Portable global positioning system receivers: static validity and environmental conditions

Investigating young children's physical activity through time and place

BACKGROUND

Previous research indicates the start of primary school (4-5-year-old) as an essential period for the development of children's physical activity (PA) patterns, as from this point, the age-related decline of PA is most often observed. During this period, young children are exposed to a wider variety of environmental- and social contexts and therefore their PA is influenced by more diverse factors. However, in order to understand children's daily PA patterns and identify relevant opportunities for PA promotion, it is important to further unravel in which (social) contexts throughout the day, PA of young children takes place.

METHODS

We included a cross-national sample of 21 primary schools from the Startvaardig study. In total, 248 children provided valid accelerometer and global positioning (GPS) data. Geospatial analyses were conducted to quantify PA in (social) environments based on their school and home. Transport-related PA was evaluated using GPS speed-algorithms. PA was analysed at different environments, time-periods and for week- and weekend days separately.

RESULTS

Children accumulated an average of 60 min of moderate-to-vigorous PA (MVPA), both during week- and weekend days. Schools contributed to approximately half of daily MVPA during weekdays. During weekends, environments within 100 m from home were important, as well as locations outside the home-school neighbourhood. Pedestrian trips contributed to almost half of the daily MVPA.

CONCLUSIONS

We identified several social contexts relevant for children's daily MVPA. Schools have the potential to significantly contribute to young children's PA patterns and are therefore encouraged to systematically evaluate and implement parts of the school-system that stimulate PA and potentially also learning processes. Pedestrian trips also have substantial contribution to daily MVPA of young children, which highlights the importance of daily active transport in school- and parental routines.

Association between match-related physical activity profiles and playing positions in different tasks: A data driven approach

Assessing the intensity characteristics of specific soccer drills (matches, small-side game, and match-based exercises) could help practitioners to plan training sessions by providing the optimal stimulus for every player. In this paper, we propose a data analytics framework to assess the neuromuscular or metabolic characteristics of a soccer-specific exercise in relation with the expected match intensity. GPS data describing the physical tasks' external intensity during an entire season of twenty-eight semi-professional soccer players competing at the fourth Italian division were used in this study. A supervised machine-learning approach was tested in order to detect difference in playing positions in different sport-specific drills. Moreover, a non-supervised machine-learning model was used to profile the match neuromuscular and metabolic characteristics. Players' playing positions during matches and match-based exercises are characterised by specific metabolic and neuromuscular characteristics related to tactical demands, while in the small-side game these differences are not detected. Additionally, our framework permits to evaluate if the match performance request is mirrored during training drills. Practitioners could evaluate the type of stimulus performed by a player in a specific training drill in order to assess if they reflect the matches characteristics of their specific playing position.

Before-school physical activity patterns among adolescents using accelerometer and GPS data

Most adolescents do not meet physical activity (PA) guidelines. The before-school segment has been identified as one promising opportunity for intervention; however, there is a need for contextual understanding of PA in this segment. This study aimed to examine: a) adolescents' PA levels across various locations before school (6:00am - school start), b) contributions of before-school PA to daily PA and PA guidelines, and c) correlates of location-specific before-school PA. A cross-sectional analysis was conducted using adolescents' (n = 148, mean age 14.7) accelerometer and GPS data. Adolescents averaged 9.7 min in before-school moderate-to-vigorous PA (MVPA), representing substantial contributions to daily activity. Most MVPA occurred away from home and school. Significant correlates included segment duration, age, socio-economic status, and PA self-efficacy. Future work should consider these patterns and correlates to support adolescents' PA through targeted interventions.

Systematic review of best practices for GPS data usage, processing, and linkage in health, exposure science and environmental context research

Global Positioning System (GPS) technology is increasingly used in health research to capture individual mobility and contextual and environmental exposures. However, the tools, techniques and decisions for using GPS data vary from study to study, making comparisons and reproducibility challenging.

OBJECTIVES

The objectives of this systematic review were to (1) identify best practices for GPS data collection and processing; (2) quantify reporting of best practices in published studies; and (3) discuss examples found in reviewed manuscripts that future researchers may employ for reporting GPS data usage, processing and linkage of GPS data in health studies.

DESIGN

A systematic review.

DATA SOURCES

Electronic databases searched (24 October 2023) were PubMed, Scopus and Web of Science (PROSPERO ID: CRD42022322166).

ELIGIBILITY CRITERIA

Included peer-reviewed studies published in English met at least one of the criteria: (1) protocols involving GPS for exposure/context and human health research purposes and containing empirical data; (2) linkage of GPS data to other data intended for research on contextual influences on health; (3) associations between GPS-measured mobility or exposures and health; (4) derived variable methods using GPS data in health research; or (5) comparison of GPS tracking with other methods (eg, travel diary).

DATA EXTRACTION AND SYNTHESIS

We examined 157 manuscripts for reporting of best practices including wear time, sampling frequency, data validity, noise/signal loss and data linkage to assess risk of bias.

RESULTS

We found that 6% of the studies did not disclose the GPS device model used, only 12.1% reported the per cent of GPS data lost by signal loss, only 15.7% reported the per cent of GPS data considered to be noise and only 68.2% reported the inclusion criteria for their data.

CONCLUSIONS

Our recommendations for reporting on GPS usage, processing and linkage may be transferrable to other geospatial devices, with the hope of promoting transparency and reproducibility in this research.

PROSPERO REGISTRATION NUMBER

CRD42022322166.

