Investigating the day-level associations between affective variability and physical activity using ecological momentary assessment.

BACKGROUND: Understanding affect as a determinant of physical activity has gained increased attention in health behavior research. Fluctuations in affect intensity from moment-to-moment (i.e., affective variability) may interfere with cognitive and regulatory processes, making it difficult to engage in goal-directed behaviors such as physical activity. Preliminary evidence indicates that those with greater trait-level affective variability engage in lower levels of habitual physical activity. However, the extent to which daily fluctuations in affect variability are associated with same-day physical activity levels is unknown. This study used ecological momentary assessment (EMA) to investigate day-level associations between affective variability (i.e., within-subject variance) and physical activity. METHODS: Young adults (N = 231, M = 23.58 ± 3.02 years) provided three months of smartphone-based EMA and smartwatch-based activity data. Every two weeks, participants completed a 4-day EMA measurement burst (M = 5.17 ± 1.28 bursts per participant). Bursts consisted of hourly randomly-prompted EMA surveys assessing momentary positive-activated (happy, energetic), positive-deactivated (relaxed), negative-activated (tense, stressed), and negative-deactivated (sad, fatigued) affect. Participants continuously wore a smartwatch to measure physical activity across the three months. Mixed-effects location scale modeling examined the day-level associations of affective variability (i.e., positive-activated, positive-deactivated, negative-activated, and negative-deactivated) and physical activity, controlling for covariates such as mean levels of affect, between-subject effects of physical activity, time of day, day of week, day in study, and smartwatch wear time. RESULTS: There were 41,546 completed EMA surveys (M = 182.22 ± 69.82 per participant) included in the analyses. Above and beyond mean levels of affect, greater day-level variability in positive-activated affect was associated with greater physical activity on that same day compared to other days (τ = 0.01, p < .001), whereas greater day-level variability in negative-deactivated affect was associated with less physical activity on that same day compared to other days (τ = -0.01, p < .001). Day-level variability in positive-deactivated affect or negative-activated affect were not associated with day-level physical activity (ps > .05) CONCLUSIONS: Individuals were less active on days with greater variability in feeling sad and fatigued but more active on days with greater variability in feeling happy and energetic. Understanding the dynamic relationships of affective variability with day-level physical activity can strengthen physical activity interventions by considering how these processes differ within individuals and unfold within the context of daily life. Future research should examine causal pathways between affective variability and physical activity across the day.

Potential of social engagement for overcoming barriers to physical activity in individuals with spinal cord injury.

Introduction: Many barriers to physical activity (PA) exist for individuals with spinal cord injury (SCI). Social engagement may improve motivation to perform PA, which in turn may increase PA levels. This pilot study investigates how social engagement facilitated by mobile technology may reduce lack of motivation as a barrier to PA in individuals with SCI and demonstrates design implications for future technologies. Methods: A user-needs survey was conducted with participants in the community. We recruited 26 participants (16 individuals with SCI and 10 family members or peers). A participatory design process using semi-structured interviews was used to identify themes relating to PA barriers. Results: One theme related to PA barriers was lack of PA-focused forums to connect with peers. Participants with SCI considered connecting with other individuals with SCI more motivating than connecting with their family members. Another key finding was that participants with SCI did not perceive that personal fitness trackers were targeted towards wheelchair-based activities. Conclusions: Engagement and communication with peers who have similar functional mobility levels and life experiences can potentially improve motivation for PA; however, PA-motivational platforms are not tailored towards wheelchair-users. Our preliminary findings show that some individuals with SCI are not satisfied with current mobile-technologies for wheelchair-based PA.

The ILHBN: challenges, opportunities, and solutions from harmonizing data under heterogeneous study designs, target populations, and measurement protocols.

