SenseWear Pro Armband Research Articles

Sleep and physical activity: a cross-sectional objective profile of people with rheumatoid arthritis.

Regular physical activity (PA) is important for people with rheumatoid arthritis (RA). Poor sleep is a common complaint among people with RA, which may have an influence on their PA levels. There is a lack of objective information regarding total sleep time (TST) and PA duration in this population. A cross-sectional study design was used. SenseWear Pro3 Armband(R)TM is used to measure TST and total PA duration. Four valid days, with 95% wear time necessary for inclusion in final results. Disease activity and function were measured using the DAS-28, HAQ and VAS. Data analysis carried out using SPSS v22. Seventy-five (75) participants completed monitoring period, with 51 (68%) meeting modified PA duration guidelines. Data with 95% wear time over a minimum of 4days were available for 32 recorded participants, with a mean TST of 5.7 (SD_1.11) hours per night and a median 1.25 (IQR_1.88) hours of daily PA. TST had a positive significant relationship with PA (p = 0.018); PA demonstrated a negative significant relationship with functional limitations (p = 0.009) and correlated with lower CRP levels; CRP levels had in turn a significant relationship to global health (p = 0.034). Total sleep time was low for people with RA. People with RA who are more physically active have longer TST. These findings provide an objective profile of TST and PA duration in people with RA and suggest a relationship between increased PA duration and longer TST. Further research is needed to confirm these novel findings.

Sedentary behaviour, physical activity, cardiorespiratory fitness and cardiometabolic risk in psychosis: The PsychiActive project

This study aimed to explore the possible independent associations of sedentary behaviour (SB), physical activity (PA), and cardiorespiratory fitness (CRF) with clustered (CCRS) and individual cardiometabolic risk (waist circumference [waist], systolic/diastolic blood pressure, triglycerides, high-density lipoprotein-cholesterol, and fasting blood glucose) in patients with psychosis. In 43 outpatients with psychosis (mean age±SD: 42.3±8.5years, 86% men), SB and light, moderate-to-vigorous, and total PA were measured with the SenseWear Pro3 Armband, and CRF with the 6-minute walking test. Multiple linear regression models adjusted for multiple confounders were applied. High SB, low PA and low CRF levels were associated with an unfavourable cardiometabolic risk profile (increased presence of metabolic syndrome and number of cardiometabolic abnormalities, as well as worse values and elevated presence of abnormalities for all individual cardiometabolic risk factors). SB was associated with CCRS, number of cardiometabolic abnormalities, waist, and fasting blood glucose (all p<0.05). After adjusting for PA and CRF, waist and fasting blood glucose remained significant. Light PA was associated with waist, moderate-to-vigorous PA with CCRS, and total PA with CCRS and waist (all p<0.05). These results became non-significant after adjusting for SB and CRF. CRF was associated with CCRS, waist, and systolic blood pressure (all p<0.05). The associations with CCRS and waist remained significant after adjusting for SB and PA. Together, these results suggest the importance of considering SB and CRF, regardless PA, in the prevention and treatment of cardiometabolic disorders among patients with psychosis.

Insulin-Associated Weight Gain in Type 2 Diabetes Is Associated With Increases in Sedentary Behavior

The insulin therapy–mediated weight gain in patients with type 2 diabetes (T2D) may relate to altered physical activity patterns (1). In this study, we examined the hypothesis that initiation of insulin therapy would be associated with an increase in sedentary behavior (i.e., sitting time) and lower low-, moderate-, and vigorous-intensity physical activity, which would subsequently relate to weight gain. We included 40 T2D patients who started insulin therapy and followed these patients for a period of 12 months. Patients were randomly selected from one university hospital, three nonuniversity teaching hospitals, and four primary care practices. The decision to start insulin treatment was at the discretion of the responsible physician and was always based on failure of glycemic control while on oral glucose-lowering agents and diet. Measurements were performed before and 6 months and 12 months after initiation of insulin therapy. We examined body weight, waist-to-hip circumference, fasting glucose, and HbA1c using standardized procedures. Free-living daytime physical activity was objectively measured (SenseWear Pro3 Armband, BodyMedia, Pittsburgh, PA) (2). We examined 1 ) time (hours/day) spent in sitting ( 3.0 METs); 2 ) steps per day; and 3 ) sit-to-stand maneuvers (transition from …

