Cardiorespiratory fitness levels are low early after stroke (i.e., <1 month since stroke onset), with fitness levels of stroke survivors ranging from 44% to 76% that of age- and sex-matched sedentary healthy adults [
Indirect calorimetry using a metabolic cart is commonly used to measure the EE of physical activities. The metabolic cart measures the volume of oxygen uptake (VO2) using breath-by-breath analyses and has been shown to be a valid measure of VO2 uptake during different workloads in sedentary adults, moderately trained individuals, and athletes [
In a recent systematic review 60 different devices to measure physical activity in stroke were identified [
This study is a part of a larger study in which we aimed to compare EE of acute stroke survivors to healthy controls. In this paper we will only discuss the result regarding the validity and reliability of the SWAunaffected. Using a mobile metabolic cart as a gold standard we sought to determine the concurrent validity and reliability of SWA measures of EE during a physical activity in stroke survivors whose stroke onset was less than 1 month ago. We hypothesised that the SWAunaffected is a valid and reliable tool to estimate EE during activity in acute stroke survivors.
Stroke survivors admitted to the acute stroke ward at the Austin Hospital in Melbourne, Australia, were eligible to participate if they met the following criteria: (1) >18 years of age, (2) being within 1 month after stroke, (3) clinically diagnosed with stroke, (4) cognitively able to consent as assessed by the treating clinician, (5) sufficient English language command to follow complex instructions, and (6) medically cleared to participate by their treating clinician.
Stroke survivors were excluded from participating in the study if they had (1) comorbidities that impaired their ability to either walk or perform sit-to-stands (i.e., repeated standing up from and sitting down on a plinth) for six minutes (e.g., severe Chronic Obstructive Pulmonary Disorder, lower limb surgery) or (2) other neurological comorbidities that might affect the EE of activity (e.g., Parkinson’s disease).
All stroke survivors who participated in this study provided written informed consent. The study was approved by the Austin Health Human Research Ethics Committee (reference number H2011/04447).
Each participant’s age, height (measured using a stadiometer), weight while clothed but without shoes (measured using digital scales), and smoking status were recorded. Additionally, we obtained date of stroke, severity of stroke on admission, and stroke subtype from the participant’s medical records. The National Institutes of Health Stroke Severity (NIHSS) scale was used to measure stroke severity with scores ranging from 0 to 42. Stroke severity was categorised into mild (<8), moderate (8–16), and severe (>16) [
To measure EE of activity in both ambulatory and nonambulatory stroke survivors, we used two different test protocols: walking and sit-to-stand. Stroke survivors able to ambulate under supervision or with light manual support for balance and coordination (with or without a walking aid) performed the walking protocol. Stroke survivors who were unable to walk independently and needed manual support from at least two people performed the sit-to-stand protocol. We consulted with the participants’ treating clinician (i.e., neurologist or allied health professional) to determine which protocol was most appropriate. All participants started with a three-minute resting period in a seated position followed by two bouts of six minutes of continuous activity (i.e., walking or sit-to-stands). Between the two bouts, participants rested for 30 minutes in different positions (i.e., seated, lying flat, and lying on an incline), allowing EE to return to baseline levels before commencing the second six-minute bout. We aimed for participants to reach steady-state during the six-minute activity bouts, with steady-state defined as variability in VO2 of less than 2.0 mLO2/kg/min over the last three minutes of activity [
Ambulatory stroke survivors walked back and forth along a 30-metre corridor at a self-selected pace. Participants performing the sit-to-stand protocol started in a seated position on a height-adjustable physiotherapy plinth, which was set at a height that required moderate effort and minimal assistance only for balance from the researchers. Before every test we emphasised to the participant that the goal was to move at a steady pace and
EE was measured using a metabolic cart (Oxycon™ Mobile Device, CareFusion Australia Pty Ltd) and the SWA. For completeness, we applied one SWA on each arm (the arm most impaired from the stroke—
The SWAs were placed dorsal on the upper limb midway between the elbow and shoulder joint. The SWA consists of triaxial accelerometers that record movement and position, and sensors that measure heat flux and galvanic skin response. Data from the accelerometers and sensors are integrated and converted to EE in Metabolic Equivalent of Tasks (METs) per minute using proprietary algorithms of the manufacturer.
The metabolic cart measured VO2 continuously using breath-by-breath analyses, averaged over three breaths; the readout of the data was in five-second epochs. Calibration of the metabolic cart was performed according to the manufacturer’s operational instructions prior to testing. Gas calibration was performed against gas with a ratio of 16% O2 and 4% CO2 in Nitrogen. The ambient conditions were automatically measured by the unit. The participants were fitted with a facemask and a harness that carries the Oxycon units that allow telemetric transmission of data to a laptop.
Step-count was recorded by direct observation using a manual counter and by the SWA. The accelerometer output of the SWA is converted to step-counts using proprietary algorithms of the manufacturer. Sit-to-stand counts were also recorded by direct observation using a manual counter; a single sit-to-stand was counted when the participant stood up and sat back down.
