1
|
Bao L, Intille SS. Activity Recognition from User-Annotated Acceleration Data. LECTURE NOTES IN COMPUTER SCIENCE 2004. [DOI: 10.1007/978-3-540-24646-6_1] [Citation(s) in RCA: 1184] [Impact Index Per Article: 56.4] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Academic Contribution Register] [Indexed: 12/04/2022]
|
|
21 |
1184 |
2
|
|
|
26 |
324 |
3
|
Patrick K, Griswold WG, Raab F, Intille SS. Health and the mobile phone. Am J Prev Med 2008; 35:177-81. [PMID: 18550322 PMCID: PMC2527290 DOI: 10.1016/j.amepre.2008.05.001] [Citation(s) in RCA: 236] [Impact Index Per Article: 13.9] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Academic Contribution Register] [Received: 04/02/2008] [Revised: 04/02/2008] [Accepted: 05/05/2008] [Indexed: 11/16/2022]
|
Research Support, N.I.H., Extramural |
17 |
236 |
4
|
Mannini A, Intille SS, Rosenberger M, Sabatini AM, Haskell W. Activity recognition using a single accelerometer placed at the wrist or ankle. Med Sci Sports Exerc 2013; 45:2193-203. [PMID: 23604069 PMCID: PMC3795931 DOI: 10.1249/mss.0b013e31829736d6] [Citation(s) in RCA: 180] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Academic Contribution Register] [Indexed: 02/04/2023]
Abstract
PURPOSE Large physical activity surveillance projects such as the UK Biobank and NHANES are using wrist-worn accelerometer-based activity monitors that collect raw data. The goal is to increase wear time by asking subjects to wear the monitors on the wrist instead of the hip, and then to use information in the raw signal to improve activity type and intensity estimation. The purposes of this work was to obtain an algorithm to process wrist and ankle raw data and to classify behavior into four broad activity classes: ambulation, cycling, sedentary, and other activities. METHODS Participants (N = 33) wearing accelerometers on the wrist and ankle performed 26 daily activities. The accelerometer data were collected, cleaned, and preprocessed to extract features that characterize 2-, 4-, and 12.8-s data windows. Feature vectors encoding information about frequency and intensity of motion extracted from analysis of the raw signal were used with a support vector machine classifier to identify a subject's activity. Results were compared with categories classified by a human observer. Algorithms were validated using a leave-one-subject-out strategy. The computational complexity of each processing step was also evaluated. RESULTS With 12.8-s windows, the proposed strategy showed high classification accuracies for ankle data (95.0%) that decreased to 84.7% for wrist data. Shorter (4 s) windows only minimally decreased performances of the algorithm on the wrist to 84.2%. CONCLUSIONS A classification algorithm using 13 features shows good classification into the four classes given the complexity of the activities in the original data set. The algorithm is computationally efficient and could be implemented in real time on mobile devices with only 4-s latency.
Collapse
|
Research Support, N.I.H., Extramural |
12 |
180 |
5
|
Svetkey LP, Batch BC, Lin PH, Intille SS, Corsino L, Tyson CC, Bosworth HB, Grambow SC, Voils C, Loria C, Gallis JA, Schwager J, Bennett GG, Bennett GB. Cell phone intervention for you (CITY): A randomized, controlled trial of behavioral weight loss intervention for young adults using mobile technology. Obesity (Silver Spring) 2015; 23:2133-41. [PMID: 26530929 PMCID: PMC4636032 DOI: 10.1002/oby.21226] [Citation(s) in RCA: 118] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Academic Contribution Register] [Received: 03/21/2015] [Revised: 05/20/2015] [Accepted: 06/15/2015] [Indexed: 01/04/2023]
Abstract
OBJECTIVE To determine the effect on weight of two mobile technology-based (mHealth) behavioral weight loss interventions in young adults. METHODS Randomized, controlled comparative effectiveness trial in 18- to 35-year-olds with BMI ≥ 25 kg/m(2) (overweight/obese), with participants randomized to 24 months of mHealth intervention delivered by interactive smartphone application on a cell phone (CP); personal coaching enhanced by smartphone self-monitoring (PC); or Control. RESULTS The 365 randomized participants had mean baseline BMI of 35 kg/m(2) . Final weight was measured in 86% of participants. CP was not superior to Control at any measurement point. PC participants lost significantly more weight than Controls at 6 months (net effect -1.92 kg [CI -3.17, -0.67], P = 0.003), but not at 12 and 24 months. CONCLUSIONS Despite high intervention engagement and study retention, the inclusion of behavioral principles and tools in both interventions, and weight loss in all treatment groups, CP did not lead to weight loss, and PC did not lead to sustained weight loss relative to Control. Although mHealth solutions offer broad dissemination and scalability, the CITY results sound a cautionary note concerning intervention delivery by mobile applications. Effective intervention may require the efficiency of mobile technology, the social support and human interaction of personal coaching, and an adaptive approach to intervention design.
