Validity of Estimated Results from a Wearable Device for the Tests Time Up and Go and Sit to Stand in Young Adults and in People with Chronic Diseases.

BACKGROUND: Health care professionals need a valid tool to assess the physical ability of patients with chronic diseases. We aimed to assess the validity of the results of physical fitness tests estimated by a wrist wearable device in young adults and chronic disease people. METHODS: Participants wore a sensor placed on their wrist and performed two physical fitness tests (sit to stand (STS) and time up and go (TUG)). We checked the concordance of sensor-estimated results using Bland-Altman analysis, root-mean-square error, and intraclass coefficient of correlation (ICC). RESULTS: In total, 31 young adults (groups A; median age = 25 ± 5 years) and 14 people with chronic diseases (groups B; median age = 70 ± 15 years) were included. Concordance was high for both STS (ICCA = 0.95, and ICCB = 0.90), and TUG (ICCA = 0.75, ICCB = 0.98). The best estimations were given by the sensor during STS tests in young adults (mean bias = 0.19 ± 2.69; p = 0.12) and chronic disease people (mean bias = -0.14 ± 3.09 s; p = 0.24). The sensor provided the largest estimation errors over 2 s during the TUG test in young adults. CONCLUSION: This study showed that the results provided by the sensor are consistent with those of the gold standard during STS and TUG in both healthy youth and people with chronic diseases.

The Functional Independence of Patients With Stroke Sequelae: How Important Is the Speed, Oxygen Consumption, and Energy Cost of Walking?

OBJECTIVE: To evaluate the association between self-selected walking speed (Sfree), oxygen consumption at Sfree (Vo2free), the oxygen cost of walking (Cw) at Sfree, and mobility independence and independence for activities of daily living in individuals poststroke. DESIGN: Cross-sectional study. SETTING: Hospital. PARTICIPANTS: Individuals with stroke who were able to walk without human assistance were included. We included 90 individuals (N=90; mean age, 63.5±14.0y). INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Cw was captured during walking from measurements of Sfree and Vo2free. We assessed mobility independence based on the modified Functional Ambulation Classification (mFAC) and independence in activities of daily living by the Barthel Index (BI). Multiple linear regression analyses were performed to evaluate the independence of Cw, Vo2free, and Sfree from the determination of BI and mFAC among the various characteristics of the population (age, stroke delay, body mass index, motor function, spasticity). RESULTS: We reported Cw=0.36 mL/kg/m (interquartile range [IQR]=0.28 mL/kg/m), Sfree=0.60±0.32 m/s, Vo2free=11.2 mL/kg/min (IQR=1.8 mL/kg/min). The multiple linear regression analyses showed that Cw and Sfree were independently associated with the BI (P<.01) and the mFAC (P<.01) scores. Vo2free was not found to be an explanatory variable of functional independence (P>.05). CONCLUSIONS: Cw was independently associated with functional independence. This association appears to be primarily determined by Sfree and not Vo2free, underscoring the importance of evaluating and acting on Sfree to improve the functional independence of individuals with stroke.

Reliability of ActiGraph GT3X+ placement location in the estimation of energy expenditure during moderate and high-intensity physical activities in young and older adults.

WHO defines physical activity (PA) as any bodily movement produced by skeletal muscles that requires energy expenditure (EE). The purpose of this study was to compare the EE estimations by ActiGraph GT3X+ with a gold standard measurement, the portable gas analyser in a set of 3 different PAs. This cross-sectional study involved 56 participants, age range (years, [min, max]: young people [20, 33], older adults [65, 83]). Participants completed a single session of three experimental PAs including biking, treadmill walking, and treadmill running. Each participant wore five GT3X+ triaxial accelerometers and a portable gas analyser used as the gold standard measurement. The GT3X+ were placed on the wrists, the waist (centred at the pelvis), and the ankles. ActiGraph GT3X+ and MetaMax3B records were investigated through intraclass correlation coefficient. Magnitude of measurement error was estimated using Effect Size. The GT3X+ wrist and GT3X+ waist underestimated EE regardless of the PA type. The GT3X+ ankles strongly overestimated EE during biking (mean bias = 489 ± 392%) and walking (mean bias = 106 ± 58%), while it underestimated EE during running (mean bias = -47 ± 27%). The ActiGraph GT3X+ does not provide accurate EE estimates across a range of placement locations during moderate and high-intensity PA.