The ILHBN is funded by the National Institutes of Health to collaboratively study the interactive dynamics of behavior, health, and the environment using Intensive Longitudinal Data (ILD) to (a) understand and intervene on behavior and health and (b) develop new analytic methods to innovate behavioral theories and interventions. The heterogenous study designs, populations, and measurement protocols adopted by the seven studies within the ILHBN created practical challenges, but also unprecedented opportunities to capitalize on data harmonization to provide comparable views of data from different studies, enhance the quality and utility of expensive and hard-won ILD, and amplify scientific yield. The purpose of this article is to provide a brief report of the challenges, opportunities, and solutions from some of the ILHBN's cross-study data harmonization efforts. We review the process through which harmonization challenges and opportunities motivated the development of tools and collection of metadata within the ILHBN. A variety of strategies have been adopted within the ILHBN to facilitate harmonization of ecological momentary assessment, location, accelerometer, and participant engagement data while preserving theory-driven heterogeneity and data privacy considerations. Several tools have been developed by the ILHBN to resolve challenges in integrating ILD across multiple data streams and time scales both within and across studies. Harmonization of distinct longitudinal measures, measurement tools, and sampling rates across studies is challenging, but also opens up new opportunities to address cross-cutting scientific themes of interest.

Health behavior changes, such as prevention of suicidal thoughts and behaviors, smoking, drug use, and alcohol use; and the promotion of mental health, sleep, and physical activities, and decreases in sedentary behavior, are difficult to sustain. The ILHBN is a cooperative agreement network funded jointly by seven participating units within the National Institutes of Health to collaboratively study how factors that occur in individuals' everyday life and in their natural environment influence the success of positive health behavior changes. This article discusses how information collected using smartphones, wearables, and other devices can provide helpful active and passive reflections of the participants' extent of risk and resources at the moment for an extended period of time. However, successful engagement and retention of participants also require tailored adaptations of study designs, measurement tools, measurement intervals, study span, and device choices that create hurdles in integrating (harmonizing) data from multiple studies. We describe some of the challenges, opportunities, and solutions that emerged from harmonizing intensive longitudinal data under heterogeneous study and participant characteristics within the ILHBN, and share some tools and recommendations to facilitate future data harmonization efforts.

Examining Whether Physical Activity Location Choices Were Associated With Weekly Physical Activity Maintenance Across 13 Months of the COVID-19 Pandemic in Emerging Adults.

BACKGROUND: Recent studies have shown potentially detrimental effects of the COVID-19 pandemic on physical activity (PA) in emerging adults (ages 18-29 y). However, studies that examined the effects of COVID-19 on PA location choices and maintenance for this age group remain limited. The current study investigated changes in PA location choices across 13 months during the pandemic and their associations with PA maintenance in this population. METHODS: Emerging adults (N = 197) living in the United States completed weekly survey on personal smartphones (May 2020-June 2021) regarding PA location choices and maintenance. Mixed-effects models examined the main effects of PA location choice and its interaction with weeks into the pandemic on participants' PA maintenance. RESULTS: On a given week, participants performing PA on roads/sidewalks or at parks/open spaces were 1½ and 2 times as likely to maintain PA levels, respectively. Moreover, after September 2021, weeks when individuals performed PA on roads/sidewalks had a protective effect on PA maintenance. CONCLUSIONS: Performing PA on roads/sidewalks and at parks/open spaces was associated with PA maintenance during the COVID-19 pandemic. PA promotion and intervention efforts for emerging adults during large-scale disruptions to daily life should focus on providing programmed activities in open spaces to maintain their PA levels.

How acute affect dynamics impact longitudinal changes in physical activity among children.

Research examined how acute affect dynamics, including stability and context-dependency, contribute to changes in children's physical activity levels as they transition from late-childhood to early-adolescence. Children (N = 151) (ages 8-12 years at baseline) participated in an ecological momentary assessment and accelerometry study with six semi-annual bursts (7 days each) across three years. A two-stage mixed-effects multiple location-scale model tested random intercept, variance, and slope estimates for positive affect as predictors of moderate-to-vigorous physical activity (MVPA). Multi-year declines in MVPA were greater for children who had greater subject-level variance in positive affect. Children who experienced more positive affect when alone did not experience steeper declines in physical activity. Interventions aiming for long-term modifications in children's physical activity may focus on buffering the effects of within-day fluctuations in affect or tailoring programs to fit the needs of "acute dynamic process phenotypes."

Relationship between pain, fatigue, and physical activity levels during a technology-based physical activity intervention.