Collapse
|
Randomized Controlled Trial |
10 |
118 |
6
|
Abstract
Healthcare systems in developed countries are experiencing severe financial stress as age demographics shift upward, leading to a larger percentage of older adults needing care. One way to potentially reduce or slow spiraling medical costs is to use technology, not only to cure sickness, but also to promote wellness throughout all stages of life, thereby avoiding or deferring expensive medical treatments. Ubiquitous computing and context-aware algorithms offer a new healthcare opportunity and a new set of research challenges: exploiting emerging consumer electronic devices to motivate healthy behavior as people age by presenting "just-in-time" information at points of decision and behavior.
Collapse
|
Research Support, U.S. Gov't, Non-P.H.S. |
21 |
108 |
7
|
Dunton GF, Liao Y, Intille SS, Spruijt-Metz D, Pentz M. Investigating children's physical activity and sedentary behavior using ecological momentary assessment with mobile phones. Obesity (Silver Spring) 2011; 19:1205-12. [PMID: 21164502 DOI: 10.1038/oby.2010.302] [Citation(s) in RCA: 100] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Academic Contribution Register] [Indexed: 11/08/2022]
Abstract
The risk of obesity during childhood can be significantly reduced through increased physical activity and decreased sedentary behavior. Recent technological advances have created opportunities for the real-time measurement of these behaviors. Mobile phones are ubiquitous and easy to use, and thus have the capacity to collect data from large numbers of people. The present study tested the feasibility, acceptability, and validity of an electronic ecological momentary assessment (EMA) protocol using electronic surveys administered on the display screen of mobile phones to assess children's physical activity and sedentary behaviors. A total of 121 children (ages 9-13, 51% male, 38% at risk for overweight/overweight) participated in EMA monitoring from Friday afternoon to Monday evening during children's nonschool time, with 3-7 surveys/day. Items assessed current activity (e.g., watching TV/movies, playing video games, active play/sports/exercising). Children simultaneously wore an Actigraph GT2M accelerometer. EMA survey responses were time-matched to total step counts and minutes of moderate-to-vigorous physical activity (MVPA) occurring in the 30 min before each EMA survey prompt. No significant differences between answered and unanswered EMA surveys were found for total steps or MVPA. Step counts and the likelihood of 5+ min of MVPA were significantly higher during EMA-reported physical activity (active play/sports/exercising) vs. sedentary behaviors (reading/computer/homework, watching TV/movies, playing video games, riding in a car) (P < 0.001). Findings generally support the acceptability and validity of a 4-day EMA protocol using mobile phones to measure physical activity and sedentary behavior in children during leisure time.
