Physical activity recognition from accelerometer data using a multi-scale ensemble method

Accurate and detailed measurement of an individual's physical activity is a key requirement for helping researchers understand the relationship between physical activity and health. Accelerometers have become the method of choice for measuring physical activity due to their small size, low cost, convenience and their ability to provide objective information about physical activity. However, interpreting accelerometer data once it has been collected can be challenging. In this work, we applied machine learning algorithms to the task of physical activity recognition from triaxial accelerometer data. We employed a simple but effective approach of dividing the accelerometer data into short non-overlapping windows, converting each window into a feature vector, and treating each feature vector as an i.i.d training instance for a supervised learning algorithm. In addition, we improved on this simple approach with a multi-scale ensemble method that did not need to commit to a single window size and was able to leverage the fact that physical activities produced time series with repetitive patterns and discriminative features for physical activity occurred at different temporal scales.

The association between adolescent self-reported physical activity and wellness : the missing piece for youth wellness programs

Purpose Potential positive associations between youth physical activity and wellness scores could emphasize the value of youth physical activity engagement and promotion interventions, beyond the many established physiological and psychological benefits of increased physical activity. The purpose of this study was to explore the associations between adolescents' self-reported physical activity and wellness. Methods This investigation included 493 adolescents (165 males and 328 females) aged between 12 and 15 years. The participants were recruited from six secondary schools of varying socioeconomic status within a metropolitan area. Students were administered the Five-Factor Wellness Inventory and the International Physical Activity Questionnaire for Adolescents to assess both wellness and physical activity, respectively. Results Data indicated that significant associations between physical activity and wellness existed. Self-reported physical activity was shown to be positively associated with four dimensions including friendship, gender identity, spirituality, and exercise—the higher order factor physical self and total wellness, and negatively associated with self-care, self-worth, love, and cultural identity. Conclusion This study suggests that relationships exist between self-reported physical activity and various elements of wellness. Future research should use controlled trials of physical activity and wellness to establish causal links among youth populations. Understanding the nature of these relationships, including causality, has implications for the justification of youth physical activity promotion interventions and the development of youth physical activity engagement programs.

Measurement equivalence of the dispositional resistance to change scale

Intended to bridge the gap between the latest methodological developments and cross-cultural research, this interdisciplinary resource presents the latest strategies for analyzing cross-cultural data. Techniques are demonstrated through the use of applications that employ cross national data sets such as the latest European Social Survey. With an emphasis on the generalized latent variable approach, internationally?prominent researchers from a variety of fields explain how the methods work, how to apply them, and how they relate to other methods presented in the book. Syntax and graphical and verbal explanations of the techniques are included. [from publisher's website]

Calibration and validation of wearable monitors

Background Wearable monitors are increasingly being used to objectively monitor physical activity in research studies within the field of exercise science. Calibration and validation of these devices are vital to obtaining accurate data. This article is aimed primarily at the physical activity measurement specialist, although the end user who is conducting studies with these devices also may benefit from knowing about this topic. Best Practices Initially, wearable physical activity monitors should undergo unit calibration to ensure interinstrument reliability. The next step is to simultaneously collect both raw signal data (e.g., acceleration) from the wearable monitors and rates of energy expenditure, so that algorithms can be developed to convert the direct signals into energy expenditure. This process should use multiple wearable monitors and a large and diverse subject group and should include a wide range of physical activities commonly performed in daily life (from sedentary to vigorous). Future Directions New methods of calibration now use "pattern recognition" approaches to train the algorithms on various activities, and they provide estimates of energy expenditure that are much better than those previously available with the single-regression approach. Once a method of predicting energy expenditure has been established, the next step is to examine its predictive accuracy by cross-validating it in other populations. In this article, we attempt to summarize the best practices for calibration and validation of wearable physical activity monitors. Finally, we conclude with some ideas for future research ideas that will move the field of physical activity measurement forward.