Comparing Location Data From Smartphone and Dedicated Global Positioning System Devices: Implications for Epidemiologic Research

In this study, we compared location data from a dedicated Global Positioning System (GPS) device with location data from smartphones. Data from the Interventions, Equity, and Action in Cities Team (INTERACT) Study, a study examining the impact of urban-form changes on health in 4 Canadian cities (Victoria, Vancouver, Saskatoon, and Montreal), were used. A total of 337 participants contributed data collected for about 6 months from the Ethica Data smartphone application (Ethica Data Inc., Toronto, Ontario, Canada) and the SenseDoc dedicated GPS (MobySens Technologies Inc., Montreal, Quebec, Canada) during the period 2017-2019. Participants recorded an average total of 14,781 Ethica locations (standard deviation, 19,353) and 197,167 SenseDoc locations (standard deviation, 111,868). Dynamic time warping and cross-correlation were used to examine the spatial and temporal similarity of GPS points. Four activity-space measures derived from the smartphone app and the dedicated GPS device were compared. Analysis showed that cross-correlations were above 0.8 at the 125-m resolution for the survey and day levels and increased as cell size increased. At the day or survey level, there were only small differences between the activity-space measures. Based on our findings, we recommend dedicated GPS devices for studies where the exposure and the outcome are both measured at high frequency and when the analysis will not be aggregate. When the exposure and outcome are measured or will be aggregated to the day level, the dedicated GPS device and the smartphone app provide similar results.

Monitoring mobility in older adults using a Global Positioning System (GPS) smartwatch and accelerometer: A validation study

There is growing interest in identifying valid and reliable methods for detecting early mobility limitations in aging populations. A multi-sensor approach that combines accelerometry with Global Positioning System (GPS) devices could provide valuable insights into late-life mobility decline; however, this innovative approach requires more investigation. We conducted a series of two experiments with 25 older participants (66.2±8.5 years) to determine the validity of a GPS enabled smartwatch (TicWatch S2 and Pro 3 Ultra GPS) and separate accelerometer (ActiGraph wGT3X-BT) to collect movement, navigation and body posture data relevant to mobility. In experiment 1, participants wore the TicWatchS2 and ActiGraph simultaneously on the wrist for 3 days. In experiment 2, participants wore the TicWatch Pro 2 Ultra GPS on the wrist and ActiGraph on the thigh for 3 days. In both experiments participants also carried a Qstarz data logger for trips outside the home. The TicWatch Pro 3 Ultra GPS performed better than the S2 model and was similar to the Qstarz in all tested trip-related measures, and it was able to estimate both passive and active trip modes. Both models showed similar results to the gold standard Qstarz in life-space-related measures. The TicWatch S2 demonstrated good to excellent overall agreement with the ActiGraph algorithms for the time spent in sedentary and non-sedentary activities, with 84% and 87% agreement rates, respectively. Under controlled conditions, the TicWatch Pro 3 Ultra GPS consistently measured step count in line with the participants' self-reported data, with a bias of 0.4 steps. The thigh-worn ActiGraph algorithm accurately classified sitting and lying postures (97%) and standing postures (90%). Our multi-sensor approach to monitoring mobility has the potential to capture both accelerometer-derived movement data and trip/life-space data only available through GPS. In this study, we found that the TicWatch models were valid devices for capturing GPS and raw accelerometer data, making them useful tools for assessing real-life mobility in older adults.

Comparison of external load indicators between official matches and sport-specific training in semi-professional soccer players: focus on intensity and strength

BACKGROUND

The aim of this study was to investigate any differences in external load indicators (ELi) between official matches (OM) and sport-specific tasks in semi-professional soccer players.

METHODS

Among 28 semi-professional soccer players, 1932 observations (age: 25±6 years, height: 183±6 cm, weight: 75.2±7 kg; FC Palermo, Palermo, Italy) were collected through GPS devices (Qstarz BT-Q1000EX, 10 Hz; Qstarz International Co., Ltd., Taipei, Taiwan) and the related software (LaGalaColli V: 8.6.4.3; Spinitalia Srl, Rome, Italy) during the season 2019-2020. Participants were monitored during OM, friendly matches (FM), small sided games (SSG), and match-based exercises (MBE), considering the percentage of intense accelerations (%int. acc.), percentage of intense decelerations (%int. dec.), and passive recovery time /min (PrT/m) as Eli.

RESULTS

We detected the highest mean value for PrT/m in OM and the lowest in MBE and SSG (18.36±4.38 and 13.4±5.26 and 13.4±4.29 (s/min), respectively). The lowest mean values of %int. acc. and %int. dec. were found in OM and the highest in SSG (8.64±1.52 vs. 13.02±3.14 and 9.25±1.56 vs. 15.68±3.14, for %int. acc. and %int. dec., respectively). Significant differences between the four tasks for all the ELi considered (P<0.001). The post-hoc pairwise comparisons revealed significant differences for all the ELi between all tasks (P<0.001) except for the %int. acc. between MBE vs. FM (P=0.003). No significant difference was found in PrT/m between MBE vs. FM and SSG vs. FM.

CONCLUSIONS

ELi are in accordance with the performance model by achieving better values in training than OM, suggesting the fundamental role of GPS for monitoring external load in soccer.

Characterizing mobility patterns of forest goers in southern Lao PDR using GPS loggers

BACKGROUND

In the Greater Mekong Subregion (GMS), forest-going populations are considered high-risk populations for malaria and are increasingly targeted by national control programmes' elimination efforts. A better understanding of forest-going populations' mobility patterns and risk associated with specific types of forest-going trips is necessary for countries in the GMS to achieve their objective of eliminating malaria by 2030.

METHODS

Between March and November 2018, as part of a focal test and treat intervention (FTAT), 2,904 forest-goers were recruited in southern Lao PDR. A subset of forest-goers carried an "i-Got-U" GPS logger for roughly 2 months, configured to collect GPS coordinates every 15 to 30 min. The utilization distribution (UD) surface around each GPS trajectory was used to extract trips to the forest and forest-fringes. Trips with shared mobility characteristics in terms of duration, timing and forest penetration were identified by a hierarchical clustering algorithm. Then, clusters of trips with increased exposure to dominant malaria vectors in the region were further classified as high-risk. Finally, gradient boosting trees were used to assess which of the forest-goers' socio-demographic and behavioural characteristics best predicted their likelihood to engage in such high-risk trips.