Collapse
|
Clinical Trial |
14 |
100 |
8
|
Abstract
BACKGROUND Accelerometry and other sensing technologies are important tools for physical activity measurement. Engineering advances have allowed developers to transform clunky, uncomfortable, and conspicuous monitors into relatively small, ergonomic, and convenient research tools. New devices can be used to collect data on overall physical activity and, in some cases, posture, physiological state, and location, for many days or weeks from subjects during their everyday lives. In this review article, we identify emerging trends in several types of monitoring technologies and gaps in the current state of knowledge. BEST PRACTICES The only certainty about the future of activity-sensing technologies is that researchers must anticipate and plan for change. We propose a set of best practices that may accelerate adoption of new devices and increase the likelihood that data being collected and used today will be compatible with new data sets and methods likely to appear on the horizon. FUTURE DIRECTIONS We describe several technology-driven trends, ranging from continued miniaturization of devices that provide gross summary information about activity levels and energy expenditure to new devices that provide highly detailed information about the specific type, amount, and location of physical activity. Some devices will take advantage of consumer technologies, such as mobile phones, to detect and respond to physical activity in real time, creating new opportunities in measurement, remote compliance monitoring, data-driven discovery, and intervention.
Collapse
|
Research Support, N.I.H., Extramural |
13 |
71 |
9
|
Intille SS, Bobick AF. Disparity-space images and large occlusion stereo. COMPUTER VISION — ECCV '94 1994. [DOI: 10.1007/bfb0028349] [Citation(s) in RCA: 68] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Academic Contribution Register] [Indexed: 02/11/2023]
|
|
31 |
68 |
10
|
Abstract
To overcome problems with traditional methods for measuring stereotypical motor movements in persons with Autism Spectrum Disorders (ASD), we evaluated the use of wireless three-axis accelerometers and pattern recognition algorithms to automatically detect body rocking and hand flapping in children with ASD. Findings revealed that, on average, pattern recognition algorithms correctly identified approximately 90% of stereotypical motor movements repeatedly observed in both laboratory and classroom settings. Precise and efficient recording of stereotypical motor movements could enable researchers and clinicians to systematically study what functional relations exist between these behaviors and specific antecedents and consequences. These measures could also facilitate efficacy studies of behavioral and pharmacologic interventions intended to replace or decrease the incidence or severity of stereotypical motor movements.
Collapse
|
Journal Article |
14 |
58 |
11
|
Patrick K, Intille SS, Zabinski MF. An ecological framework for cancer communication: implications for research. J Med Internet Res 2005; 7:e23. [PMID: 15998614 PMCID: PMC1550654 DOI: 10.2196/jmir.7.3.e23] [Citation(s) in RCA: 57] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Academic Contribution Register] [Received: 09/15/2004] [Accepted: 02/19/2005] [Indexed: 11/24/2022] Open
Abstract
The field of cancer communication has undergone a major revolution as a result of the Internet. As recently as the early 1990s, face-to-face, print, and the telephone were the dominant methods of communication between health professionals and individuals in support of the prevention and treatment of cancer. Computer-supported interactive media existed, but this usually required sophisticated computer and video platforms that limited availability. The introduction of point-and-click interfaces for the Internet dramatically improved the ability of non-expert computer users to obtain and publish information electronically on the Web. Demand for Web access has driven computer sales for the home setting and improved the availability, capability, and affordability of desktop computers. New advances in information and computing technologies will lead to similarly dramatic changes in the affordability and accessibility of computers. Computers will move from the desktop into the environment and onto the body. Computers are becoming smaller, faster, more sophisticated, more responsive, less expensive, and--essentially--ubiquitous. Computers are evolving into much more than desktop communication devices. New computers include sensing, monitoring, geospatial tracking, just-in-time knowledge presentation, and a host of other information processes. The challenge for cancer communication researchers is to acknowledge the expanded capability of the Web and to move beyond the approaches to health promotion, behavior change, and communication that emerged during an era when language- and image-based interpersonal and mass communication strategies predominated. Ecological theory has been advanced since the early 1900s to explain the highly complex relationships among individuals, society, organizations, the built and natural environments, and personal and population health and well-being. This paper provides background on ecological theory, advances an Ecological Model of Internet-Based Cancer Communication intended to broaden the vision of potential uses of the Internet for cancer communication, and provides some examples of how such a model might inform future research and development in cancer communication.