Identification and Validity of Accelerometer Cut-Points for Toddlers

The purpose of this study was to derive ActiGraph cut-points for sedentary (SED), light-intensity physical activity (LPA), and moderate-to-vigorous physical activity (MVPA) in toddlers and evaluate their validity in an independent sample. The predictive validity of established preschool cut-points were also evaluated and compared. Twenty-two toddlers (mean age = 2.1 years ± 0.4 years) wore an ActiGraph accelerometer during a videotaped 20-min play period. Videos were subsequently coded for physical activity (PA) intensity using the modified Children's Activity Rating Scale (CARS). Receiver operating characteristic (ROC) curve analyses were conducted to determine cut-points. Predictive validity was assessed in an independent sample of 18 toddlers (mean age = 2.3 ± 0.4 years). From the ROC curve analyses, the 15-s count ranges corresponding to SED, LPA, and MVPA were 0–48, 49–418, and >418 counts/15 s, respectively. Classification accuracy was fair for the SED threshold (ROC-AUC = 0.74, 95% confidence interval = 0.71–0.76) and excellent for MVPA threshold (ROC-AUC = 0.90, 95% confidence interval = 0.88–0.92). In the cross-validation sample, the toddler cut-point and established preschool cut-points significantly overestimated time spent in SED and underestimated time in spent in LPA. For MVPA, mean differences between observed and predicted values for the toddler and Pate cut-points were not significantly different from zero. In summary, the ActiGraph accelerometer can provide useful group-level estimates of MVPA in toddlers. The results support the use of the Pate cut-point of 420 counts/15 s for MVPA.

Comparison of accelerometer cut points for predicting activity intensity in youth

The absence of comparative validity studies has prevented researchers from reaching consensus regarding the application of intensity-related accelerometer cut points for children and adolescents. PURPOSE This study aimed to evaluate the classification accuracy of five sets of independently developed ActiGraph cut points using energy expenditure, measured by indirect calorimetry, as a criterion reference standard. METHODS A total of 206 participants between the ages of 5 and 15 yr completed 12 standardized activity trials. Trials consisted of sedentary activities (lying down, writing, computer game), lifestyle activities (sweeping, laundry, throw and catch, aerobics, basketball), and ambulatory activities (comfortable walk, brisk walk, brisk treadmill walk, running). During each trial, participants wore an ActiGraph GT1M, and VO 2 was measured breath-by-breath using the Oxycon Mobile portable metabolic system. Physical activity intensity was estimated using five independently developed cut points: Freedson/Trost (FT), Puyau (PU), Treuth (TR), Mattocks (MT), and Evenson (EV). Classification accuracy was evaluated via weighted κ statistics and area under the receiver operating characteristic curve (ROC-AUC). RESULTS Across all four intensity levels, the EV (κ = 0.68) and FT (κ = 0.66) cut points exhibited significantly better agreement than TR (κ = 0.62), MT (κ = 0.54), and PU (κ = 0.36). The EV and FT cut points exhibited significantly better classification accuracy for moderate-to vigorous-intensity physical activity (ROC-AUC = 0.90) than TR, PU, or MT cut points (ROC-AUC = 0.77-0.85). Only the EV cut points provided acceptable classification accuracy for all four levels of physical activity intensity and performed well among children of all ages. The widely applied sedentary cut point of 100 counts per minute exhibited excellent classification accuracy (ROC-AUC = 0.90). CONCLUSIONS On the basis of these findings, we recommend that researchers use the EV ActiGraph cut points to estimate time spent in sedentary, light-, moderate-, and vigorous-intensity activity in children and adolescents. Copyright © 2011 by the American College of Sports Medicine.

Validity of accelerometry for measurement of activity in people with brain injury

Purpose To evaluate the validity of a uniaxial accelerometer (MTI Actigraph) for measuring physical activity in people with acquired brain injury (ABI) using portable indirect calorimetry (Cosmed K4b(2)) as a criterion measure. Methods Fourteen people with ABI and related gait pattern impairment (age 32 +/- 8 yr) wore an MTI Actigraph that measured activity (counts(.)min-(1)) and a Cosmed K4b(2) that measured oxygen consumption (mL(.)kg(-1.)min(-1)) during four activities: quiet sitting (QS) and comfortable paced (CP), brisk paced (BP), and fast paced (FP) walking. MET levels were predicted from Actigraph counts using a published equation and compared with Cosmed measures. Predicted METs for each of the 56 activity bouts (14 participants X 4 bouts) were classified (light, moderate, vigorous, or very vigorous intensity) and compared with Cosmed-based classifications. Results Repeated-measures ANOVA indicated that walking condition intensities were significantly different (P < 0.05) and the Actigraph detected the differences. Overall correlation between measured and predicted METs was positive, moderate, and significant (r = 0.74). Mean predicted METs were not significantly different from measured for CP and BP, but for FP walking, predicted METs were significantly less than measured (P < 0.05). The Actigraph correctly classified intensity for 76.8% of all activity bouts and 91.5% of light- and moderate-intensity bouts. Conclusions Actigraph counts provide a valid index of activity across the intensities investigated in this study. For light to moderate activity, Actigraph-based estimates of METs are acceptable for group-level analysis and are a valid means of classifying activity intensity. The Actigraph significantly underestimated higher intensity activity, although, in practice, this limitation will have minimal impact on activity measurement of most community-dwelling people with ABI.