The test protocol was terminated if a participant did not meet the following criteria assessed in a sitting position before the six-minute activity bouts: systolic blood pressure between 120 to 220 mm Hg (automatic blood pressure monitor OMRON, Australia), oxygen saturation > 92%, heart rate between 40 and 100 bpm (pulse oximeter, Oxycon Mobile Device, CareFusion Australia Pty Ltd), and temperature < 38.5°C (tympanic thermometer, Covidien, Medtronics, Australia). The test was also terminated if the participant requested stopping or felt unwell.
Purposeful sampling was used to recruit participants and we aimed to include stroke survivors who were able and not able to walk. We considered it feasible and practical to recruit 20 stroke survivors. We continued recruitment until 20 stroke survivors completed both activity bouts and had complete data sets including EE data measured by the metabolic cart and SWAunaffected.
After the test had been completed the data of the metabolic cart and SWAs were downloaded on to a computer. In this study we expressed EE in METs. The Oxycon expresses EE in VO2 in ml/kg/min which is automatically converted to METs/min, where 1 MET is equal to a VO2 of 3.5 ml/kg/min.
The output of the metabolic cart data is averaged over five-second epochs; we averaged the metabolic cart data for each minute to match the SWA data, which is collected in METs/min. EE under steady-state conditions was calculated by averaging the EE output over the last three minutes of the six-minute bouts for each participant for both the data acquired by the metabolic cart and the SWAs. We used descriptive statistics, calculated medians and interquartile ranges (IQR) for demographic data, anthropometric data, walking speed, step-counts, and sit-to-stand counts, and we calculated means and standard deviations for the EE of steady-state activity.
We confirmed that all EE data were normally distributed using the Shapiro-Wilk test. We calculated intraclass correlation coefficients (ICC) and Lin’s concordance correlation coefficients (CCC) to assess agreement between measures. Both ICC [
Additionally we employed reduced major axis (RMA) regression, which is appropriate in the setting of this study, where both measurement tools produce readings that are susceptible to measurement error [
To test our hypotheses regarding
Step-count measurements of the SWA utilise accelerometer data from the movement of the wearer’s arm. When the wearer’s arms are fixed on walking frames or supported by people walking with physical assistance, the recorded accelerometry data are likely to lack validity. We therefore excluded step-count data of participants who walked with a 4-wheel frame or required physical assistance. We tested our hypothesis regarding
We used the following ICC and CCC cutoff points to interpret the strength of agreement: less than 0.40:
We recruited 23 acute stroke survivors. Fourteen participants completed the walking protocol; one participant was unable to complete the second bout of walking due to fatigue. We excluded the data of another participant who completed less than 2.5 minutes of walking due to fatigue. Nine participants performed the sit-to-stand protocol; we had missing data for two participants due to machine failure and one participant was unable to perform the second bout of sit-to-stands due to fatigue. One participant had a bilateral stroke and performed the sit-to-stand protocol. The SWA data of both arms of this participant were regarded as EE of the affected arm (SWAaffected). We included the average of EE values of both arms for this participant in the analyses; hence the difference in numbers of SWA measures in the group that performed sit-to-stand (Figure
Flowchart of datasets for metabolic cart and SWA available for analyses.
We analysed the data of 22 participants. The median age was 78 (IQR 73–81) and all participants performed the test within the first seven days after stroke (Table
Participant characteristics.
All | Walking | Sit-to-stand | |
---|---|---|---|
Age, years | 78 (70 to 83) | 78 (70 to 85) | 78 (73 to 78) |
Male ( | 13 | 9 | 4 |
Time since stroke, days | 4 (2 to 6) | 4 (2 to 6) | 4 (3 to 5) |
Height, cm | 164.5 | 163.0 | 165.0 |
Body weight, kg | 73.0 | 72.2 | 76.7 |
Affected side, | 8/1 | 5/0 | 3/1 |
Stroke severity: | |||
Mild NIHSS < 8 ( | 18 | 11 | 7 |
Moderate NIHSS 8–16 ( | 4 | 2 | 2 |
Severe NIHSS > 16 ( | 0 | 0 | 0 |
All data is reported as medians and IQRs unless stated otherwise.
During both the 1st and 2nd bouts of walking we found
Energy expenditure of walking and sit-to-stands and agreement between the metabolic cart and
Outcome energy expenditure (METs) | |||||||
---|---|---|---|---|---|---|---|
Activity bout ( | Metabolic cart | | Mean difference (SD) | ICC (95% CI) | CCC ( | RMA slope | RMA intercept |
1st walk | 2.72 (0.54) | 3.65 (0.76) | −0.93 (0.66) | 0.02 (0.0 to 0.54) | 0.24 (−0.02 to 0.51) | 1.42 | −0.21 |
2nd walk | 2.78 (0.52) | 3.47 (0.49) | −0.69 (0.45) | 0.13 (0.0 to 0.63) | 0.31 (0.02 to 0.61 | 0.94 | 0.85 |
1st sit-to-stands | 2.35 (0.95) | 2.21 (0.94) | 0.47 (0.79) | 0.38 (0.0 to 0.88) | 0.37 (−0.33 to 1.00) | 1.04 | −0.57 |
2nd sit-to-stands | 2.49 (1.07) | 1.83 (1.22) | 1.08 (0.85) | 0.25 (0.0 to 0.88) | 0.34 (−0.19 to 0.86) | 0.64 | −0.14 |
Energy expenditure is reported as mean (SD);
Energy expenditure walking (1st): metabolic cart and SWAunaffected
Energy expenditure walking (2nd): metabolic cart and SWAunaffected
We found
We first assessed the test-retest reliability of our gold standard, the metabolic cart, and found excellent agreement between the EE measured during the 1st and the 2nd bout of walking (ICC = 0.96, 95% CI 0.87 to 0.99; CCC = 0.96, 95% CI 0.90 to 1.00,
However, this was not the case for EE of walking measured using the SWAunaffected, which showed
SWAunaffected: energy expenditure between 1st and 2nd bout of walking.