Objective: The majority of individuals with spinal cord injury (SCI) experience chronic pain. Chronic pain can be difficult to manage because of variability in the underlying pain mechanisms. More insight regarding the relationship between pain and physical activity (PA) is necessary to understand pain responses during PA. The objective of this study is to explore possible relationships between PA levels and secondary conditions including pain and fatigue.Design: Prospective cohort analysis of a pilot study.Setting: Community.Participants: Twenty individuals with SCI took part in the study, and sixteen completed the study.Interventions: Mobile-health (mHealth) based PA intervention for two-months during the three-month study.Outcome measures: Chronic Pain Grade Scale (CPGS) questionnaire, The Wheelchair User's Shoulder Pain Index (WUSPI), Fatigue Severity Scale (FSS), and PA levels measured by the mHealth system.Results: A positive linear relationship was found between light-intensity PA and task-specific pain. However, the relationship between moderate-intensity PA and pain interference was best represented by a curvilinear relationship (polynomial regression of second order). Light-intensity PA showed positive, linear correlation with fatigue at baseline. Moderate-intensity PA was not associated with fatigue during any phase of the study.Conclusion: Our results indicated that PA was associated with chronic pain, and the relationship differed based on intensity and amount of PA performed. Further research is necessary to refine PA recommendations for individuals with SCI who experience chronic pain.Trial registration: ClinicalTrials.gov identifier: NCT03773692.

How intensive longitudinal data can stimulate advances in health behavior maintenance theories and interventions.

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.

Real-Time Data Collection to Examine Relations Between Physical Activity and Affect in Adults With Mental Illness.

Adults with serious mental illness engage in limited physical activity, which contributes to significant health disparities. This study explored the use of both ecological momentary assessments (EMAs) and activity trackers in adults with serious mental illness to examine the bidirectional relationship between activity and affect with multilevel modeling. Affective states were assessed up to seven times per day using EMA across 4 days. The participants (n = 20) were equipped with a waist-worn accelerometer to measure moderate to vigorous physical activity. The participants had a mean EMA compliance rate of 88.3%, and over 90% of completed EMAs were matched with 30-min windows of accelerometer wear. The participants who reported more positive affect than others had a higher probability of engaging in moderate to vigorous physical activity. Engaging in more moderate to vigorous physical activity than one's usual was associated with more negative affect. This study begins to address the effect of momentary mood on physical activity in a population of adults that is typically difficult to reach.

Correction: Mobile health-based physical activity intervention for individuals with spinal cord injury in the community: A pilot study.

[This corrects the article DOI: 10.1371/journal.pone.0223762.].

Mobile health-based physical activity intervention for individuals with spinal cord injury in the community: A pilot study.

Low levels of physical activity (PA) and high levels of sedentary behavior in individuals with spinal cord injury (SCI) have been associated with secondary conditions such as pain, fatigue, weight gain, and deconditioning. One strategy for promoting regular PA is to provide people with an accurate estimate of everyday PA level. The objective of this research was to use a mobile health-based PA measurement system to track PA levels of individuals with SCI in the community and provide them with a behavior-sensitive, just-in-time-adaptive intervention (JITAI) to improve their PA levels. The first, second, and third phases of the study, each with a duration of one month, involved collecting baseline PA levels, providing near-real-time feedback on PA level (PA Feedback), and providing PA Feedback with JITAI, respectively. PA levels in terms of energy expenditure in kilocalories, and minutes of light- and moderate- or vigorous-intensity PA were assessed by an activity monitor during the study. Twenty participants with SCI took part in this research study with a mean (SD) age of 39.4 (12.8) years and 12.4 (12.5) years since injury. Sixteen participants completed the study. Sixteen were male, 16 had paraplegia, and 12 had complete injury. Within-participant comparisons indicated that only two participants had higher energy expenditure (>10%) or lower energy expenditure (<-10%) during PA Feedback with JITAI compared to the baseline. However, eleven participants (69.0%) had higher light- and/or moderate-intensity PA during PA Feedback with JITAI compared to the baseline. To our knowledge, this is the first study to test a PA JITAI for individuals with SCI that responds automatically to monitored PA levels. The results of this pilot study suggest that a sensor-enabled mobile JITAI has potential to improve PA levels of individuals with SCI. Future research should investigate the efficacy of JITAI through a clinical trial.