Social Participation and Physical Activity Incentive at Home in Stroke Survivor: Contribution of Technologies.

Increased physical activity has been demonstrated as a relevant treatment after a stroke, with positive effects on impairment recovery, activity limitation, social participation and quality of life. Furthermore, PA is now recommended as part of the stroke recovery pathway, starting during inpatient care and extending through rehabilitation and community integration. The purpose of this presentation is to describe how current technologies may facilitate a continuity of care for stroke survivors. We present a synthesis of 8 studies that we have conducted to date to assess and monitor the activity level of post-stroke patients at home. The results of these studies show that home rehabilitation of post-stroke patients requires the use of individualized monitoring criteria to optimize patient care. To encourage the patient to increase his level of moderate physical activity and reduce his sedentary time, it would be recommended to propose a regularly monitored and structured program.

Effect of Individualized Coaching at Home on Quality of Life in Subacute Stroke Patients.

Background: Stroke causes psychological disorders and cognitive impairments that affect activities of daily living and quality of life. Physical activity (PA) in stroke recovery is beneficial. The benefits of PA on quality of life after stroke are less documented. The aim of the study was to evaluate the effect of a home-based PA incentive program at home in post-stroke patients in the subacute phase on quality of life. Methods: This is a prospective, randomized, single-blind, and monocentric clinical trial. Eighty-three patients were randomly assigned to either an experimental group (EG; n = 42) or to a control group (CG; n = 41). The experimental group followed a home-based PA incentive program for 6 months. Three incentive methods were used: daily monitoring with an accelerometer, weekly telephone calls, and home visits every three weeks. Patients were evaluated before intervention (T0) and after intervention (T1) at 6 months. The control group was a non-intervention group receiving usual care. The outcome was the quality of life with the EuroQol EQ-5D-5L evaluated at baseline and 6 months post-intervention. Results: The mean age was 62.2 years ± 13.6 with a post-stroke time of 77.9 ± 45.1 days. The mean values of the utility index (EQ-5D-5L) in the control group and experimental group at T1 were 0.721 ± 0.207 and 0.808 ± 0.193, respectively (p = 0.02). Discussion: Our study shows a significant difference in the Global QOL index (EQ-5D-5L) between the two groups of subacute stroke patients after 6 months of the individualized coaching program, which combined home visits and weekly telephone calls.

Perceived exertion and energy expenditure during physical activities in healthy young people and older adults.

AIM: To test the validity of Borg's 6-20 rating of perceived exertion scale in assessing the exertion intensity over a multi-activity session in young and older adults.Materials and methods: This cross-sectional study included 56 healthy participants. All participants underwent a single session of activities including working on a computer, treadmill walking, biking, and treadmill running. RESULTS: Results showed a non-significant correlation between the overall perceived exertion and energy expenditure in young people (Rho=-0.05, p=0.75) and in older adults (Rho=-0.05, p=0.78) for the whole session. However, results showed that older adults perceived significantly higher exertion compared to young people while working on a computer, walking and running, whereas they presented lower energy expenditure while resting and working on a computer. CONCLUSIONS: Combining the perceived exertion method with other commonly used methods to estimate exercise intensity would be recommended for older adults.

Comparison of Energy Expenditure Assessed Using Wrist- and Hip-Worn ActiGraph GT3X in Free-Living Conditions in Young and Older Adults.