Physiological responses, hitting accuracy and step count of a tennis drill in function of court surface: a randomised cross-over design

The present study examined physiological responses, hitting accuracy and step count during a tennis drill on both clay and hard courts. Twenty elite tennis players performed two identical ball machine led drills. Maximum and mean heart rate, energy expenditure, playing intensity (MET values) and step count were measured using the Polar RCX-5 device and the SenseWear Pro3 Armband. Hitting accuracy was calculated as the percentage of balls that were hit within marked zones. There was no significant difference and a trivial effect size between clay and hard court for maximal and mean heart rate, MET values and hitting accuracy. There was a small effect size and a trend towards a significantly higher energy expenditure on clay court. Step count showed a large effect size and was significantly lower on clay court. The correlations between step count, hitting accuracy and the physiological responses indicated little difference between clay and hard court. There was a significant moderate positive correlation between step count and hitting accuracy on hard court only. Despite a significant difference in step count, this study did not find a significant difference in physiological responses and hitting accuracy between clay and hard court during a ball machine led drill.

Energy expenditure in office workers with identified health risks

Objective. To measure the daily energy expenditure in employees previously identified as having ≥2 risk factors for chronic disease, and to identify potential risk-reducing interventions for implementation within or outside the workplace. Design. A total of 122 employees with ≥2 risk factors for chronic disease identified in an in-house screening programme were invited to participate in a 6-month health management programme. Physical assessments included anthropometric measurements, blood pressure, blood glucose and cholesterol estimations, and bicycle ergometry. Participants were invited to wear a ‘metabolic armband' (Body Media SenseWear Pro Armband®) for 6 days. Metabolic measures included active and total energy expenditure (AEE, TEE), and daily MET levels (metabolic equivalents expressed as kcal/kg/hour). Differences were explored between genders, and relationships sought between energy expenditure, lifestyle and anthropometric data. Setting. A corporate working environment. All measures and assessments were carried out in the in-house fitness facility. Interventions. The health management programme involved physical assessments and personalised weight and activity management plans. Main outcome measures. TEE per day, duration and quantification of physical activity, METS, AEE, number of steps per day and body position recording. Relationships were explored between the latter and anthropometric measures such as body mass index (BMI) and percentage body fat. Result. Altogether 53 (43%) of the eligible subjects volunteered for the 6-month programme and 49 enrolled for the metabolic armband study. The males were more active than the females, but both had BMI and body fat estimates that categorised them as overweight to obese. METS and AEE were positively correlated with duration of exercise rather than intensity, and negatively correlated with BMI. In a stepwise regression analysis for the total group 77% of the variance in MET levels was accounted for by per cent body fat and steps per day. Multivariate analysis by gender (with per cent body fat as the dependent variable) suggested that males would have to increase the duration of vigorous exercise in order to reduce body fat, while females would benefit from sitting less, sleeping more, and increasing the duration of moderate exercise. Conclusion and clinical relevance. In a self-selected sample involving motivated individuals, the SenseWear® armband provided information that would be useful in directing further research in women, focusing on sleeping pattern and moderately increasing activity levels. South African Journal of Sports Medicine Vol. 20 (2) 2008: pp. 40-43

Reliability of commercially available sleep and activity trackers with manual switch-to-sleep mode activation in free-living healthy individuals