RESULTS

A total of 122 forest-goers accepted carrying a GPS logger resulting in the collection of 803 trips to the forest or forest-fringes. Six clusters of trips emerged, helping to classify 385 (48%) trips with increased exposure to malaria vectors based on high forest penetration and whether the trip happened overnight. Age, outdoor sleeping structures and number of children were the best predictors of forest-goers' probability of engaging in high-risk trips. The probability of engaging in high-risk trips was high (~ 33%) in all strata of the forest-going population.

CONCLUSION

This study characterized the heterogeneity within the mobility patterns of forest-goers and attempted to further segment their role in malaria transmission in southern Lao People's Democratic Republic (PDR). National control programmes across the region can leverage these results to tailor their interventions and messaging to high-risk populations and accelerate malaria elimination.

Validity, Reliability, and Usability of a Smartphone App to Measure Bicycling Location

This study evaluates concurrent validity, test-retest reliability, and usability of the Strava smartphone app for measuring bicycling locations in urban and rural field tests. Strava location data were inside an 11-meter buffer on average 64% of the time compared to Qstarz' 52%, over 100 evaluations (n participants=73). Most participants agreed or strongly agreed that the Strava app was useful (83%) and that they would prefer to use a smartphone app to track their bicycling (42%). Results indicate that the Strava app is reliable and valid for measuring bicycling locations in these field tests.

Characterizing human movement patterns using GPS data loggers in an area of persistent malaria in Zimbabwe along the Mozambique border

BACKGROUND

Human mobility is a driver for the reemergence or resurgence of malaria and has been identified as a source of cross-border transmission. However, movement patterns are difficult to measure in rural areas where malaria risk is high. In countries with malaria elimination goals, it is essential to determine the role of mobility on malaria transmission to implement appropriate interventions.

METHODS

A study was conducted in Mutasa District, Zimbabwe, to investigate human movement patterns in an area of persistent transmission along the Mozambique border. Over 1 year, a convenience sample of 20 participants/month was recruited from active malaria surveillance cohorts to carry an IgotU^® GT-600 global positioning system (GPS) data logger during all daily activities. Consenting participants were tested for malaria at data logger distribution using rapid antigen diagnostic tests and completed a survey questionnaire. GPS data were analyzed using a trajectory analysis tool, and participant movement patterns were characterized throughout the study area and across the border into Mozambique using movement intensity maps, activity space plots, and statistical analyses.

RESULTS

From June 2016-May 2017, 184 participants provided movement tracks encompassing > 350,000 data points and nearly 8000 person-days. Malaria prevalence at logger distribution was 3.7%. Participants traveled a median of 2.8 km/day and spent a median of 4.6 h/day away from home. Movement was widespread within and outside the study area, with participants traveling up to 500 km from their homes. Indices of mobility were higher in the dry season than the rainy season (median km traveled/day = 3.5 vs. 2.2, P = 0.03), among male compared to female participants (median km traveled/day = 3.8 vs. 2.0, P = 0.0008), and among adults compared to adolescents (median total km traveled = 104.6 vs. 59.5, P = 0.05). Half of participants traveled outside the study area, and 30% traveled into Mozambique, including 15 who stayed in Mozambique overnight.

CONCLUSIONS

Study participants in Mutasa District, Zimbabwe, were highly mobile throughout the year. Many participants traveled long distances from home, including overnight trips into Mozambique, with clear implications for malaria control. Interventions targeted at mobile populations and cross-border transmission may be effective in preventing malaria introductions in this region.

From motorised to active travel: using GPS data to explore potential physical activity gains among adolescents

Background

A high proportion of adolescents worldwide are not doing enough physical activity for health benefits. Replacing short motorised trips with walking or cycling has the potential to increase physical activity at the population level. This study aimed to estimate the proportion of short distance motorised trips that could be replaced with walking or cycling, and the potential physical activity gains by sociodemographic and trip characteristics.

Methods

Data were from a subsample of the NEighbourhood Activity in Youth (NEArbY) study conducted among adolescents in Melbourne. A total of 217 adolescents with at least one motorised trip completed a survey and wore a Global Positioning Systems (GPS) device for eight consecutive days. Classification of travel modes were based on speed. GPS data points were geocoded in ArcGIS. Motorised trips within walkable (1.3 km) and cyclable (4.2 km) distances were identified (threshold based on 80^th percentile of walking and cycling trip distances among Victorian adolescents), and the additional physical activity minutes that could be accrued by replacing walkable or cyclable motorised trip to active trips were quantified. Multilevel linear regression was used to assess differences in physical activity minutes gain by sociodemographic and trip characteristics.

Results

A total of 4,116 motorised trips were made. Of these, 17% were walkable and 61% were cyclable. Replacing motorised trips by walking and cycling resulted in estimated gains of six minutes and 15 min of physical activity per day, respectively.

Conclusion

The sizable proportion of replaceable trips and potential physical activity gains from this shift calls for attention to improve safe and connected infrastructure to support active travel.

Mobility evaluation by GPS tracking in a rural, low-income population in Cambodia

Global Positioning System (GPS) technology is an effective tool for quantifying individuals' mobility patterns and can be used to understand their influence on infectious disease transmission. In Cambodia, mobility measurements have been limited to questionnaires, which are of limited efficacy in rural environments. In this study, we used GPS tracking to measure the daily mobility of Cambodian forest goers, a population at high risk of malaria, and developed a workflow adapted to local constraints to produce an optimal dataset representative of the participants' mobility. We provide a detailed assessment of the GPS tracking and analysis of the data, and highlight the associated difficulties to facilitate the implementation of similar studies in the future.