Collapse
|
other |
20 |
57 |
12
|
Mannini A, Rosenberger M, Haskell WL, Sabatini AM, Intille SS. Activity Recognition in Youth Using Single Accelerometer Placed at Wrist or Ankle. Med Sci Sports Exerc 2017; 49:801-812. [PMID: 27820724 PMCID: PMC5850929 DOI: 10.1249/mss.0000000000001144] [Citation(s) in RCA: 54] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Academic Contribution Register] [Indexed: 11/21/2022]
Abstract
PURPOSE State-of-the-art methods for recognizing human activity using raw data from body-worn accelerometers have primarily been validated with data collected from adults. This study applies a previously available method for activity classification using wrist or ankle accelerometer to data sets collected from both adults and youth. METHODS An algorithm for detecting activity from wrist-worn accelerometers, originally developed using data from 33 adults, is tested on a data set of 20 youth (age, 13 ± 1.3 yr). The algorithm is also extended by adding new features required to improve performance on the youth data set. Subsequent tests on both the adult and youth data were performed using crossed tests (training on one group and testing on the other) and leave-one-subject-out cross-validation. RESULTS The new feature set improved overall recognition using wrist data by 2.3% for adults and 5.1% for youth. Leave-one-subject-out cross-validation accuracy performance was 87.0% (wrist) and 94.8% (ankle) for adults, and 91.0% (wrist) and 92.4% (ankle) for youth. Merging the two data sets, overall accuracy was 88.5% (wrist) and 91.6% (ankle). CONCLUSIONS Previously available methodological approaches for activity classification in adults can be extended to youth data. Including youth data in the training phase and using features designed to capture information on the activity fragmentation of young participants allows a better fit of the methodological framework to the characteristics of activity in youth, improving its overall performance. The proposed algorithm differentiates ambulation from sedentary activities that involve gesturing in wrist data, such as that being collected in large surveillance studies.
Collapse
|
Research Support, N.I.H., Extramural |
8 |
54 |
13
|
Liao Y, Intille SS, Dunton GF. Using ecological momentary assessment to understand where and with whom adults' physical and sedentary activity occur. Int J Behav Med 2015; 22:51-61. [PMID: 24639067 DOI: 10.1007/s12529-014-9400-z] [Citation(s) in RCA: 49] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Academic Contribution Register] [Indexed: 10/25/2022]
Abstract
PURPOSE This study used Ecological Momentary Assessment (EMA), a real-time self-report strategy, to describe the physical and social contexts of adults' physical activity and sedentary activity during their everyday lives and to determine whether these patterns and relationships differ for men and women. METHODS Data from 114 adults were collected through mobile phones across 4 days. Eight electronic EMA surveys were randomly prompted each day asking about current activities (e.g., physical or sedentary activity), physical and social contexts, and perceived outdoor environmental features (e.g., greenness/vegetation, safety, and traffic). All participants also wore accelerometers during this period to objectively measure moderate-to-vigorous physical activity (MVPA) and sedentary activity. RESULTS Home was the most common physical context for EMA-reported physical and sedentary activity. Most of these activities occurred when participants were alone. When alone, the most commonly EMA-reported physical activity and sedentary activity was walking and reading/using computer, respectively. When in outdoor home locations (e.g., yard and driveway) women demonstrated higher levels of MVPA, whereas men demonstrated higher levels of MVPA when in outdoor park settings (ps < .05). Men but not women demonstrated higher levels of MVPA in settings with a greater degree of perceived greenness and vegetation (p < .05). CONCLUSIONS The current study shows how EMA via mobile phones and accelerometers can be combined to offer an innovative approach to assess the contexts of adults' daily physical and sedentary activity. Future studies could consider utilizing this method in more representative samples to gather context-specific information to inform the development of physical activity interventions.