IntroductionWearable health devices have become trendy among consumers, but it is not known whether they accurately measure sleep and physical activity parameters. To address this question, we have studied the measured data of two consumer-level activity monitors (Up Move Jawbone® (U) and Withings Pulse 02® (W)) and compared it with reference methods for sleep and activity recordings, namely the Bodymedia SenseWear Pro Armband® actigraph (SWA) and home-polysomnography (H-PSG). MethodsTwenty healthy patients were assessed at home, during sleep, with the four devices. An additional 24-h period of recording was then planned during which they wore the 2 trackers and the SWA. Physical activity and sleep parameters obtained with the 4 devices were analyzed. ResultsSignificant correlations with H-PSG were obtained for total sleep time (TST) for all the devices: r=0.48 for W (p=0.04), r=0.63 for U (p=0.002), r=0.7 for SWA (p=0.0003). The best coefficient was obtained with SWA. Significant correlations were also obtained for time in bed (TIB) for U and SWA vs PSG (r=0.79 and r=0.76, p<0.0001 for both) but not for W (r=0.45, p=0.07). No significant correlations were obtained for deep sleep, light sleep, and sleep efficiency (SE) measurements with W, U and SWA. Sleep latency (SL) correlated with H-PSG only when measured against SWA (r=0.5, p=0.02).Physical activity assessment revealed significant correlations for U and W with SWA for step count (both r=0.95 and p<0.0001) and active energy expenditure (EE) (r=0.65 and 0.54; p=0.0006 and p<0.0001). Total EE was also correctly estimated (r=0.75 and 0.52; p<0.0001 and p=0.001). ConclusionSleep and activity monitors are only able to produce a limited set of reliable measurements, such as TST, step count, and active EE, with a preference for U which performs globally better. Despite the manual activation to sleep mode, U and W were not suitable for giving correct data such as sleep architecture, SE, and SL. In the future, to enhance accuracy of such monitors, researchers and providers have to collaborate to write algorithms based reliably on sleep physiology. It could avoid misleading the consumer.

Temporal and bidirectional associations between physical activity and sleep in primary school-aged children

The directionality of the relationship between children's physical activity and sleep is unclear. This study examined the temporal and bidirectional associations between objectively measured physical activity, energy expenditure, and sleep in primary school-aged children. A subgroup of children (n = 65, aged 8-11 years) from the Fitness, Activity and Skills Testing Study conducted in Melbourne, Australia, had their sleep and physical activity assessed using the SenseWear Pro Armband for 8 consecutive days. Outcome measures included time spent in light-intensity physical activiy (LPA), moderate- to vigorous-intensity physical activity (MVPA), activity energy expenditure (AEE), time in bed, total sleep time, and sleep efficiency. Multilevel analyses were conducted using generalized linear latent mixed models to determine whether physical activity on 1 day was associated with sleep outcomes that night, and whether sleep during 1 night was associated with physical activity the following day. No significant associations were observed between time in bed, total sleep time, and sleep efficiency with LPA, MVPA, and AEE in either direction. This study found no temporal or bidirectional associations between objectively measured physical activity, AEE, and sleep. Future research is needed to understand other sleep dimensions that may impact on or be influenced by physical activity to provide potential intervention targets to improve these outcomes.

Evaluation of a non-invasive multisensor accelerometer for calculating energy expenditure in ventilated intensive care patients compared to indirect calorimetry and predictive equations.

Continuous measurement of resting energy expenditure (REE) in critically ill patients remains challenging but is required to prevent malnutrition. SenseWear Pro 3 Armband (SWA) is a research grade accelerometer for assessment of REE with the advantage of easy handling. In a prospective study we compared SWA with indirect calorimetry (IC) and predictive equations in critically ill, ventilated patients. REE was measured by SWA, IC and calculated by predictive formulas. Potential confounding factors that influence REE were also recorded. Results of SenseWear Armband and indirect calorimetry were compared using the Bland-Altman method. 34 ICU patients were investigated. SWA underestimated resting energy expenditure compared to IC with a mean bias of ΔREE=-253.6±333.2kcal, equivalent to -11.7% (p=0.025). This underestimation was seen in both, medical (-14.9%) and surgical (-12.9%) patients and the bias was greater in patients with fever (-19.0%), tachycardia (-18.7%) or tachypnea (-26.2%). Differences were also noted when SWA was compared to predictive formulas. At present, SWA cannot be regarded as an alternative to indirect calorimetry. Individual measurements are often inaccurate and should be used with caution until improved algorithms, based on the results of this study, have been implemented.