Investigating Health Risk Environments in Housing Programs for Young Adults: Protocol for a Geographically Explicit Ecological Momentary Assessment Study.

BACKGROUND: Young adults who experience homelessness are exposed to environments that contribute to risk behavior. However, few studies have examined how access to housing may affect the health risk behaviors of young adults experiencing homelessness. OBJECTIVE: This paper describes the Log My Life study that uses an innovative, mixed-methods approach based on geographically explicit ecological momentary assessment (EMA) through cell phone technology to understand the risk environment of young adults who have either enrolled in housing programs or are currently homeless. METHODS: For the quantitative arm, study participants age 18-27 respond to momentary surveys via a smartphone app that collects geospatial information repeatedly during a 1-week period. Both EMAs (up to 8 per day) and daily diaries are prompted to explore within-day and daily variations in emotional affect, context, and health risk behavior, while also capturing infrequent risk behaviors such as sex in exchange for goods or services. For the qualitative arm, a purposive subsample of participants who indicated engaging in risky behaviors are asked to complete an in-depth qualitative interview using an interactive, personalized geospatial map rendering of EMA responses. RESULTS: Recruitment began in June of 2017. To date, 170 participants enrolled in the study. Compliance with EMA and daily diary surveys was generally high. In-depth qualitative follow-ups have been conducted with 15 participants. We expect to recruit 50 additional participants and complete analyses by September of 2019. CONCLUSIONS: Mixing the quantitative and qualitative arms in this study will provide a more complete understanding of differences in risk environments between homeless and housed young adults. Furthermore, this approach can improve recall bias and enhance ecological validity. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/12112.

Classifier Personalization for Activity Recognition Using Wrist Accelerometers.

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.

Affective response during physical activity: Within-subject differences across phases of behavior change.

OBJECTIVE: Affective response during physical activity may be a key factor reinforcing future behavior. However, little is known about how affective responses during physical activity may differ across phases of behavior change. This study used real-time Ecological Momentary Assessment (EMA) to examine within-subject differences in affective response during physical activity in daily life as individuals transitioned across phases of behavior change. METHOD: A sample of 115 adults (M = 41.0 years, 74% female) participated in an intensive longitudinal study with measurement bursts at 0, 6, and 12-months. Each burst consisted of 8 randomly-prompted EMA occasions per day across 4 days. EMA self-report items assessed current activity level (i.e., physical activity or nonphysical activity), and positive and negative affect. Questionnaires measured phase of behavior change (e.g., preaction [no regular physical activity], action [regular physical activity <6 months], and maintenance [regular physical activity ≥6 months]) at each burst. Three-level (Level-1 = occasion, Level-2 = burst, Level-3 = person) linear regression models tested Phase of Change (Level-2, within-subject) × Physical Activity Level (Level-1, within-subject) interactions controlling for day of week, time of day, and sex. RESULTS: Positive affective response during physical activity (vs. nonphysical activity) was higher when individuals were in preaction phases (vs. action). Negative affective response during physical activity (vs. nonphysical activity) was lower when individuals were in the maintenance phase (vs. action). CONCLUSIONS: Long-term maintenance of physical activity may be particularly challenging, given the lack of positive reinforcement that is thought to be needed to sustain behavior. (PsycINFO Database Record

Response patterns and intra-dyadic factors related to compliance with ecological momentary assessment among mothers and children.

Ecological momentary assessment (EMA) is a real-time sampling strategy that may address limitations in health research, such as the inability to examine how processes unfold on a daily basis. However, EMA studies are prone to limited data availability due to difficulties in implementing sophisticated protocols and systematic non-compliance with prompts, resulting in biased estimates and limited statistical power. The objectives of this study were to describe the availability of data, to examine response patterns, and to analyze factors related to EMA prompt compliance in a dyadic EMA study with mothers and children. Participants (N = 404) each received up to eight EMA prompts (i.e., audible pings) per day for a total of 7 days. Each EMA survey consisted of items assessing affect, perceived stress, and social context. Participants responded to approximately 80% (range: 3.4%-100%) of prompted EMA surveys, and completed 92.6% of surveys once started. Mothers and children identifying as Hispanic, as well as mothers in lower-income households, were less likely to comply with any given EMA prompt. Participant dyads were more likely to comply with prompts when they were together. Understanding factors related to systematic EMA prompt non-compliance is an important step to reduce the likelihood of biased estimates and improve statistical power. Socioeconomic factors may impede mothers' compliance with EMA protocols. Furthermore, mothers' presence and involvement may enhance children's compliance with EMA protocols.

