Brain activation in response to personalized behavioral and physiological feedback from self-monitoring technology: pilot study

Background: The recent surge in commercially available wearable technology has allowed real-time self-monitoring of behavior (eg, physical activity) and physiology (eg, glucose levels). However, there is limited neuroimaging work (ie, functional magnetic resonance imaging [fMRI]) to identify how people’s brains respond to receiving this personalized health feedback and how this impacts subsequent behavior. Objective: Identify regions of the brain activated and examine associations between activation and behavior. Methods: This was a pilot study to assess physical activity, sedentary time, and glucose levels over 14 days in 33 adults (aged 30 to 60 years). Extracted accelerometry, inclinometry, and interstitial glucose data informed the construction of personalized feedback messages (eg, average number of steps per day). These messages were subsequently presented visually to participants during fMRI. Participant physical activity levels and sedentary time were assessed again for 8 days following exposure to this personalized feedback. Results: Independent tests identified significant activations within the prefrontal cortex in response to glucose feedback compared with behavioral feedback (P<.001). Reductions in mean sedentary time (589.0 vs 560.0 minutes per day, P=.014) were observed. Activation in the subgyral area had a moderate correlation with minutes of moderate-to-vigorous physical activity (r=0.392, P=.043). Conclusion: Presenting personalized glucose feedback resulted in significantly more brain activation when compared with behavior. Participants reduced time spent sedentary at follow-up. Research on deploying behavioral and physiological feedback warrants further investigation

Metadata correction: Brain activation in response to personalized behavioral and physiological feedback from self-monitoring technology: pilot study

[This corrects the article DOI: 10.2196/jmir.8890.]

A novel algorithm for determining the contextual characteristics of movement behaviors by combining accelerometer features and wireless beacons: development and implementation

Background: Unfortunately, global efforts to promote “how much” physical activity people should be undertaking have been largely unsuccessful. Given the difficulty of achieving a sustained lifestyle behavior change, many scientists are re-examining their approaches. One such approach is to focus on understanding the context of the lifestyle behavior (i.e., where, when, and with whom) with a view to identifying promising intervention targets. Objective: The aim of this study was to develop and implement an innovative algorithm to determine “where” physical activity occurs using proximity sensors coupled with a widely used physical activity monitor. Methods: A total of 19 Bluetooth beacons were placed in fixed locations within a multilevel, mixed-use building. In addition, 4 receiver-mode sensors were fitted to the wrists of a roving technician who moved throughout the building. The experiment was divided into 4 trials with different walking speeds and dwelling times. The data were analyzed using an original and innovative algorithm based on graph generation and Bayesian filters. Results: Linear regression models revealed significant correlations between beacon-derived location and ground-truth tracking time, with intraclass correlations suggesting a high goodness of fit (R2=.9780). The algorithm reliably predicted indoor location, and the robustness of the algorithm improved with a longer dwelling time (>100 s; error <10%, R2=.9775). Increased error was observed for transitions between areas due to the device sampling rate, currently limited to 0.1 Hz by the manufacturer. Conclusions: This study shows that our algorithm can accurately predict the location of an individual within an indoor environment. This novel implementation of “context sensing” will facilitate a wealth of new research questions on promoting healthy behavior change, the optimization of patient care, and efficient health care planning (e.g., patient-clinician flow, patient-clinician interaction)

Measurement invariance of TGMD-3 in children with and without mental and behavioral disorders

This study evaluated whether the Test of Gross Motor Development 3 (TGMD-3) is a reliable tool to compare children with and without mental and behavioural disorders across gross motor skill domains. A total of 1075 children (aged 3-11 years), 98 with mental and behavioural disorders and 977 without (typically developing), were included in the analyses. The TGMD-3 evaluates fundamental gross motor skills of children across two domains: locomotor skills and ball skills. Two independent testers simultaneously observed children’s performances (agreement over 95%). Each child completed one practice and then two formal trials. Scores were recorded only during the two formal trials. Multigroup Confirmatory Factor Analysis tested the assumption of TGMD-3 measurement invariance across disability groups. According to the magnitude of changes in Root Mean Square Error of Approximation and Comparative Fit Index between nested models, the assumption of measurement invariance across groups was valid. Loadings of the manifest indicators on locomotor and ball skills were significant (p < .001) in both groups. Item Response Theory analysis showed good reliability results across locomotor and the ball skills full latent traits. The present study confirmed the factorial structure of TGMD-3 and demonstrated its feasibility across normally developing children and children with mental and behavioural disorders. These findings provide new opportunities for understanding the effect of specific intervention strategies on this population