Day-to-day relations between stress and sleep and the mediating role of perseverative cognition

ObjectiveThe goals of this longitudinal diary-based study were to shed light on the day-level relationship between stress and subsequent sleep, and to examine whether perseverative cognition is a mediating factor in this relation. MethodsA total of 44 Dutch PhD students were followed during a two-month period, from one month before their public thesis defense (ie, a stressful life event), until one month thereafter. Participants completed short evening and morning questionnaires on eight occasions (in anticipation of and following the defense), including questions about day-level stress, sleep quality, and perseverative cognition. Objective sleep parameters were collected with the SenseWear Pro Armband. ResultsMultilevel analysis was used to analyze daily observations nested within individuals. Analyses revealed that day-level stress was not directly related to subsequent subjective sleep indicators or to subsequent objective sleep indicators. Day-level stress was significantly associated with day-level perseverative cognition, and daily variations in perseverative cognition were significantly related to several day-level objective sleep parameters (sleep efficiency, marginally to number of awakenings, and wake after sleep onset), and to several day-level subjective sleep parameters (sleep quality, number of awakenings, wake after sleep onset). Finally, mediation analyses using path analysis suggested that, on the day level, perseverative cognition functions as a mediator between stress and several sleep parameters, namely, subjective sleep quality, objective sleep efficiency, and subjective wake after sleep onset. ConclusionPerseverative cognition is a promising explanatory mechanism linking day-level stress to subjective and objective measures of sleep.

An Observational Study of Parental Practices on Children’s Physical Activity

Self-reported parental practices have been shown to be positively associated with child physical activity (PA). However, there is little research examining parental practices on children’s PA in a controlled laboratory setting. PURPOSE: The purpose was to examine observed parental practices and children’s objective PA in a controlled laboratory setting (racquetball court). METHODS: Participants included parent and child dyads (n=40) with children aged 8-13 years (male = 58%; white = 68%; low SES = 43%; normal weight = 73%). Parent and child dyads participated in activities for 30 minutes in a controlled laboratory setting. Active activities included: soccer, basketball, floor hockey, jump rope, stationary bike, elliptical, and step aerobics video. Sedentary activities included: TV, puzzles, magazines, crayons and coloring books, and Legos. Observations were made every 30 seconds; observing 20 seconds then recording 10 seconds using a modified SOFIT observation form (60 observations per parent-child dyad). Observations assessed parental practices, including encouragement and discouragement of PA and sedentary activity (SA). Physical activity was assessed by the SenseWear Pro Armband. Paired t-tests were used to analyze the data (SPSS v 21). RESULTS: Overall, children engaged in PA for 24 min (SD = 4.8) and parents 16 min (SD 9.6). After dividing children into two groups based on activity level, parents of higher active children were more encouraging than parents of lower active children (54.3 vs 40.9 times; p = 0.002). Similarly, the lower active children had parents encourage SA more (18.8 vs 3.9 times; p ≤ 0.001). Overweight children had parents discourage SA more compared to normal weight children (0.73 vs. 0.10 times; p ≤ 0.001). Parents of overweight children also verbally discouraged (SA) more relative to parents of normal weight children (0.64 vs. 0.10 times; p ≤ 0.001). CONCLUSIONS: Our findings illustrate that observed parental practices relate to children’s PA and weight status in a controlled laboratory setting. Future research might investigate whether these laboratory-based findings translate into increased PA in free-living children.

Associations between physical activity and health-related fitness – volume versus pattern

ABSTRACTApproximately 3.2 million people die of non-communicable diseases (NCD) each year due to insufficient physical activity. Physical activity guidelines are possibly perceived as too demanding and might thus pose a barrier. We addressed the question if a more stable physical activity pattern is associated with higher levels of health-related fitness than one with high and low intensities, regardless of the physical activity level (PAL). Physical activity was objectively measured in 296 men and women (53.7 ± 8.94 years) with the SenseWear Pro Armband®. Using this data, the PAL and a Gini index were calculated to report the physical activity pattern. Health-related fitness was expressed as a fitness index. PAL was weakly correlated to health-related fitness (r = 0.38, P < .0001). The Gini index was also weakly correlated to the fitness index (r = 0.23, P < .0001). Results of the ANCOVA showed that participants in the first quartile of PAL always scored significantly lower for health-related fitness than participants in quartile four, after adjustment for the Gini index. These results suggest that as long as the volume of physical activity is high, health-related fitness will be high as well, independent of the physical activity pattern or variability in intensities throughout the day.