Collapse
|
Research Support, Non-U.S. Gov't |
10 |
49 |
14
|
Albinali F, Intille SS, Haskell W, Rosenberger M. Using Wearable Activity Type Detection to Improve Physical Activity Energy Expenditure Estimation. PROCEEDINGS OF THE ... ACM INTERNATIONAL CONFERENCE ON UBIQUITOUS COMPUTING . UBICOMP (CONFERENCE) 2010; 2010:311-320. [PMID: 30191204 PMCID: PMC6122605 DOI: 10.1145/1864349.1864396] [Citation(s) in RCA: 46] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Academic Contribution Register] [Indexed: 10/19/2022]
Abstract
Accurate, real-time measurement of energy expended during everyday activities would enable development of novel health monitoring and wellness technologies. A technique using three miniature wearable accelerometers is presented that improves upon state-of-the-art energy expenditure (EE) estimation. On a dataset acquired from 24 subjects performing gym and household activities, we demonstrate how knowledge of activity type, which can be automatically inferred from the accelerometer data, can improve EE estimates by more than 15% when compared to the best estimates from other methods.
Collapse
|
research-article |
15 |
46 |
15
|
Beaudin JS, Intille SS, Morris ME. To track or not to track: user reactions to concepts in longitudinal health monitoring. J Med Internet Res 2007; 8:e29. [PMID: 17236264 PMCID: PMC1794006 DOI: 10.2196/jmir.8.4.e29] [Citation(s) in RCA: 42] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Academic Contribution Register] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND Advances in ubiquitous computing, smart homes, and sensor technologies enable novel, longitudinal health monitoring applications in the home. Many home monitoring technologies have been proposed to detect health crises, support aging-in-place, and improve medical care. Health professionals and potential end users in the lay public, however, sometimes question whether home health monitoring is justified given the cost and potential invasion of privacy. OBJECTIVE The aim of the study was to elicit specific feedback from health professionals and laypeople about how they might use longitudinal health monitoring data for proactive health and well-being. METHODS Interviews were conducted with 8 health professionals and 26 laypeople. Participants were asked to evaluate mock data visualization displays that could be generated by novel home monitoring systems. The mock displays were used to elicit reactions to longitudinal monitoring in the home setting as well as what behaviors, events, and physiological indicators people were interested in tracking. RESULTS Based on the qualitative data provided by the interviews, lists of benefits of and concerns about health tracking from the perspectives of the practitioners and laypeople were compiled. Variables of particular interest to the interviewees, as well as their specific ideas for applications of collected data, were documented. CONCLUSIONS Based upon these interviews, we recommend that ubiquitous "monitoring" systems may be more readily adopted if they are developed as tools for personalized, longitudinal self-investigation that help end users learn about the conditions and variables that impact their social, cognitive, and physical health.
Collapse
|
Research Support, Non-U.S. Gov't |
18 |
42 |
16
|
Dunton GF, Intille SS, Wolch J, Pentz MA. Children's perceptions of physical activity environments captured through ecological momentary assessment: a validation study. Prev Med 2012; 55:119-21. [PMID: 22659225 DOI: 10.1016/j.ypmed.2012.05.015] [Citation(s) in RCA: 33] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Academic Contribution Register] [Received: 01/11/2012] [Revised: 04/18/2012] [Accepted: 05/22/2012] [Indexed: 11/24/2022]
Abstract
OBJECTIVE This study used ecological momentary assessment (EMA) to investigate whether children's perceptions of physical activity (PA) settings correspond with (1) parents' perceptions of neighborhood characteristics (convergent construct validity) and (2) children's level of PA in those settings (concurrent criterion validity). METHODS Low-to-middle income, ethnically-diverse children (N=108) (ages 9-13) living in Southern California participated in 8 days of EMA during non-school time. EMA measured current activity type (e.g., sports/exercise, TV watching) and perceptions of the current setting (i.e., vegetation, traffic, safety). The Neighborhood Environment Walkability Survey (NEWS) assessed parents' perceptions of neighborhood characteristics. EMA responses were time-matched to moderate-to-vigorous physical activity (MVPA) (measured by accelerometer) in the 30 min before and after each EMA survey. Data were collected in 2009-2010. RESULTS Children's perceptions of vegetation and traffic in PA settings corresponded with parents' perceptions of the aesthetics (OR=2.21, 95% CI=1.04-4.73) and traffic (OR=2.64, 95% CI=1.31-5.30) in neighborhood environment, respectively. MVPA minutes were higher in settings perceived by children to have less traffic (β=3.47, p<.05). CONCLUSIONS This work provides initial support for the construct and criterion validity of EMA-based measures of children's perceptions of their PA environments.