Estimating cut points: A simple method for new wearables

Wearable technology is readily available for continuous assessment due to a growing number of commercial devices with increased data capture capabilities. However, many commercial devices fail to support suitable parameters (cut points) derived from the literature to help quantify physical activity (PA) due to differences in manufacturing. A simple metric to estimate cut points for new wearables is needed to aid data analysis. Objective: The purpose of this pilot study was to investigate a simple methodology to determine cut points based on ratios between sedentary behaviour (SB) and PA intensities for a new wrist worn device (PRO-Diary™) by comparing its output to a validated and well characterised ‘gold standard’ (ActiGraph™). Study design: Twelve participants completed a semi-structured (four-phase) treadmill protocol encompassing SB and three PA intensity levels (light, moderate, vigorous). The outputs of the devices were compared accounting for relative intensity. Results: Count ratios (6.31, 7.68, 4.63, 3.96) were calculated to successfully determine cut-points for the new wrist worn wearable technology during SB (0–426) as well as light (427–803), moderate (804–2085) and vigorous (≥2086) activities, respectively. Conclusion: Our findings should be utilised as a primary reference for investigations seeking to use new (wrist worn) wearable technology similar to that used here (i.e., PRO-Diary™) for the purposes of quantifying SB and PA intensities. The utility of count ratios may be useful in comparing devices or SB/PA values estimated across different studies. However, a more robust examination is required for different devices, attachment locations and on larger/diverse cohorts

A dental stool with chest support reduces lower back muscle activation

Activation of back musculature during work tasks leads to fatigue and potential injury. This is especially prevalent in dentists who perform much of their work from a seated position. We examined the use of an ergonomic dental stool with mid-sternum chest support for reducing lower back muscle activation. Electromyography of lower back extensors was assessed from 30 dental students for 20 s during three conditions in random order: (a) sitting upright at 90° of hip flexion on a standard stool, (b) leaning forward at 80° of hip flexion on a standard stool, and (c) leaning forward at 80° of hip flexion while sitting on an ergonomic stool. Muscular activity of the back extensors was reduced when using the ergonomic stool compared to the standard stool, by 33-50% (p < 0.01). This suggests a potential musculoskeletal benefit with use of a dental stool with mid-sternum chest support

Physical activity profile of old order Amish, Mennonite, and contemporary children

Purpose: This study explored the influence of modernity on the physical activity behaviors (e.g., intensity and timing) of children. Methods: Children aged 8-13 yr living a traditional lifestyle (Old Order Amish [OOA], n = 68; Old Order Mennonite [OOM], n = 120) were compared with children living a contemporary lifestyle (rural Saskatchewan [RSK], n = 132; urban Saskatchewan [USK], n = 93). Physical activity was objectively assessed for seven consecutive days using Actigraph 7164 accelerometers. Custom software was used to reduce the raw accelerometer data into standardized outcome variables. Results: On weekdays, there were group differences in moderate physical activity between all lifestyle groups (OOA > OOM > USK > RSK). On the weekend, the group differences in moderate physical activity persisted between, but not within, lifestyle groups (OOA = OOM > USK = RSK). During school hours, all groups had similar activity and inactivity periods; however, they differed in magnitude, with the OOA and OOM being both more sedentary and more active. In comparison with the children in school, the OOA and the OOM children had 44% lower sedentary time out of school compared with only 15% lower for RSK and USK children. Conclusions: Although cross sectional, these data suggest that contemporary/modern living is associated with lower levels of moderate-and vigorous-intensity physical activity compared with lifestyles representative of earlier generations. Analyzing the physical activity and inactivity patterns of traditional lifestyle groups such as the OOA and the OOM can provide valuable insight into the quantity and quality of physical activity necessary to promote health. Copyright © 2010 by the American College of Sports Medicine