Improved Position Estimation Algorithm of Agricultural Mobile Robots Based on Multisensor Fusion and Autoencoder Neural Network

High-precision position estimations of agricultural mobile robots (AMRs) are crucial for implementing control instructions. Although the global navigation satellite system (GNSS) and real-time kinematic GNSS (RTK-GNSS) provide high-precision positioning, the AMR accuracy decreases when the signals interfere with buildings or trees. An improved position estimation algorithm based on multisensor fusion and autoencoder neural network is proposed. The multisensor, RTK-GNSS, inertial-measurement-unit, and dual-rotary-encoder data are fused with Extended Kalman filter (EKF). To optimize the EKF noise matrix, the autoencoder and radial basis function (ARBF) neural network was used for modeling the state equation noise and EKF measurement equation. A multisensor AMR test platform was constructed for static experiments to estimate the circular error probability and twice-the-distance root-mean-squared criteria. Dynamic experiments were conducted on road, grass, and field environments. To validate the robustness of the proposed algorithm, abnormal working conditions of the sensors were tested on the road. The results showed that the positioning estimation accuracy was improved compared to the RTK-GNSS in all three environments. When the RTK-GNSS signal experienced interference or rotary encoders failed, the system could still improve the position estimation accuracy. The proposed system and optimization algorithm are thus significant for improving AMR position prediction performance.

Validity and Reliability of an Inertial Sensor Device for Specific Running Patterns in Soccer

Electronic performance tracking devices are largely employed in team sports to monitor performance and improve training. To date, global positioning system (GPS) based devices are those mainly used in soccer training. The aim of this study was to analyse the validity and reliability of the inertial sensor device (ISD) in monitoring distance and speed in a soccer-specific circuit and how their performance compare to a GPS system. 44 young male soccer players (age: 14.9 ± 1.1, range 9–16, years, height: 1.65 ± 0.10 m, body mass: 56.3 ± 8.9 kg) playing in a non-professional soccer team in Italy, participated in the study. We assessed the players trough a soccer running sport-specific circuit. An ISD and a GPS were used to assess distance and speed. Data was compared to a video reference system, and the difference were quantified by means of the root mean square error (RMSE). Significant differences were found for both GPS and ISD devices for distance and speed. However, lower error for distance (dRMSE 2.23 ± 1.01 m and 5.75 ± 1.50 m, respectively) and speed (sRMSE 0.588 ± 0.152 m·s^–1 and 1.30 ± 0.422 m·s^–1, respectively) were attained by the ISD compared to the GPS. Overall, our results revealed a statistically significant difference between systems in data monitoring for either distance and speed. However, results of this study showed that a smaller error was obtained with the ISD than the GPS device. Despite caution is warranted within the interpretation of these results, we observed a better practical applicability of the ISD due to its small size, lower cost and the possibility to use the device indoor.

Smart Watch Versus Classic Receivers: Static Validity of Three GPS Devices in Different Types of Built Environments

In order to study the relationship between human physical activity and the design of the built environment, it is important to measure the location of human movement accurately. In this study, we compared an inexpensive GPS receiver (Holux RCV-3000) and a frequently used Garmin Forerunner 35 smart watch, with a device that has been validated and recommended for physical activity research (Qstarz BT-Q1000XT). These instruments were placed on six geodetic points, which represented a range of different environments (e.g., residential, open space, park). The coordinates recorded by each device were compared with the known coordinates of the geodetic points. There were no differences in accuracy among the three devices when averaged across the six sites. However, the Garmin was more accurate in the city center and the Holux was more accurate in the park and housing estate areas compared to the other devices. We consider the location accuracy of the Holux and the Garmin to be comparable to that of the Qstarz. Therefore, we consider these devices to be suitable instruments for locating physical activity. Researchers must also consider other differences among these devices (such as battery life) when determining if they are suitable for their research studies.

Objective measurement of children's physical activity geographies: A systematic search and scoping review

This study aimed to systematically identify, map out, and describe geographical information systems (GIS)-based approaches that have been employed to measure children's neighborhood geographies for physical activity behaviors. Forty studies were included, most were conducted in the USA. Heterogeneity in GIS methods and measures was found. The majority of studies estimated children's environments using Euclidean or network buffers ranging from 100 m to 5 km. No singular approach to measuring children's physical activity geographies was identified as optimal. Geographic diversity in studies as well as increased use of measures of actual neighborhood exposure are needed. Improved consistency and transparency in reporting research methods is urgently required.

•

Varied GIS measures of children's physical activity geographies were identified.

•

Evidence was heterogeneous and predominantly from the USA.

•

Most research used Euclidean or network buffers ranging from 100 m to 5 km.

•

Larger buffer sizes (i.e., ≥800 m) performed better than smaller buffer sizes.

•

No optimal approach to measuring children's activity geographies was determined.

Proximity Interactions in a Permanently Housed Dairy Herd: Network Structure, Consistency, and Individual Differences

Understanding the herd structure of housed dairy cows has the potential to reveal preferential interactions, detect changes in behavior indicative of illness, and optimize farm management regimes. This study investigated the structure and consistency of the proximity interaction network of a permanently housed commercial dairy herd throughout October 2014, using data collected from a wireless local positioning system. Herd-level networks were determined from sustained proximity interactions (pairs of cows continuously within three meters for 60 s or longer), and assessed for social differentiation, temporal stability, and the influence of individual-level characteristics such as lameness, parity, and days in milk. We determined the level of inter-individual variation in proximity interactions across the full barn housing, and for specific functional zones within it (feeding, non-feeding). The observed networks were highly connected and temporally varied, with significant preferential assortment, and inter-individual variation in daily interactions in the non-feeding zone. We found no clear social assortment by lameness, parity, or days in milk. Our study demonstrates the potential benefits of automated tracking technology to monitor the proximity interactions of individual animals within large, commercially relevant groups of livestock.