The relationship between mitochondrial function and walking performance in older adults with a wide range of physical function

BackgroundAge related declines in walking performance may be partly attributable to skeletal muscle mitochondrial dysfunction as mitochondria produce over 90% of ATP needed for movement and the capacity for oxidative phosphorylation decreases with age. MethodsParticipants were from two studies: an ancillary to the Lifestyle Interventions and Independence for Elders (LIFE) Study (n=33), which recruited lower functioning participants (Short Physical Performance Battery [SPPB], 7.8±1.2), and the Study of Energy and Aging-Pilot (SEA, n=29), which enrolled higher functioning (SPPB, 10.8±1.4). Physical activity was measured objectively using the Actigraph accelerometer (LIFE) and SenseWear Pro armband (SEA). Phosphocreatine recovery following muscle contraction of the quadriceps was measured using 31P magnetic resonance spectroscopy and ATPmax (mM ATP/s) was calculated. Walking performance was defined as time (s) to walk 400m at a usual-pace. The cross-sectional association between mitochondrial function and walking performance was assessed using multivariable linear regression. ResultsParticipants were 77.6±5.3years, 64.2% female and 67.2% white. ATPmax was similar in LIFE vs. SEA (0.52±0.14 vs. 0.55±0.14, p=0.31), despite different function and activity levels (1.6±2.2 vs.77.4±73.3min of moderate activity/day, p<0.01). Higher ATPmax was related to faster walk-time in SEA (r2=0.19, p=0.02,); but not the LIFE (r2<0.01, p=0.74) cohort. ConclusionsMitochondrial function was associated with walking performance in higher functioning, active older adults, but not lower functioning, sedentary older adults.

Bias in food intake reporting in children and adolescents with type 1 diabetes: the role of body size, age and gender.

An assessment of total daily energy intake is helpful in planning the overall treatment of children with type 1 diabetes (T1D). However, energy intake misreporting may hinder nutritional intervention. To assess the plausibility of energy intake reporting and the potential role of gender, body mass index (BMI) z-score (z-BMI), disease duration and insulin requirement in energy intake misreporting in a sample of children and adolescents with T1D. The study included 58 children and adolescents aged 8-16 yr with T1D. Anthropometry, blood pressure and glycated hemoglobin (HbA1c) were measured. Subjects were instructed to wear a SenseWear Pro Armband (SWA) for 3 consecutive days, including a weekend day and to fill out with their parents a weighed dietary record for the same days. Predicted energy expenditure (pEE) was calculated by age and gender specific equations, including gender, age, weight, height and physical activity level (assessed by SWA). The percent reported energy intake (rEI)/pEE ratio was used as an estimate of the plausibility of dietary reporting. Misreporting of food intake, especially under-reporting, was common in children and adolescents with T1D: more than one-third of participants were classified as under-reporters and 10% as over-reporters. Age, z-BMI and male gender were associated with the risk of under-reporting (model R2 = 0.5). Waist circumference was negatively associated with the risk of over-reporting (model R2 = 0.25). Children and adolescents with T1D frequently under-report their food intake. Age, gender and z-BMI contribute to identify potential under-reporters.

The Impact of a Videogame-Based Pilot Physical Activity Program in Older Adults with Schizophrenia on Subjectively and Objectively Measured Physical Activity.

The purpose of this report is to describe the impact of a videogame-based pilot physical activity program using the Kinect for Xbox 360 game system (Microsoft, Redmond, WA, USA) on physical activity in older adults with schizophrenia. In this one group pre-test, post-test pilot study, 20 participants played an active videogame for 30 min, once a week for 6 weeks. Physical activity was measured by self-report with the Yale Physical Activity Survey and objectively with the Sensewear Pro armband at enrollment and at the end of the 6-week program. There was a significant increase in frequency of self-reported vigorous physical activity. We did not detect a statistically significant difference in objectively measured physical activity although increase in number of steps and sedentary activity were in the desired direction. These results suggest participants' perception of physical activity intensity differs from the intensity objectively captured with a valid and reliable physical activity monitor.