The World Health Organization has presented their recommendations for energy expenditure to improve public health. Activity trackers do represent a modern solution for measuring physical activity, particularly in terms of steps/day and energy expended in physical activity (active energy expenditure). According to the manufacturer's instructions, these activity trackers can be placed on different body locations, mostly at the wrist and the hip, in an undifferentiated manner. The objective of this study was to compare the absolute error rate of active energy expenditure measured by a wrist-worn and hip-worn ActiGraph GT3X+ over a 24-h period in free-living conditions in young and older adults. Over the period of a 24-h period, 22 young adults and 22 older adults were asked to wear two ActiGraph GT3X+ at two different body locations recommended by the manufacturer, namely one around the wrist and one above the hip. Freedson algorithm was applied for data analysis. For both groups, the absolute error rate tended to decrease from 1,252 to 43% for older adults and from 408 to 46% for young participants with higher energy expenditure. Interestingly, for both young and older adults, the wrist-worn ActiGraph provided a significantly higher values of active energy expenditure (943 ± 264 cal/min) than the hip-worn (288 ± 181 cal/min). Taken together, these results suggest that caution is needed when using active energy expenditure as an activity tracker-based metric to quantify physical activity.

Intensity level and on-court role of wheelchair rugby players during competition.

BACKGROUND: This study aims at quantifying the level of physical activity of wheelchair rugby players during matches in order to compare defensives players (DP) and offensives players (OP) profiles. Our hypothesis is that OP would present a higher energy expenditure and intensity level values during matches than DP, due to specific actions according to the on-court role. METHODS: Fifty-two players, including 24 DP and 28 OP (mean age of 34±9 years), from eight French teams involved in the national elite championship and in the French national cup, participated. The seven wheelchair rugby players' classes were differentiated from 0.5 points (most severe deficiencies) to 3.5 points (less severe deficiencies). DP and OP were regrouped from 0.5 to 1.5 points and from 2 to 3.5 points, respectively. Energy expenditure (in kcal), intensity level (in metabolic equivalent of task) and physical activity time (in minutes) of wheelchair rugby players during competition were evaluated. RESULTS: Statistical analysis between DP and OP showed a significant difference in vigorous activity time with a higher vigorous activity time for OP than DP; P<0.007), associated with higher mean intensity level for OP vs. DP (4.3±1.0 METs vs. 3.8±0.9 METs respectively; P=0.049). No significant differences between DP and OP were found for active energy expenditure (385±158 kcal vs. 446±199 kcal, for DP and OP respectively) during matches. CONCLUSIONS: This study highlighted significantly different wheelchair rugby player profiles between competing DP and OP for the time spent in high intensity and intensity level. Offensive players were more explosive during a match than DP; therefore, training should be adapted accordingly to their roles.

Effort Assessment of Stroke Patients in Physiotherapy Session by Accelerometry and Perceived Exertion Score: Preliminary Study.

OBJECTIVE: To determine whether post-stroke patient's perceived exertion correlates with effort intensity score as measured by a wearable sensor and to assess whether estimates of perceived exertion are correlated to the cerebral hemisphere involved in the stroke. METHODS: We evaluated the effort intensity score during physiotherapy sessions using a wearable sensor and subjects assessed their perceived exertion using the modified Borg CR10 Scale. RESULTS: Fifty-seven subacute stroke patients participated in the study. The correlation between perceived exertion rating and measured effort intensity was insignificant-mean (r=-0.04, p=0.78) and peak (r=-0.05, p=0.70). However, there was a significant difference (p<0.02) in the perceived exertion ratings depending on the cerebral hemisphere where the stroke occurred. Patients with left-hand side lesions rated their perceived exertion as 4.5 (min-max, 0.5-8), whereas patients with right-hand side lesions rated their perceived exertion as 5.0 (2-8). CONCLUSION: While there was an insignificant correlation between perceived exertion and effort intensity measured by a wearable sensor, a consistent variations in perceived exertion estimates according to the side of the cerebral lesion was identified and established.

Comparison of Step Count Assessed Using Wrist- and Hip-Worn Actigraph GT3X in Free-Living Conditions in Young and Older Adults.