Collapse
|
Research Support, N.I.H., Extramural |
13 |
33 |
17
|
Dunton GF, Rothman AJ, Leventhal AM, Intille SS. How intensive longitudinal data can stimulate advances in health behavior maintenance theories and interventions. Transl Behav Med 2021; 11:281-286. [PMID: 31731290 DOI: 10.1093/tbm/ibz165] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Academic Contribution Register] [Indexed: 11/13/2022] Open
Abstract
Interventions that promote long-term maintenance of behaviors such as exercise, healthy eating, and avoidance of tobacco and excessive alcohol are critical to reduce noncommunicable disease burden. Theories of health behavior maintenance tend to address reactive (i.e., automatic) or reflective (i.e., deliberative) decision-making processes, but rarely both. Progress in this area has been stalled by theories that say little about when, why, where, and how reactive and reflective systems interact to promote or derail a positive health behavior change. In this commentary, we discuss factors influencing the timing and circumstances under which an individual may shift between the two systems such as (a) limited availability of psychological assets, (b) interruption in exposure to established contextual cues, and (c) lack of intrinsic or appetitive motives. To understand the putative factors that regulate the interface between these systems, research methods are needed that are able to capture properties such as (a) fluctuation over short periods of time, (b) change as a function of time, (c) context dependency, (d) implicit and physiological channels, and (e) idiographic phenomenology. These properties are difficult to assess with static, cross-sectional, laboratory-based, or retrospective research methods. We contend that intensive longitudinal data (ILD) collection and analytic strategies such as smartphone and sensor-based real-time activity and location monitoring, ecological momentary assessment (EMA), machine learning, and systems modeling are well-positioned to capture and interpret within-person shifts between reactive and reflective systems underlying behavior maintenance. We conclude with examples of how ILD can accelerate the development of theories and interventions to sustain health behavior over the long term.
Collapse
|
Research Support, N.I.H., Extramural |
4 |
32 |
18
|
Nawyn J, Intille SS, Larson K. Embedding Behavior Modification Strategies into a Consumer Electronic Device: A Case Study. LECTURE NOTES IN COMPUTER SCIENCE 2006. [DOI: 10.1007/11853565_18] [Citation(s) in RCA: 31] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Academic Contribution Register] [Indexed: 12/31/2022]
|
|
19 |
31 |
19
|
Dunton GF, Intille SS, Wolch J, Pentz MA. Investigating the impact of a smart growth community on the contexts of children's physical activity using Ecological Momentary Assessment. Health Place 2012; 18:76-84. [PMID: 22243909 DOI: 10.1016/j.healthplace.2011.07.007] [Citation(s) in RCA: 31] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Academic Contribution Register] [Received: 04/11/2011] [Revised: 07/05/2011] [Accepted: 07/17/2011] [Indexed: 11/17/2022]
Abstract
This quasi-experimental research used Ecological Momentary Assessment with electronic surveys delivered through mobile phones to determine whether children change the type of contexts (i.e., settings) where they engage in physical activity after a recent move to a smart growth (SG) community in the U.S. as compared to children living in conventional low-to-medium density U.S. suburban communities (controls). SG vs. control children engaged in a greater proportion of physical activity bouts with friends, a few blocks from home, and at locations to which they walked. Over six months, the proportion of physical activity bouts reported at home (indoors) and in high traffic locations decreased among SG but not control children. Six-month increases in daily moderate-to-vigorous physical activity did not significantly differ by group. Children might have altered the type of contexts where they engage in physical activity after moving to SG communities, yet more time may be necessary for these changes to impact overall physical activity.