Estimating sleep from multisensory armband measurements: validity and reliability in teens.

Given the recognition that sleep may influence obesity risk, there is increasing interest in measuring sleep parameters within obesity studies. The goal of the current analyses was to determine whether the SenseWear(®) Pro3 Armband (armband), typically used to assess physical activity, is reliable at assessing sleep parameters. The armband was compared with the AMI Motionlogger(®) (actigraph), a validated activity monitor for sleep assessment, and with polysomnography, the gold standard for assessing sleep. Participants were 20 adolescents (mean age = 15.5 years) with a mean body mass index percentile of 63.7. All participants wore the armband and actigraph on their non-dominant arm while in-lab during a nocturnal polysomnographic recording (600 min). Epoch-by-epoch sleep/wake data and concordance of sleep parameters were examined. No significant sleep parameter differences were found between the armband and polysomnography; the actigraph tended to overestimate sleep and underestimate wake compared with polysomnography. Both devices showed high sleep sensitivity, but lower wake detection rates. Bland-Altman plots showed large individual differences in armband sleep parameter concordance rates. The armband did well estimating sleep overall, with group results more similar to polysomnography than the actigraph; however, the armband was less accurate at an individual level than the actigraph.

Extremes Of Weight Gain And Weight Loss

HISTORY: Extreme weight changes, or changes in weight greater than 10 kg within a 2 year period, can be caused by numerous factors that are much different than typical weight fluctuations. We examined two interesting cases of extreme weight change from participants in the Energy Balance Study to illustrate the physiological and behavioral variables associated with the weight change over a 15-month period, including rigorous assessments of energy intake, moderate-vigorous physical activity (MVPA) and energy expenditure, and body composition. Participant 1 was a 21 year old non-smoking African-American female who gained 11.1 kg over a 15 month period (Baseline Weight= 84.4 kg; Follow-up Weight= 95.5 kg). Participant 2 was a 30 year old Caucasian male who lost 17.4 kg over the same 15 month period (Baseline Weight= 93.5 kg; Follow-up Weight= 76.1 kg). PHYSICAL EXAMINATION: Participants were measured at quarterly intervals for the following information: 1) body weight; 2) energy intake via interviewer administered 24-hour dietary recalls; 3) energy expenditure via a SenseWear Pro armband; and 4) surveys monitoring life events. DIFFERENTIAL DIAGNOSIS: -Extremes of weight change occurred in both participants. TEST AND RESULTS: -Participant 1 was far less active than the average female in the study, engaging in as little (MVPA) as 3.3 minutes/day at month 3, and as many as 65.0 minutes/day at month 15. Participant 1 also had difficulty accurately recording her energy intake, as the values were implausible. -Participant 2 engaged in far more MVPA than the average male in the study, participating in as much as 162.0 min/day at month 9. Participant 2 was able to more accurately track his energy intake as his MVPA increased. FINAL/WORKING DIAGNOSIS: -MVPA was an instrumental factor in the extreme weight changes that occurred in both subjects. -MVPA involvement also increased awareness of energy intake. TREATMENT AND OUTCOMES: 1. The large amount of MVPA that Participant 2 regularly engaged in was a major catalyst for his weight loss. 2. Participant 1 had extremely low MVPA which may have contributed to her large weight gain. 3. MVPA should be encouraged for weight maintenance as well as for weight loss.