A socio-spatial analysis of pedestrian falls in Aotearoa New Zealand

Falls are a leading cause of injury and accidental death, particularly amongst older people. Evidence of environmental risk factors for pedestrian falls among older adults could support age-friendly urban design and contribute to efforts to reduce the incidence of pedestrian falls and support outdoor mobility among older adults. Yet investigation of the environment in which pedestrian falls occur is often hampered by its reliance on participant recall and self-report information. We identified the point locations of falls occurring on the road or street among adults that were attended by an ambulance in New Zealand over a two-year period (2016-2018) and connected these to a range of social (e.g. deprivation) and environmental (e.g. slope, greenspace) risk factors. Three types of analysis were used: a descriptive analysis of fall rates, logistic regression assessing whether a patient was transported to hospital following a fall, and a negative binomial regression analysis of the pedestrian falls by small area. We found a number of differences in the built environment surrounding fall locations between age groups. Compared with younger age groups, older adults showed high fall rates closer to home, and higher fall rates in areas with many types of destinations nearby. Additionally, our results showed a higher rate of pedestrian falls in more deprived areas. People who live in more deprived areas also fell over more frequently, but the pattern is stronger based on deprivation at the fall location, rather than home location. Residents of more deprived areas were less likely to be transported to hospital following a fall. Thus, our findings have equity implications for both environments and patient experience. These patterns could not have been identified without the novel use of spatially specific fall data.

Accuracy of Distance Recordings in Eight Positioning-Enabled Sport Watches: Instrument Validation Study

Background

Elite athletes and recreational runners rely on the accuracy of global navigation satellite system (GNSS)–enabled sport watches to monitor and regulate training activities. However, there is a lack of scientific evidence regarding the accuracy of such sport watches.

Objective

The aim was to investigate the accuracy of the recorded distances obtained by eight commercially available sport watches by Apple, Coros, Garmin, Polar, and Suunto when assessed in different areas and at different speeds. Furthermore, potential parameters that affect the measurement quality were evaluated.

Methods

Altogether, 3 × 12 measurements in urban, forest, and track and field areas were obtained while walking, running, and cycling under various outdoor conditions.

Results

The selected reference distances ranged from 404.0 m to 4296.9 m. For all the measurement areas combined, the recorded systematic errors (±limits of agreements) ranged between 3.7 (±195.6) m and –101.0 (±231.3) m, and the mean absolute percentage errors ranged from 3.2% to 6.1%. Only the GNSS receivers from Polar showed overall errors <5%. Generally, the recorded distances were significantly underestimated (all P values <.04) and less accurate in the urban and forest areas, whereas they were overestimated but with good accuracy in 75% (6/8) of the sport watches in the track and field area. Furthermore, the data assessed during running showed significantly higher error rates in most devices compared with the walking and cycling activities.

Conclusions

The recorded distances might be underestimated by up to 9%. However, the use of all investigated sport watches can be recommended, especially for distance recordings in open areas.

Investigating longitudinal context-specific physical activity patterns in transition from primary to secondary school using accelerometers, GPS, and GIS

INTRODUCTION

Previous longitudinal studies indicate that physical activity (PA) significantly declines from primary-to secondary school, and report both changes in individual and environmental determinants of PA. In order to understand this transition and to prevent this negative trend, it is important to gather contextually rich data on possible mechanisms that drive this decline. Therefore, the aim of this study was to investigate changes of PA patterns in transition between primary and secondary school, and to add domain-specific insights of how, where, and when these changes occur.

METHODS

In total, 175 children participated in a 7-day accelerometer- and Global Positioning System (GPS) protocol at their last year of primary and their first year of secondary school. GPS data-points were overlaid with Geographical Information Systems (GIS) data using ArcGIS 10.1 software. Based on the GPS locations of individual data-points, we identified child's PA at home, school, local sports grounds, shopping centers, and other locations. Also, trips in active and passive transport were identified according to previously validated GPS speed-algorithms. Longitudinal multi-level linear mixed models were fitted adjusting for age, gender, meteorological circumstances, and the nested structure of days within children and children within schools. Outcome measures were minutes spent in light PA and moderate-to-vigorous PA, specified for the time-segments before school, during school, after school and weekend days.

RESULTS

Total PA significantly declined from primary to secondary school. Although transport-related PA increased before- and during school, decreases were found for especially afterschool time spent at sports grounds and transport-related PA during weekends.

CONCLUSIONS

This is the first study that demonstrated longitudinal changes of context- and domain-specific PA patterns in transition between primary and secondary school, based on device-assessed PA. Given the importance of this transition-period for the development of long-term PA patterns, results from this study warrant the development of evidence-based PA programs in this transition period, while acknowledging the integrative role of schools, parents, and afterschool sports providers. More specifically, the results underline the need to increase children's PA levels in primary schools, promote afterschool PA at secondary schools, and to prevent the drop-out in sports participation at secondary schools.

The Feasibility of Remotely Piloted Aircrafts for VOR Flight Inspection

This article analyzes the use of Remotely Piloted Aircrafts (RPA) in VOR (Very High Frequency Omnidirectional Range) flight inspection. Initially, tests were performed to check whether the Autopilot Positioning System (APS) met the regulatory requirements. The results of these tests indicated that the APS provided information within the standard regulations. A Hardware in the Loop (HIL) platform was implemented to perform flight tests following the waypoints generated by a mission automation routine. One test was performed without introducing disturbance into the proposed test platform. The other four tests were performed introducing errors in latitude and longitude in the APS into the platform. The errors introduced had the same characteristics as those measured in the initial tests, in order for the simulation tests to be as similar as possible to the real situation. The tests performed with positioning errors only did not lead to false misalignment detection. However, introducing positioning errors and a 4° VOR misalignment error, a misalignment of 3.99° was observed during the flight test. This is a value greater than the maximum one allowed by the regulations, and the system indicates the VOR misalignment. Five flight inspection tests were performed. In addition to the APS errors, tests with a modulation error were also conducted. Introducing a 4° VOR misalignment in conjunction with modulation error, a misalignment of 4.02° was observed, resulting in successful misalignment detection.