Background: Walking represents a major component of physical activity (PA), and its restriction could degrade autonomy and quality of life. An important objective for preventive and/or rehabilitative strategies to improve balance and gait in normal and pathological aging conditions is to focus on physical activity. Activity monitors have recently been getting increasingly popular and represent a modern solution to measure-and communicate-PA notably in terms of steps/day. These activity monitors are well-suited for various populations as they can be worn on a variety of locations on the body, including the wrist and the hip (i.e., the two most common locations), in an undifferentiated way according to the manufacturer's instruction. The aim of this study was hence to verify potential differences in step count (SC) by comparing this parameter assessed using wrist- and hip-worn activity trackers over a 24-h period in free-living conditions in young and older adults. Methods: Young adults (n = 22) and older adults (n = 22) voluntarily participated in this study. They were required to wear two commercially-available Actigraph GT3X+ activity monitors simultaneously at two locations recommended by the manufacturer, i.e., one positioned around the wrist and one above the hip, over a 24-h period in free-living conditions. The manufacturer's software was used to obtain estimates of the SC. Results: For both groups, the wrist-worn activity tracker provided significantly higher SC than the hip-worn activity tracker did. For both placements on the body, older adults exhibited significantly lower SC than young adults. Interestingly, for both young and older participants, the difference between both measurements tended to decrease for longer distances. Conclusion: The different estimations of the step count provided by the comparison between two identical Actigraph GT3x on the wrist or the hip during the 24-h observation period in free-living conditions in young and older adults strongly suggests that caution is needed when using total step per day values as an outcome to quantify walking behavior. Probably we can suggest the same caution across implementation of different activity Tracker.

Compendium of Physical Activities Strongly Underestimates the Oxygen Cost During Activities of Daily Living in Stroke Patients.

OBJECTIVE: The aim of the study was to measure the metabolic equivalent task when performing physical activities of daily living in poststroke individuals. DESIGN: Poststroke individuals who were able to walk without human assistance were recruited and asked to perform the following activities of daily living: washing dishes (activity code: 05041 in Ainsworth's compendium), walking at a slow pace of less than 2 mph (activity code: 17151), climbing stairs (activity code: 17133), and walking down stairs (activity code: 17070). The metabolic equivalent task was measured along these activities using a portable breath gas exchange analyzer. The measured values were then compared with Ainsworth's compendium. RESULTS: Thirty-five participants were included (mean [SD] age = 64.3 [14.3] yrs). The mean (SD) resting metabolic rate was 3.08 (0.79) ml O2 kg(-1) min(-1). The metabolic equivalent task values were significantly higher than the compendium values: metabolic equivalent task washing dishes = 2.57 (0.96) versus 1.80 for compendium; metabolic equivalent task walking = 4.16 (0.93) versus 2.00 for compendium; metabolic equivalent task climbing stairs = 5.90 (1.43) versus 4.00 for compendium; metabolic equivalent task walking down stairs = 3.29 (0.48) versus 3.50 for compendium. CONCLUSIONS: The metabolic equivalent tasks during activities were higher than Ainsworth's compendium. Stroke individuals are thus exposed to high oxygen requirements when performing activities of daily living, which could have a strong impact on their ability to perform these activities in real life.

Rating of perceived exertion with Borg scale in stroke over two common activities of the daily living.

Background The Borg Scale for the rating of perceived exertion (RPE) is recommended to measure the intensity of physical exercise during stroke rehabilitation, but its reliability in activities of daily living is not explored. Objective To evaluate the correlation between the RPE using the Borg Scale (6-20) and the intensity of effort as measured by the Total Energy Expenditure per minute (TEE.min-1) in a post-stroke population for two tasks: walking at spontaneous comfortable speed and walking up and down stairs. Methods A cross-sectional study has been conducted. Any post-stroke subjects able to walk without being helped were recruited. Subjects were asked to walk at their spontaneous comfortable walking speed for 6 min and then to walk up and down stairs with a portable gas analyzer to measure the TEE.min-1. The RPE was evaluated by the Borg scale (6-20). The correlation between the RPE and the TEE.min-1 for each subject's walking task and stairs task was calculated with the Pearson coefficient. Results Twenty subjects were included. TEE.min-1 averaged at 5.6 (±1.2 kcal.min-1) for the walking task and 9.58 (±4.3 kcal.min-1) for the stairs task. The median RPE was 11 (min 6; max 15) for the walking task and 11 (min 6; max 16) for the stairs task. The correlation coefficient between the RPE and TEE.min-1 was r = 0.12 (p = 0.25). Conclusion Our work has not determined a correlation between the RPE and TEE.min-1 for two common activities of daily living in post-stroke subjects.