Validity of the SenseWear armband step count measure during controlled and free-living conditions

Background/ObjectiveAdvances in technology continue to provide numerous options for physical activity assessment. These advances necessitate evaluation of the validity of newly developed activity monitors being used in clinical and research settings. The purpose of this study was to validate the SenseWear Pro3 Armband (SWA) step counts during treadmill walking and free-living conditions. MethodsStudy 1 observed 39 individuals (17 males, 22 females) wearing an SWA and a Yamax Digiwalker SW-701 pedometer (DIGI) during treadmill walking, utilizing manually counted steps as the criterion. Study 2 compared free-living step count data from 35 participants (17 males, 18 females) wearing the SWA and DIGI (comparison) for 3 consecutive days. ResultsDuring Study 1, the SWA underestimated steps by 16.0%, 10.7%, 5.6%, 6.1%, and 6.5% at speeds of 54 m/min, 67 m/min, 80 m/min, 94 m/min, and 107 m/min, respectively, compared to manually counted steps. During Study 2, the intraclass correlation (ICC) coefficient of mean steps/d between the SWA and DIGI was strong (r = 0.98, p < 0.001). Unlike Study 1, the SWA overestimated step counts during the 3-day wear period by an average of 1028 steps/d (or +11.3%) compared to the DIGI. When analyzed individually, the SWA consistently overestimated step counts for each day (p < 0.05). ConclusionThe SWA underestimates steps during treadmill walking and appears to overestimate steps during free-living compared to the DIGI pedometer. Caution is warranted when using the SWA to count steps. Modifications are needed to enhance step counting accuracy.

Assessing the energy expenditure of elite female soccer players using the SenseWear Pro Armband

Assessing the energy expenditure of elite female soccer players using the SenseWear Pro Armband

Validation of the SenseWear Pro3 Armband using an incremental exercise test.

The purpose of this study is to assess the accuracy of a multisensor activity monitor in measuring energy expenditure (EE) using an incremental exercise test. The SenseWear Pro3 Armband (SWA) has been shown a valid and practical tool in measuring the EE of daily living activities but shows significant errors in estimating EE of activities of vigorous and very vigorous intensity. Recently, a new algorithm was developed for SWA (SWA v5.2). The aim of this study was to validate the new SWA algorithm in assessing EE using an incremental exercise test. Data were obtained from 44 students (age, 21.1 ± 1.4 years). During an incremental running test, EE estimates of the SWA were compared with the indirect calorimetry (IC). A paired t-test, Bland and Altman plots, and correlation coefficients were used as statistical techniques. Compared with the IC, the SWA showed no significant difference when walking at 1.5 m·s (p = 0.901) but significantly underestimated EE at higher speeds starting from a jogging speed of 1.67 m·s for men and from a running speed of 2 m·s for women. The underestimation increased significantly with increasing intensity in both male and female participants. The accurate measurement of EE at moderate intensity makes the monitor a valid tool in estimating daily life activities. However, our study results question the applicability of the monitor for individuals willing to monitor their EE during vigorous or very vigorous exercise intensities because a significant underestimation of the new algorithm is still present. In future, the EE algorithm needs to be further adjusted to give an accurate estimate of EE for high-intensity exercises.

Validity of physical activity monitors for assessing lower intensity activity in adults.

BackgroundAccelerometers can provide accurate estimates of moderate-to-vigorous physical activity (MVPA). However, one of the limitations of these instruments is the inability to capture light activity within an acceptable range of error. The purpose of the present study was to determine the validity of different activity monitors for estimating energy expenditure (EE) of light intensity, semi-structured activities.MethodsForty healthy participants wore a SenseWear Pro3 Armband (SWA, v.6.1), the SenseWear Mini, the Actiheart, ActiGraph, and ActivPAL monitors, while being monitored with a portable indirect calorimetry (IC). Participants engaged in a variety of low intensity activities but no formalized scripts or protocols were used during these periods.ResultsThe Mini and SWA overestimated total EE on average by 1.0% and 4.0%, respectively, while the AH, the GT3X, and the AP underestimated total EE on average by 7.8%, 25.5%, and 22.2%, respectively. The pattern-recognition monitors yielded non-significant differences in EE estimates during the semi-structured period (p = 0.66, p = 0.27, and p = 0.21 for the Mini, SWA, and AH, respectively).ConclusionsThe SenseWear Mini provided more accurate estimates of EE during light to moderate intensity semi-structured activities compared to other activity monitors. This monitor should be considered when there is interest in tracking low intensity activities in groups of individuals.