State of the art reviews : measurement of physical activity in children and adolescents

To date, a wide range of methods has been used to measure physical activity in children and adolescents. These include self-report methods such as questionnaires, activity logs, and diaries as well as objective measures of physical activity such as direct observation, doubly labeled water, heart rate monitoring, accelerometers, and pedometers. The purpose of this review is to overview the methods currently being used to measure physical activity in children and adolescents. For each measurement approach, new developments and/or innovations are identified and discussed. Particular attention is given to the use of accelerometers and the calibration of accelerometer output to units of energy expenditure to developing children.

Validity of accelerometry in ambulatory children and adolescents with cerebral palsy

To evaluate the validity of the ActiGraph accelerometer for the measurement of physical activity intensity in children and adolescents with cerebral palsy (CP) using oxygen uptake (VO 2) as the criterion measure. Thirty children and adolescents with CP (mean age 12.6 ± 2.0 years) wore an ActiGraph 7164 and a Cosmed K4b 2 portable indirect calorimeter during four activities; quiet sitting, comfortable paced walking, brisk paced walking and fast paced walking. VO 2 was converted to METs and activity energy expenditure and classiWed as sedentary, light or moderate-to-vigorous intensity according to the conventions for children. Mean ActiGraph counts min -1 were classiWed as sedentary, light or moderate-to-vigorous (MVPA) intensity using four diVerent sets of cut-points. VO 2 and counts min¡1 increased signiWcantly with increases in walking speed (P < 0.001). Receiver operating characteristic (ROC) curve analysis indicated that, of the four sets of cut-points evaluated, the Evenson et al. (J Sports Sci 26(14):1557-1565, 2008) cut-points had the highest classiWcation accuracy for sedentary (92%) and MVPA (91%), as well as the second highest classiWcation accuracy for light intensity physical activity (67%). A ROC curve analysis of data from our participants yielded a CP-speciWc cut-point for MVPA that was lower than the Evenson cut-point (2,012 vs. 2,296 counts min¡1), however, the diVerence in classiWcation accuracy was not statistically signiWcant 94% (95% CI = 88.2-97.7%) vs. 91% (95% CI = 83.5-96.5%). In conclusion, among children and adolescents with CP, the ActiGraph is able to diVerentiate between diVerent intensities of walking. The use of the Evenson cut-points will permit the estimation of time spent in MVPA and allows comparisons to be made between activity measured in typically developing adolescents and adolescents with CP. © 2011 Springer-Verlag.

Calibration and comparison of accelerometer cut points in preschool children

Objective The present study aimed to develop accelerometer cut points to classify physical activities (PA) by intensity in preschoolers and to investigate discrepancies in PA levels when applying various accelerometer cut points. Methods To calibrate the accelerometer, 18 preschoolers (5.8 +/- 0.4 years) performed eleven structured activities and one free play session while wearing a GT1M ActiGraph accelerometer using 15 s epochs. The structured activities were chosen based on the direct observation system Children's Activity Rating Scale (CARS) while the criterion measure of PA intensity during free play was provided using a second-by-second observation protocol (modified CARS). Receiver Operating Characteristic (ROC) curve analyses were used to determine the accelerometer cut points. To examine the classification differences, accelerometer data of four consecutive days from 114 preschoolers (5.5 +/- 0.3 years) were classified by intensity according to previously published and the newly developed accelerometer cut points. Differences in predicted PA levels were evaluated using repeated measures ANOVA and Chi Square test. Results Cut points were identified at 373 counts/15 s for light (sensitivity: 86%; specificity: 91%; Area under ROC curve: 0.95), 585 counts/15 s for moderate (87%; 82%; 0.91) and 881 counts/15 s for vigorous PA (88%; 91%; 0.94). Further, applying various accelerometer cut points to the same data resulted in statistically and biologically significant differences in PA. Conclusions Accelerometer cut points were developed with good discriminatory power for differentiating between PA levels in preschoolers and the choice of accelerometer cut points can result in large discrepancies.