Validity of proximity sensor-based wear-time detection using the ActiGraph GT9X.

Our study investigated the performance of proximity sensor-based wear-time detection using the GT9X under laboratory and free-living settings. Fifty-two volunteers (23.2 ± 3.8 y; 23.2 ± 3.7 kg/m2) participated in either a laboratory or free-living protocol. Lab participants wore and removed a wrist-worn GT9X on 3-5 occasions during a 3-hour directly observed activity protocol. The 2-day free-living protocol used an independent temperature sensor and self-report as the reference to determine if wrist and hip-worn GT9X accurately determined wear (i.e., sensitivity) and non-wear (i.e., specificity). Free-living estimates of wear/non-wear were also compared to Troiano 2007 and Choi 2012 wear/non-wear algorithms. In lab, sensitivity and specificity of the wrist-worn GT9X in detecting total minutes of wear-on and off was 93% and 49%, respectively. The GT9X detected wear-off more often than wear-on, but with a greater margin of error (4.8 ± 11.6 vs. 1.4 ± 1.4 min). In the free-living protocol, wrist and hip-worn GT9X's yielded sensitivity and specificity of 72 and 90% and 84 and 92%, respectively. GT9X estimations had inferior sensitivity but superior specificity to Troiano 2007 and Choi 2012 algorithms. Due to inaccuracies, it may not be advisable to singularly use the proximity-sensor-based wear-time detection method to detect wear-time.

REAL-TIME SUBJECTIVE ASSESSMENT OF PSYCHOLOGICAL STRESS: ASSOCIATIONS WITH OBJECTIVELY-MEASURED PHYSICAL ACTIVITY LEVELS.

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.

Household chaos and sleep-disturbing behavior of family members: results of a pilot study of African American early adolescents.

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.

Activity Recognition in Youth Using Single Accelerometer Placed at Wrist or Ankle.

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.

Estimation of Energy Expenditure for Wheelchair Users Using a Physical Activity Monitoring System.

OBJECTIVE: To develop and evaluate energy expenditure (EE) estimation models for a physical activity monitoring system (PAMS) in manual wheelchair users with spinal cord injury (SCI). DESIGN: Cross-sectional study. SETTING: University-based laboratory environment, a semistructured environment at the National Veterans Wheelchair Games, and the participants' home environments. PARTICIPANTS: Volunteer sample of manual wheelchair users with SCI (N=45). INTERVENTION: Participants were asked to perform 10 physical activities (PAs) of various intensities from a list. The PAMS consists of a gyroscope-based wheel rotation monitor (G-WRM) and an accelerometer device worn on the upper arm or on the wrist. Criterion EE using a portable metabolic cart and raw sensor data from PAMS were collected during each of these activities. MAIN OUTCOME MEASURES: Estimated EE using custom models for manual wheelchair users based on either the G-WRM and arm accelerometer (PAMS-Arm) or the G-WRM and wrist accelerometer (PAMS-Wrist). RESULTS: EE estimation performance for the PAMS-Arm (average error ± SD: -9.82%±37.03%) and PAMS-Wrist (-5.65%±32.61%) on the validation dataset indicated that both PAMS-Arm and PAMS-Wrist were able to estimate EE for a range of PAs with <10% error. Moderate to high intraclass correlation coefficients (ICCs) indicated that the EE estimated by PAMS-Arm (ICC3,1=.82, P<.05) and PAMS-Wrist (ICC3,1=.89, P<.05) are consistent with the criterion EE. CONCLUSIONS: Availability of PA monitors can assist wheelchair users to track PA levels, leading toward a healthier lifestyle. The new models we developed can estimate PA levels in manual wheelchair users with SCI in laboratory and community settings.