Behavioral mapping of children's physical activities and social behaviors in an indoor preschool facility: methodological challenges in revealing the influence of space in play

BACKGROUND

GIS (Geographic Information Systems) based behavior maps are useful for visualizing and analyzing how children utilize their play spaces. However, a GIS needs accurate locational information to ensure that observations are correctly represented on the layout maps of play spaces. The most commonly used tools for observing and coding free play among children in indoor play spaces require that locational data be collected alongside other play variables. There is a need for a practical, cost-effective approach for extending most tools for analyzing free play by adding geospatial locational information to children's behavior data collected in indoor play environments.

RESULTS

We provide a non-intrusive approach to adding locational information to behavior data acquired from video recordings of preschool children in their indoor play spaces. The gridding technique showed to be a cost-effective method of gathering locational information about children from video recordings of their indoor physical activities and social behaviors. Visualizing the proportions of categories and observed intervals was done using bubble pie charts which allowed for the merging of multiple categorical information on one map. The addition of locational information to other play activity and social behavior data presented the opportunity to assess what types of equipment or play areas may encourage different physical activities and social behaviors among preschool children.

CONCLUSIONS

Gridding is an effective method for providing locational data when analyzing physical activities and social behaviors of preschool children in indoor spaces. It is also reproducible for most GIS behavior mapping focusing on indoor environments. This bypasses the need to have positioning devices attached to children during observations, which can raise ethical considerations regarding children's privacy and methodological implications with children playing less naturally. It also supports visualizations on behavior maps making them easier to interpret.

Combining sensor tracking with a GPS-based mobility survey to better measure physical activity in trips: public transport generates walking

Background

Policymakers need accurate data to develop efficient interventions to promote transport physical activity. Given the imprecise assessment of physical activity in trips, our aim was to illustrate novel advances in the measurement of walking in trips, including in trips incorporating non-walking modes.

Methods

We used data of 285 participants (RECORD MultiSensor Study, 2013–2015, Paris region) who carried GPS receivers and accelerometers over 7 days and underwent a phone-administered web mobility survey on the basis of algorithm-processed GPS data. With this mobility survey, we decomposed trips into unimodal trip stages with their start/end times, validated information on travel modes, and manually complemented and cleaned GPS tracks. This strategy enabled to quantify walking in trips with different modes with two alternative metrics: distance walked and accelerometry-derived number of steps taken.

Results

Compared with GPS-based mobility survey data, algorithm-only processed GPS data indicated that the median distance covered by participants per day was 25.3 km (rather than 23.4 km); correctly identified transport time vs. time at visited places in 72.7% of time; and correctly identified the transport mode in 67% of time (and only in 55% of time for public transport). The 285 participants provided data for 8983 trips (21,163 segments of observation). Participants spent a median of 7.0% of their total time in trips. The median distance walked per trip was 0.40 km for entirely walked trips and 0.85 km for public transport trips (the median number of accelerometer steps were 425 and 1352 in the corresponding trips). Overall, 33.8% of the total distance walked in trips and 37.3% of the accelerometer steps in trips were accumulated during public transport trips. Residents of the far suburbs cumulated a 1.7 times lower distance walked per day and a 1.6 times lower number of steps during trips per 8 h of wear time than residents of the Paris core city.

Conclusions

Our approach complementing GPS and accelerometer tracking with a GPS-based mobility survey substantially improved transport mode detection. Our findings suggest that promoting public transport use should be one of the cornerstones of policies to promote physical activity.

Electronic supplementary material

The online version of this article (10.1186/s12966-019-0841-2) contains supplementary material, which is available to authorized users.

Critical Hours and Important Environments: Relationships between Afterschool Physical Activity and the Physical Environment Using GPS, GIS and Accelerometers in 10-12-Year-Old Children

Introduction: The objective of this study was to assess relationships between children’s physical environment and afterschool leisure time physical activity (PA) and active transport. Methods: Children aged 10–12 years participated in a 7-day accelerometer and Global Positioning Systems (GPS) protocol. Afterschool leisure time PA and active transport were identified based on location- and speed-algorithms based on accelerometer, GPS and Geospatial Information Systems (GIS) data. We operationalized children’s exposure to the environment by combining home, school and the daily transport environment in individualized daily activity-spaces. Results: In total, 255 children from 20 Dutch primary schools from suburban areas provided valid data. This study showed that greenspaces and smaller distances from the children’s home to school were associated with afterschool leisure time PA and walking. Greater distances between home and school, as well as pedestrian infrastructure were associated with increased cycling. Conclusion: We demonstrated associations between environments and afterschool PA within several behavioral contexts. Future studies are encouraged to target specific behavioral domains and to develop natural experiments based on interactions between several types of the environment, child characteristics and potential socio-cognitive processes.

The use of GPS data loggers to describe the impact of spatio-temporal movement patterns on malaria control in a high-transmission area of northern Zambia

Background

Human movement is a driver of malaria transmission and has implications for sustainable malaria control. However, little research has been done on the impact of fine-scale movement on malaria transmission and control in high-transmission settings. As interest in targeted malaria control increases, evaluations are needed to determine the appropriateness of these strategies in the context of human mobility across a variety of transmission settings.

Methods

A human mobility study was conducted in Nchelenge District, a high-transmission setting in northern Zambia. Over 1 year, 84 participants were recruited from active malaria surveillance cohorts to wear a global positioning system data logger for 1 month during all daily activity. Participants completed a survey questionnaire and underwent malaria testing and treatment at the time of logger distribution and at collection 1 month later. Incident malaria infections were identified using polymerase chain reaction. Participant movement was characterized throughout the study area and across areas targeted for an indoor residual spraying (IRS) intervention. Participant movement patterns were compared using movement intensity maps, activity space plots, and statistical analyses. Malaria risk was characterized across participants using spatial risk maps and time spent away from home during peak vector biting hours.