Collapse
|
Research Support, Non-U.S. Gov't |
13 |
31 |
20
|
Spilsbury JC, Patel SR, Morris N, Ehayaei A, Intille SS. Household chaos and sleep-disturbing behavior of family members: results of a pilot study of African American early adolescents. Sleep Health 2017; 3:84-89. [PMID: 28346162 PMCID: PMC5373486 DOI: 10.1016/j.sleh.2016.12.006] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Academic Contribution Register] [Received: 09/12/2016] [Revised: 11/30/2016] [Accepted: 12/23/2016] [Indexed: 01/09/2023]
Abstract
BACKGROUND Although disorganized, chaotic households have been linked to poorer sleep outcomes, how household chaos actually manifests itself in the behaviors of others around the bedtime of a child or adolescent is not well understood. OBJECTIVE To determine whether household chaos was associated with specific, nightly sleep-disturbing activities of adolescents' family members. DESIGN Longitudinal study. PARTICIPANTS Twenty-six African American or multiethnic early adolescent (ages 11-12 years) and parent dyads, recruited from local schools and social-service agencies in greater Cleveland, OH. MEASUREMENTS Over 14 days, each night at bedtime, adolescents identified family-member activities keeping them awake or making it difficult to sleep by using a smart phone-administered survey. Household organization was assessed via parent-completed, validated instruments. A generalized linear mixed model examined associations between each activity and household-organization measures. RESULTS Adjusted for the effect of school being in session the next day, an increasingly chaotic household was associated with increased odds of household members disturbing adolescents' efforts to fall asleep by watching TV/listening to music (odds ratio [OR]=1.8, 95% confidence interval [CI]=1.2-3.2), phoning/texting (OR=1.7, 95% CI =1.2-2.9), or having friends/relatives over visiting at the home (OR=1.6, 95% CI =1.0-3.0). Conversely, a more chaotic household was associated with decreased odds of adolescents reporting that "nothing" was keeping them awake or making it more difficult to sleep (OR=0.6, 95% CI =0.4-0.8). Enforced sleep rules were inconsistently associated with sleep-disturbing behaviors. CONCLUSION Improving early-adolescent sleep may benefit from considering the nighttime behavior of all household members and encouraging families to see that improving early-adolescent sleep requires the household's participation.
Collapse
|
Research Support, N.I.H., Extramural |
8 |
29 |
21
|
Hiremath SV, Intille SS, Kelleher A, Cooper RA, Ding D. Detection of physical activities using a physical activity monitor system for wheelchair users. Med Eng Phys 2014; 37:68-76. [PMID: 25465284 DOI: 10.1016/j.medengphy.2014.10.009] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Academic Contribution Register] [Received: 03/15/2014] [Revised: 09/12/2014] [Accepted: 10/18/2014] [Indexed: 10/24/2022]
Abstract
Availability of physical activity monitors for wheelchair users can potentially assist these individuals to track regular physical activity (PA), which in turn could lead to a healthier and more active lifestyle. Therefore, the aim of this study was to develop and validate algorithms for a physical activity monitoring system (PAMS) to detect wheelchair based activities. The PAMS consists of a gyroscope based wheel rotation monitor (G-WRM) and an accelerometer device (wocket) worn on the upper arm or on the wrist. A total of 45 persons with spinal cord injury took part in the study, which was performed in a structured university-based laboratory environment, a semi-structured environment at the National Veterans Wheelchair Games, and in the participants' home environments. Participants performed at least ten PAs, other than resting, taken from a list of PAs. The classification performance for the best classifiers on the testing dataset for PAMS-Arm (G-WRM and wocket on upper arm) and PAMS-Wrist (G-WRM and wocket on wrist) was 89.26% and 88.47%, respectively. The outcomes of this study indicate that multi-modal information from the PAMS can help detect various types of wheelchair-based activities in structured laboratory, semi-structured organizational, and unstructured home environments.