Physical activities and sedentary pursuits in African American and Caucasian girls

The purposes of this study were to describe and compare the specific physical activity choices and sedentary pursuits of African American and Caucasian American girls. Participants were 1,124 African American and 1,068 Caucasian American eighth grade students from 31 middle schools. The 3-Day Physical Activity Recall (3DPAR) was used to measure participation in physical activities and sedentary pursuits. The most frequently reported physical activities were walking, basketball, jogging or running, bicycling, and social dancing. Differences between groups were found in 11 physical activities and 3 sedentary pursuits. Participation rates were higher in African American girls (p<.001)for social dancing, basketball, watching television, and church attendance but lower in calisthenics, ballet and other dance, jogging or running, rollerblading, soccer, softball or baseball, using an exercise machine, swimming, and homework. Cultural differences of groups should be considered when planning interventions to promote physical activity.

Comparison of surveys used to measure physical activity

Objective To compare the level of agreement in results obtained from four physical activity (PA) measurement instruments that are in use in Australia and around the world. Methods 1,280 randomly selected participants answered two sets of PA questions by telephone. 428 answered the Active Australia (AA) and National Health Surveys, 427 answered the AA and CDC Behavioural Risk Factor Surveillance System surveys (BRFSS), and 425 answered the AA survey and the short International Physical Activity Questionnaire (IPAQ). Results Among the three pairs of survey items, the difference in mean total PA time was lowest when the AA and NHS items were asked (difference=24) (SE:17) minutes, compared with 144 (SE:21) mins for AA/BRFSS and 406 (SE:27) mins for AA/IPAQ). Correspondingly, prevalence estimates for 'sufficiently active' were similar for AA and NHS (56% and 55% respectively), but about 10% higher when BRFSS data were used, and about 26% higher when the IPAQ items were used, compared with estimates from the AA survey. Conclusions The findings clearly demonstrate that there are large differences in reported PA times and hence in prevalence estimates of 'sufficient activity' from these four measures. Implications It is important to consistently use the same survey for population monitoring purposes. As the AA survey has now been used three times in national surveys, its continued use for population surveys is recommended so that trend data ever a longer period of time can be established.

Validation of accelerometry for physical activity measurement in ambulant adolescents with cerebral palsy

Background Promoting participation physical activity (PA) is an important means of promoting healthy growth and development in children with cerebral palsy (CP). The ActiGraph is a uniaxial accelerometer that provides a realtime measure of PA intensity, duration and frequency. Its small, light weight design makes it a promising measure of activity in children with CP. To date no study has validated the use of accelerometry as a measure of PA in ambulant adolescents with CP. Objectives To evaluate the validity of the ActiGraph accelerometer for measuring PA intensity in adolescents with CP, using oxygen consumption (VO2), measured using portable indirect calorimetry (Cosmed K4b2), as the criterion measure. Design Validation Study Participants/Setting: Ambulant adolescents with CP aged 10–16 years, GMFCS rating of I-III. The recruitment target is 30 (10 in each GMFCS level). Materials/Methods Participants wore the ActiGraph (counts/min) and a Cosmed K4b2 indirect calorimeter (mL/kg/min) during six activity trials: quiet sitting (QS), comfortable paced walking (CPW), brisk paced walking (BPW), fast paced walking (FPW), a ball-kicking protocol (KP) and a ball-throwing protocol (TP). MET levels (multiples of resting metabolism) for each activity were predicted from ActiGraph counts using the Freedson age-specific equation (Freedson et al. 2005) and compared with actual MET levels measured by the Cosmed. Predicted and measured METs for each activity trial were classified as light (> 1.5 METs and <4.6 METs) or moderate to vigorous intensity (≥ 4.6 METs). Results To date 36 bouts of activity have been completed (6 participants x 6 activities). Mean VO2 increased linearly as the intensity of the walking activity increased (CPW=9.47±2.16, BPW=14.06±4.38, FPW=19.21±5.68 ml/kg/min) and ActiGraph counts reflected this pattern (CPW=1099±574, BPW=2233±797 FPW=4707±1013 counts/min). The throwing protocol recording the lowest VO2 (TP=7.50±3.86 ml/kg/min) and lowest overall counts/min (TP=31±27 counts/min). When each of the 36 bouts were classified as either light or moderate to vigorous intensity using measured VO2 as the criterion measure, the Freedson equation correctly classified 28 from 36 bouts (78%). Conclusion/Clinical Implications These preliminary findings suggest that there is a relationship between the intensity of PA and direct measure of oxygen consumption and that therefore the ActiGraph may be a promising tool for accurately measuring free living PA in the community. Further data collection of the complete sample will enable secondary analysis of the relationship between PA and severity of CP (GMFCS level).