Results

Movement data were collected from 82 participants, and 63 completed a second study visit. Participants exhibited diverse mobility patterns across the study area, including movement into and out of areas targeted for IRS, potentially mitigating the impact of IRS on parasite prevalence. Movement patterns did not differ significantly by season or age, but male participants traveled longer distances and spent more time away from home. Monthly malaria incidence was 22%, and malaria risk was characterized as high across participants. Participants with incident parasitemia traveled a shorter distance and spent more time away from home during peak biting hours; however, these relationships were not statistically significant, and malaria risk score did not differ by incident parasitemia.

Conclusions

Individual movement patterns in Nchelenge District, Zambia have implications for malaria control, particularly the effectiveness of targeted IRS strategies. Large and fine-scale population mobility patterns should be considered when planning intervention strategies across transmission settings.

Electronic supplementary material

The online version of this article (10.1186/s12942-019-0183-y) contains supplementary material, which is available to authorized users.

Robust Positioning and Navigation of a Mobile Robot in an Urban Environment Using a Motion Estimator

Robust positioning and navigation of a mobile robot in an urban environment is implemented by fusing the Global Positioning System (GPS) and Inertial Navigation System (INS) data with the aid of a motion estimator. To select and isolate malicious satellite signals and guarantee the minimum number of GPS signals for the localization, an enhanced fault detection and isolation (FDI) algorithm with a short-term memory has been developed in this research. When there are sufficient satellite signals for positioning, the horizontal dilution of precision (HDOP) has been applied for selecting the best four satellite signals to localize the mobile robot. Then, the GPS data are fused with INS data by a Kalman filter (KF) for a straight path and a curved motion estimator (CME) for a curved path. That is, the INS data are properly fused to the GPS data through the KF or CME process. To verify the effectiveness of the proposed algorithm, experiments using a mobile robot have been carried out on a university campus.

Towards a comprehensive set of GPS-based indicators reflecting the multidimensional nature of daily mobility for applications in health and aging research

BACKGROUND

GPS tracking is increasingly used in health and aging research to objectively and unobtrusively assess individuals' daily-life mobility. However, mobility is a complex concept and its thorough description based on GPS-derived mobility indicators remains challenging.

METHODS

With the aim of reflecting the breadth of aspects incorporated in daily mobility, we propose a conceptual framework to classify GPS-derived mobility indicators based on their characteristic and analytical properties for application in health and aging research. In order to demonstrate how the classification framework can be applied, existing mobility indicators as used in existing studies are classified according to the proposed framework. Then, we propose and compute a set of selected mobility indicators based on real-life GPS data of 95 older adults that reflects diverse aspects of individuals' daily mobility. To explore latent dimensions that underlie the mobility indicators, we conduct a factor analysis.

RESULTS

The proposed framework enables a conceptual classification of mobility indicators based on the characteristic and analytical aspects they reflect. Characteristic aspects inform about the content of the mobility indicator and comprise categories related to space, time, movement scope, and attribute. Analytical aspects inform how a mobility indicator is aggregated with respect to temporal scale and statistical property. The proposed categories complement existing studies that often underrepresent mobility indicators involving timing, temporal distributions, and stop-move segmentations of movements. The factor analysis uncovers the following six dimensions required to obtain a comprehensive view of an older adult's daily mobility: extent of life space, quantity of out-of-home activities, time spent in active transport modes, stability of life space, elongation of life space, and timing of mobility.

CONCLUSION

This research advocates incorporating GPS-based mobility indicators that reflect the multi-dimensional nature of individuals' daily mobility in future health- and aging-related research. This will foster a better understanding of what aspects of mobility are key to healthy aging.

ExpoApp: An integrated system to assess multiple personal environmental exposures

To assess environmental exposures at the individual level, new assessment methods and tools are required. We developed an exposure assessment system (ExpoApp) for smartphones. ExpoApp integrates: (i) geo-location and accelerometry measurements from a waist attached smartphone, (ii) data from portable monitors, (iii) geographic information systems, and (iv) individual's information. ExpoApp calculates time spent in microenvironments, physical activity level, inhalation rate, and environmental exposures and doses (e.g., green spaces, inhaled ultrafine particles- UFP). We deployed ExpoApp in a panel study of 158 adults from five cities (Amsterdam and Utrecht- the Netherlands, Basel- Switzerland, Norwich- UK, and Torino- Italy) with an UFP monitor. To evaluate ExpoApp, participants also carried a reference accelerometer (ActiGraph) and completed a travel-activity diary (TAD). System reliability and validity of measurements were evaluated by comparing the monitoring failure rate and the agreement on time spent in microenvironments and physical activity with the reference tools. There were only significant failure rate differences between ExpoApp and ActiGraph in Norwich. Agreement on time in microenvironments and physical activity level between ExpoApp and reference tools was 86.6% (86.5-86.7) and 75.7% (71.5-79.4), respectively. ExpoApp estimated that participants inhaled 16.5 × 10¹⁰ particles/day of UFP and had almost no contact with green spaces (24% of participants spent ≥30 min/day in green spaces). Participants with more contact with green spaces had higher inhaled dose of UFP, except for the Netherlands, where the relationship was the inverse. ExpoApp is a reliable system and provides accurate individual's measurements, which may help to understand the role of environmental exposures on the origin and course of diseases.