Collapse
|
Validation Study |
11 |
28 |
22
|
Intille SS, Albinali F, Mota S, Kuris B, Botana P, Haskell WL. Design of a wearable physical activity monitoring system using mobile phones and accelerometers. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2012; 2011:3636-9. [PMID: 22255127 DOI: 10.1109/iembs.2011.6090611] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Academic Contribution Register] [Indexed: 11/07/2022]
Abstract
This paper describes the motivation for, and overarching design of, an open-source hardware and software system to enable population-scale, longitudinal measurement of physical activity and sedentary behavior using common mobile phones. The "Wockets" data collection system permits researchers to collect raw motion data from participants who wear multiple small, comfortable sensors for 24 hours per day, including during sleep, and monitor data collection remotely.
Collapse
|
Research Support, N.I.H., Extramural |
13 |
26 |
23
|
Beaudin JS, Intille SS, Munguia Tapia E, Rockinson R, Morris ME. Context-Sensitive Microlearning of Foreign Language Vocabulary on a Mobile Device. LECTURE NOTES IN COMPUTER SCIENCE 2007. [DOI: 10.1007/978-3-540-76652-0_4] [Citation(s) in RCA: 25] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Academic Contribution Register] [Indexed: 12/12/2022]
|
|
18 |
25 |
24
|
Mannini A, Intille SS. Classifier Personalization for Activity Recognition Using Wrist Accelerometers. IEEE J Biomed Health Inform 2018; 23:1585-1594. [PMID: 30222588 DOI: 10.1109/jbhi.2018.2869779] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Academic Contribution Register] [Indexed: 11/06/2022]
Abstract
Intersubject variability in accelerometer-based activity recognition may significantly affect classification accuracy, limiting a reliable extension of methods to new users. In this paper, we propose an approach for personalizing classification rules to a single person. We demonstrate that the method improves activity detection from wrist-worn accelerometer data on a four-class recognition problem of interest to the exercise science community, where classes are ambulation, cycling, sedentary, and other. We extend a previously published activity classification method based on support vector machines so that it estimates classification uncertainty. Uncertainty is used to drive data label requests from the user, and the resulting label information is used to update the classifier. Two different datasets-one from 33 adults with 26 activity types, and another from 20 youth with 23 activity types-were used to evaluate the method using leave-one-subject-out and leave-one-group-out cross validation. The new method improved overall recognition accuracy up to 11% on average, with some large person-specific improvements (ranging from -2% to +36%). The proposed method is suitable for online implementation supporting real-time recognition systems.
Collapse
|
Research Support, Non-U.S. Gov't |
7 |
22 |
25
|
Jones M, Taylor A, Liao Y, Intille SS, Dunton GF. REAL-TIME SUBJECTIVE ASSESSMENT OF PSYCHOLOGICAL STRESS: ASSOCIATIONS WITH OBJECTIVELY-MEASURED PHYSICAL ACTIVITY LEVELS. PSYCHOLOGY OF SPORT AND EXERCISE 2017; 31:79-87. [PMID: 29151810 PMCID: PMC5685522 DOI: 10.1016/j.psychsport.2017.03.013] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Academic Contribution Register] [Indexed: 05/10/2023]
Abstract
Psychosocial stress may be a factor in the link between physical activity and obesity. This study examines how the daily experience of psychosocial stress influences physical activity levels and weight status in adults. This study reports temporally ordered relationships between sedentary, light, and moderate-to-vigorous physical activity levels and real-time reports of subjective psychosocial stress levels. Adults (n=105) wore an accelerometer and participated in an ecological momentary assessment (EMA) of stress by answering prompts on a mobile phone several times per day over 4 days. Subjective stress was negatively related to sedentary activity in the minutes immediately preceding and immediately following an EMA prompt. Light activity was positively associated with a subsequent EMA report of higher stress, but there were no observed associations between stress and moderate-to-vigorous activity. Real-time stress reports and accelerometer readings for the same 4-day period showed no association. Nor were there associations between real-time stress reports and weight status.
Collapse
|
research-article |
8 |
19 |