Test-retest reliability of physical activity measures used in Australian population surveys

PURPOSE Accurate monitoring of prevalence and trends in population levels of physical activity is fundamental to the planning of health promotion and disease-prevention strategies. Test-retest reliability (repeatability) was assessed for four self-report measures of physical activity commonly used in population surveys: the Active Australia survey (AA, N=356), the short form of the International Physical Activity Questionnaire (IPAQ-S, N=104), the physical activity items in the Behavioral Risk Factor Surveillance System (BRFSS, N=127) and the physical activity items in the Australian National Health Survey (NHS, N=122). METHODS Percent agreement and Kappa statistics were used to assess the reliability of classification of activity status (where ‘active’= 150 minutes of activity per week) and sedentariness (where ‘sedentary’ = reporting no physical activity). Intraclass correlations (ICCs) were used to assess agreement on minutes of activity reported for each item of each survey and on total minutes reported in each survey. RESULTS Percent agreement scores for both activity status and sedentariness were very good on all four instruments. Overall the percent agreement between repeated surveys was between 73% (NHS) and 87% (IPAQ) for the criterion measure of achieving 150 minutes per week, and between 77% (NHS) and 89% (IPAQ) for the criterion of being sedentary. Corresponding Kappa statistics ranged from 0.46 (NHS) to 0.61 (AA) for activity status and from 0.20 (BRFSS) to 0.52 (AA) for sedentariness. For the individual items ICCs were highest for walking (0.45 to 0.56) and vigorous activity (0.22 to 0.64) and lowest for the moderate questions (0.16 to 0.44). CONCLUSION All four measures provide acceptable levels of test-retest reliability for assessing both activity status and sedentariness, and moderate reliability for assessing total minutes of activity. Supported by the Australian Commonwealth Department of Health and Ageing.

Disaster resilience in tertiary hospitals : a cross-sectional survey in Shandong Province, China

Background: Hospital disaster resilience can be defined as a hospital’s ability to resist, absorb, and respond to the shock of disasters while maintaining critical functions, and then to recover to its original state or adapt to a new one. This study aims to explore the status of resilience among tertiary hospitals in Shandong Province, China. Methods: A stratified random sample (n = 50) was derived from tertiary A, tertiary B, and tertiary C hospitals in Shandong Province, and was surveyed by questionnaire. Data on hospital characteristics and 8 key domains of hospital resilience were collected and analysed. Variables were binary, and analysed using descriptive statistics such as frequencies. Results: A response rate of 82% (n = 41) was attained. Factor analysis identified four key factors from eight domains which appear to reflect the overall level of disaster resilience. These were hospital safety, disaster management mechanisms, disaster resources and disaster medical care capability. The survey demonstrated that in regard to hospital safety, 93% had syndromic surveillance systems for infectious diseases and 68% had evaluated their safety standards. In regard to disaster management mechanisms, all had general plans, while only 20% had specific plans for individual hazards. 49% had a public communication protocol and 43.9% attended the local coordination meetings. In regard to disaster resources, 75.6% and 87.5% stockpiled emergency drugs and materials respectively, while less than a third (30%) had a signed Memorandum of Understanding with other hospitals to share these resources. Finally in regard to medical care, 66% could dispatch an on-site medical rescue team, but only 5% had a ‘portable hospital’ function and 36.6% and 12% of the hospitals could surge their beds and staff capacity respectively. The average beds surge capacity within 1 day was 13%. Conclusions: This study validated the broad utility of a framework for understanding and measuring the level of hospital resilience. The survey demonstrated considerable variability in disaster resilience arrangements of tertiary hospitals in Shandong province, and the difference between tertiary A hospitals and tertiary B hospitals was also identified in essential areas.