Translations equations to compare ActiGraph GT3X and Actical accelerometers activity counts

Background: This study aimed to develop a translation equation to enable comparison between Actical and ActiGraph GT3X accelerometer counts recorded minute by minute. Methods: Five males and five females of variable height, weight, body mass index and age participated in this investigation. Participants simultaneously wore an Actical and an ActiGraph accelerometer for two days. Conversion algorithms and R2 were calculated day by day for each subject between the omnidirectional Actical and three different ActiGraph (three-dimensional) outputs: 1) vertical direction, 2) combined vector, and 3) a custom vector. Three conversion algorithms suitable for minute/minute conversions were then calculated from the full data set. Results: The vertical ActiGraph activity counts demonstrated the closest relationship with the Actical, with consistent moderate to strong conversions using the algorithm: y = 0.905x, in the day by day data (R2 range: 0.514 to 0.989 and average: 0.822) and full data set (R2 = 0.865). Conclusions: The Actical is most sensitive to accelerations in the vertical direction, and does not closely correlate with three-dimensional ActiGraph output. Minute by minute conversions between the Actical and ActiGraphvertical component can be confidently performed between data sets and might allow further synthesis of information between studies

Reliability and validity of two fitness tracker devices in the laboratory and home environment for older community-dwelling people

© 2018 The Author(s). Background: Two-thirds of older Australians are sedentary. Fitness trackers have been popular with younger people and may encourage older adults to become more active. Older adults may have different gait patterns and as such it is important to establish whether fitness trackers are valid and reliable for this population. The aim of the study was to test the reliability and validity of two fitness trackers (Fitbit Flex and ChargeHR) by step count when worn by older adults. Reliability and validity were tested in two conditions: 1) in the laboratory using a two-minute-walk-test (2MWT) and 2) in a free-living environment. Methods: Two 2MWTs were completed while wearing the fitness trackers. Participants were videoed during each test. Participants were then given one fitness tracker and a GENEactiv accelerometer to wear at home for 14-days. Results: Thirty-one participants completed two 2MWTs and 30 completed the free-living procedure. Intra Class Correlation's of the fitness trackers with direct observation of steps (criterion validity) was high (ICC:0.86,95%CI:0.76,0.93). However, both fitness trackers underestimated steps. Excellent test-retest reliability (ICC = 0.75) was found between the two 2MWTs for each device, particularly the ChargeHR devices. Good strength of agreement was found for total distance and steps (fitness tracker) and moderate-to-vigorous physical activity (GENEactiv) for the free-living environment (Spearman Rho's 0.78 and 0.74 respectively). Conclusion: Reliability and validity of the Flex and ChargeHR when worn by older adults is good, however both devices underestimated step count within the laboratory environment. These fitness trackers appear suitable for consumer use and promoting physical activity for older adults

Assessing free-living physical activity using accelerometry : practical issues for researchers and practitioners

Physical activity is an integral component of a healthy lifestyle, with relationships documented between physical activity, chronic diseases, and disease risk factors. There is increasing concern that many people are not sufficiently active to benefit their health. Consequently, there is a need to determine the prevalence of physical activity engagement, identify active and inactive segments of the population, and evaluate the effectiveness of interventions. The aim of the present study was to identify and explain a number of methodological and decision-making processes associated with accelerometry, which is the most commonly used objective measure of physical activity in child and adult research.Specifically, this review addresses:(a) pre-data collection decisions,(b) data collection procedures,(c) processing of accelerometer data, and(d) outcome variables in relation to the research questions posed.An appraisal of the literature is provided to help researchers and practitioners begin field-based research, with recommendations offered for best practice. In addition, issues that require further investigation are identified and discussed to inform researchers and practitioners of the surrounding debates.Overall, the review is intended as a starting point for field-based physical activity research using accelerometers and as an introduction to key issues that should be considered and are likely to be encountered at this time.<br /