceleration signals, created by the software of manufacturers of several commercially available activity trackers.…”

Quantification of Movement in Stroke Patients under Free Living Conditions Using Wearable Sensors: A Systematic Review

“…One study was excluded due to poor methodological quality, scoring only four points ( Supplementary Materials ). Out of the remaining 32 studies that were included for data synthesis, 29 (91%) were of high quality [ 5 , 8 , 9 , 10 , 11 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 ] and three (9%) of moderate quality [ 43 , 44 , 45 ]. This inclusion process is described in Figure 1 .…”

“…Reported Time After Stroke (TAS) was highly different between studies: five studies took place during the acute phase of stroke [ 33 , 38 , 40 , 42 , 43 ]—less than a week, as defined by Bernhardt et al [ 46 ]—another eight included patients during the early sub-acute phase [ 5 , 10 , 21 , 22 , 25 , 30 , 34 , 39 ] and eleven focused on chronic stroke patients [ 8 , 9 , 11 , 20 , 26 , 27 , 28 , 29 , 36 , 41 , 44 ]. The remaining articles included patients which were in different phases after stroke onset: acute and early sub-acute [ 23 , 24 ], early-subacute and late subacute [ 19 ], late sub-acute and chronic [ 35 ] or early, late and chronic phase [ 31 , 32 , 37 , 45 ].…”

“…Accelerometers and activity monitors—with embedded accelerometer sensors—were used in all studies ( Figure 2 ). Five studies used inertial measurement units (IMUs) [ 19 , 31 , 32 , 34 , 45 ] that combine tri-axial accelerometers, gyroscopes and magnetometers, although three of them [ 19 , 34 , 45 ] did not include the data from the magnetometer in their analysis. The other two studies [ 31 , 32 ] used IMUs as part of a full body motion measuring system.…”

“…Except for the studies [ 29 , 44 ], in which the (electrohydraulic) sensors were placed along the arm, from shoulder to wrist, and [ 36 ] in which a magnetic ring was used as part of the setup, the information of the additional sensors was used to derive parameters for full body kinematic models [ 31 , 32 ], activity recognition or gait detection [ 10 , 19 , 20 , 26 , 35 , 39 ]. Four studies combined upper and lower body data [ 5 , 34 , 37 , 43 ], and three focused on walking only, in particular on the amount, number of walking bouts and gait characteristics [ 11 , 21 , 23 ]. While the wrists were clearly the preferred location of upper body studies, gait and lower body performance were evaluated by using single or a combination of sensors on the sternum, lower back, hips, thighs and ankles [ 11 , 21 , 23 ].…”

“…Several studies [ 5 , 8 , 9 , 10 , 19 , 20 , 22 , 24 , 25 , 28 , 30 , 35 , 36 , 39 , 40 , 41 , 42 , 43 ] integrated this value over a time window -ranging from a few seconds [ 8 ] to several hours [ 10 ]- to quantify the amount and intensity of upper limb movement. Studies that reported their findings using similar values, like the signal magnitude area [ 34 ], or ‘counts’ are also included in this category. Counts represent filtered and summed acceleration signals, created by the software of manufacturers of several commercially available activity trackers.…”