Can energy expenditure be accurately assessed using accelerometry-based wearable motion detectors for physical activity monitoring in post-stroke patients in the subacute phase?

Background In the subacute stroke phase, the monitoring of ambulatory activity and activities of daily life with wearable sensors may have relevant clinical applications. Do current commercially available wearable activity trackers allow us to objectively assess the energy expenditure of these activities? The objective of the present study was to compare the energy expenditure evaluated by indirect calorimetry during the course of a scenario consisting of everyday activities while estimating the energy expenditure using several commercialised wearable sensors in post-stroke patients (less than six months since stroke). Method Twenty-four patients (age 68.2 ± 13.9; post-stroke delay 34 ± 25 days) voluntarily participated in this study. Each patient underwent a scenario of various everyday tasks (transfer, walking, etc.). During the implementation, patients wore 14 wearable sensors (Armband, Actigraph GT3X, Actical, pedometer) to obtain an estimate of the energy expenditure. The actual energy expenditure was concurrently determined by indirect calorimetry. Results Except for the Armband worn on the non-plegic side, the results of our study show a significant difference between the energy expenditure values estimated by the various sensors and the actual energy expenditure when the scenario is considered as a whole. Conclusion The present results suggest that, for a series of everyday tasks, the wearable sensors underestimate the actual energy expenditure values in post-stroke patients in the subacute phase and are therefore not accurate. Several factors are likely to confound the results: types of activity, prediction equations, the position of the sensor and the hemiplegia side.

Physical Activity Level Among Stroke Patients Hospitalized in a Rehabilitation Unit.

BACKGROUND: The current literature contains little information about the level of physical activity of hospitalized patients who have had a stroke. Improving knowledge in the area could help optimize rehabilitation. OBJECTIVES: To determine the level of physical activity of hospitalized patients who have had a stroke to discover if they achieved the recommended 30 minutes of physical activity per day (equivalent to 142 kcal) during sessions of 10 consecutive minutes. SETTING: Physical and Rehabilitation Medicine Unit of the Jean Rebeyrol Hospital, Limoges, France. PARTICIPANTS: All patients (N = 88) who had sustained a stroke within the previous 6 months were included over a period of 7 months. MAIN OUTCOME MEASURES: The duration of physical activity and related energy expenditure were estimated using a SenseWear armband (BodyMedia [Jawbone]). Subjects wore the sensor on the nonparetic arm for 2 consecutive days from 9 am to 4:30 pm, corresponding to the period spent daily on rehabilitation. The Fisher simple correlation test and Mann-Whitney nonparametric test were performed. RESULTS: A total of 88 patients aged 66 ± 17 years with a mean poststroke period of 43 ± 34 days and a mean Barthel Index of 61 ± 25/100 were enrolled in the study. Between 9 am and 4:30 pm, patients took part in an average of 23 ± 30 minutes of physical activity (equivalent to 91 ± 122 kcal). Correlations were found between physical activity time in the hospital and physical activity before the stroke occurred (r = 0.345, P < .0001), the Barthel Index (r = 0.284, P = .0002), body mass index (r = -0.440, P < .0001), and time to hospital release (r = -0.183, P = .0194). CONCLUSION: It was found that 62% of patients did not achieve the recommended amount of physical activity. Sessions dedicated to physical activity could motivate patients who have had a stroke and help them meet recommendations before leaving the rehabilitation unit.