The metabolic cart was reliable between bouts of sit-to-stands, similar to our finding for walking, with
Agreement was
Energy expenditure SWAunaffected: 1st and 2nd bout of sit-to-stands.
We excluded step-count data of five participants who walked with a walking frame or needed physical assistance; the analyses included data of 8 participants. The average number of step-counts measured by the SWAunaffected was substantially lower (>190 steps) than the average step-counts measured via direct observation (Table
Step-counts and agreement between observed count and
Outcome step-counts | |||||||
---|---|---|---|---|---|---|---|
Activity bout ( | Observed counts | | Mean difference (SD) | ICC (95% CI) | CCC (95% CI) | RMA slope | RMA intercept |
1st walk ( | 592 (87) | 356 (219) | −235 (173) | 0.0 (0.0 to 0.66) | 0.22 (−0.04 to 0.48) | 2.52 | −1133 |
2nd walk ( | 602 (87) | 411 (207) | −191 (150) | 0.16 (0.0 to 0.74) | 0.30 (0.01 to 0.59 | 2.39 | −1026 |
All data is reported as mean (SD) unless stated otherwise;
The SWAunaffected showed
We set out to determine if the SWA wearable device could provide a valid measure of EE during physical activity in acute stroke patients. Our results indicated that the SWA worn on the unaffected arm did not accurately measure EE during a bout of physical activity; rather, it seemed to overestimate EE compared to the metabolic cart during walking and underestimate EE during sit-to-stands. Our findings regarding EE during walking are in contrast with the findings in the Manns and Haennel (2012) study. Their study, which included 12 chronic stroke survivors, found
We found that the SWA greatly underestimated step-counts by approximately 300 steps on average within two weeks of stroke onset. This difference was larger than the difference found in the Manns and Haennel study in which step-counts measured by the SWA were compared to step-counts measured by the StepWatch Activity Monitor (SAM) in stroke survivors > 6 months after stroke [
It is however important that our results are interpreted with caution; no formal calculations were performed to predetermine sample size and the sample size of this study was small. On the other hand we did compare the data of the SWA to the metabolic cart, which is regarded as a gold standard, and showed that in our sample it was a reliable measure of EE of activity and we are confident that the metabolic cart is a true measure of EE. Including a broad variety of stroke survivors in a clinical study like this is challenging. We were able to include ambulatory and nonambulatory stroke survivors within 14 days of stroke onset. Almost all of our participants, except one, were able to reach steady-state (22/23), regardless of their ability to ambulate. Exercising under steady-state conditions is one of the methods to improve cardiorespiratory fitness and we showed that some stroke survivors have the potential to start performing cardiorespiratory exercise early after stroke. It is important, however, that all of the included stroke survivors had mild to moderate stroke severity.
The differences between SWA and metabolic cart were systematic and small. During walking, EE was overestimated by less than 1.0 MET and during sit-to-stands it was underestimated by less than 1.1 METs. Considering that the range of activity intensity is 3 METs, that is, light intensity is <3 METs and moderate intensity is 3–6 METs, a difference of less than 1.1 METs is relatively small. It is a concern, however, that the direction of the estimation error was not consistent across the two activities we tested. Therapy session in stroke rehabilitation can consist of different exercises including walking and sit-to-stand amongst other activities. Furthermore the test-retest reliability of the SWAunaffected measuring EE showed mixed results regarding agreement, but most importantly the RMAs for both walking and sit-to-stands showed that agreement changed when levels of EE change. This suggests that SWA EE output during therapy sessions with mixed activities would be highly variable, and using the SWA would not be a reliable method to track EE over time.
Based on the results of our study the SWA does not accurately measure EE and therefore should be used with caution when measuring EE during activities early after stroke.
The authors report no conflicts of interest.
The first author (Sharon Flora Kramer) is funded by the Australian Government through an Australian Post-Graduate Award (2014–2017). The second author (Liam Johnson) was supported to conduct this research under Commonwealth Collaborative Research Network funding to Victoria University (2014–2017). The third author (Julie Bernhardt) is funded by an NHMRC Senior Research Fellowship Grant (1058635, 2014–2018). The Florey Institute for Neuroscience and Mental Health acknowledges the support of the Victorian Government via the Operational Infrastructure Support Scheme.
(1) EE and agreement between metabolic cart and SWAaffected. (2) Step-count agreement between observed counts and SWAaffected.