Comparative analysis of positioning accuracy of Samsung Galaxy smartphones in stationary measurements

Achieving single meter positioning accuracy by portable mobile devices still poses a major challenge to the satellite signal receivers constructors, despite gradual constellation completing process and the progress achieved in last decades. Nowadays popular smartphones are multifunctional devices that serve also as a personal navigation tool in navigation and sport activities using the global navigation satellite systems (GNSS) receivers installed. It would seem that introducing newer models to the global market would cause constant progress in the accuracies obtained, however, the study results do not confirm that. This study focused on Galaxy series smartphones of Samsung, one of the leading manufacturers worldwide, to examine its technological progress. The aim was to verify the thesis using statistical models and analyses to compare succeeding generations of smartphones on six devices from the series. The authors conducted two synchronous stationary measurement campaigns of 24 and 12 hours with one-second interval in obstacle-free environment which provided 70000+ and 30000+ statistical samples of position measurements. The reference values of true smartphones coordinates were determined by means of state-of-the-art precise surveying instruments and geodetic calculations. The results indicate that two newest generations of the Galaxy series included in the research, namely S6 and S7, obtained lower accuracies than their predecessors. Against the backdrop of lack of public availability of smartphones technical parameters, the conducted research results are relevant especially to smartphones positioning service users community.

Comparing the Data Quality of Global Positioning System Devices and Mobile Phones for Assessing Relationships Between Place, Mobility, and Health: Field Study

Background

Mobile devices are increasingly used to collect location-based information from individuals about their physical activities, dietary intake, environmental exposures, and mental well-being. Such research, which typically uses wearable devices or mobile phones to track location, benefits from the growing availability of fine-grained data regarding human mobility. However, little is known about the comparative geospatial accuracy of such devices.

Objective

In this study, we compared the data quality of location information collected from two mobile devices that determine location in different ways—a global positioning system (GPS) watch and a mobile phone with Google’s Location History feature enabled.

Methods

A total of 21 chronically ill participants carried both devices, which generated digital traces of locations, for 28 days. A mobile phone–based brief ecological momentary assessment (EMA) survey asked participants to manually report their location at 4 random times throughout each day. Participants also took part in qualitative interviews and completed surveys twice during the study period in which they reviewed recent mobile phone and watch trace data to compare the devices’ trace data with their memory of their activities on those days. Trace data from the devices were compared on the basis of (1) missing data days, (2) reasons for missing data, (3) distance between the route data collected for matching day and the associated EMA survey locations, and (4) activity space total area and density surfaces.

Results

The watch resulted in a much higher proportion of missing data days (P<.001), with missing data explained by technical differences between the devices as well as participant behaviors. The mobile phone was significantly more accurate in detecting home locations (P=.004) and marginally more accurate (P=.07) for all types of locations combined. The watch data resulted in a smaller activity space area and more accurately recorded outdoor travel and recreation.

Conclusions

The most suitable mobile device for location-based health research depends on the particular study objectives. Furthermore, data generated from mobile devices, such as GPS phones and smartwatches, require careful analysis to ensure quality and completeness. Studies that seek precise measurement of outdoor activity and travel, such as measuring outdoor physical activity or exposure to localized environmental hazards, would benefit from the use of GPS devices. Conversely, studies that aim to account for time within buildings at home or work, or those that document visits to particular places (such as supermarkets, medical facilities, or fast food restaurants), would benefit from the greater precision demonstrated by the mobile phone in recording indoor activities.

Are disadvantaged children more likely to be excluded from analysis when applying global positioning systems inclusion criteria?

Objective

When using global positioning systems (GPS) to assess an individual’s exposure to their environment, a first step in data cleaning is to establish minimum GPS ‘inclusion criteria’ (a set of rules used to determine which GPS data are able to be included in analyses). Care is needed at this stage to avoid any data exclusion (data loss) systematically biasing results in terms of characteristics of the environment and participants. The extent of potential systematic bias in sample retention due to GPS data loss and application of GPS inclusion criteria is unknown. The aim of this study was to describe differences in sample size and socio-demographic characteristics of the retained sample when applying three different GPS inclusion criteria. The study assessed 7-day GPS data collected from children (aged 9–13 years) recruited from nine schools in Auckland, New Zealand as part of the Kids in the City study.

Results

Participants from ethnic minorities and those attending schools in lower socioeconomic areas were disproportionately excluded from the retained samples. This highlights potential equity implications in basing the assessment of exposure—which ultimately influences research results on the relationship between environment and health—on non-representative GPS data.

The "Residential" Effect Fallacy in Neighborhood and Health Studies: Formal Definition, Empirical Identification, and Correction

BACKGROUND

Because of confounding from the urban/rural and socioeconomic organizations of territories and resulting correlation between residential and nonresidential exposures, classically estimated residential neighborhood-outcome associations capture nonresidential environment effects, overestimating residential intervention effects. Our study diagnosed and corrected this "residential" effect fallacy bias applicable to a large fraction of neighborhood and health studies.

METHODS

Our empirical application investigated the effect that hypothetical interventions raising the residential number of services would have on the probability that a trip is walked. Using global positioning systems tracking and mobility surveys over 7 days (227 participants and 7440 trips), we employed a multilevel linear probability model to estimate the trip-level association between residential number of services and walking to derive a naïve intervention effect estimate and a corrected model accounting for numbers of services at the residence, trip origin, and trip destination to determine a corrected intervention effect estimate (true effect conditional on assumptions).

RESULTS

There was a strong correlation in service densities between the residential neighborhood and nonresidential places. From the naïve model, hypothetical interventions raising the residential number of services to 200, 500, and 1000 were associated with an increase by 0.020, 0.055, and 0.109 of the probability of walking in the intervention groups. Corrected estimates were of 0.007, 0.019, and 0.039. Thus, naïve estimates were overestimated by multiplicative factors of 3.0, 2.9, and 2.8.

CONCLUSIONS

Commonly estimated residential intervention-outcome associations substantially overestimate true effects. Our somewhat paradoxical conclusion is that to estimate residential effects, investigators critically need information on nonresidential places visited.

The Demands of a Women's College Soccer Season

The purpose of this study was to use GPS, accelerometers, and session rating of perceived exertion (sRPE) to examine the demands of a Division II women’s soccer team. Data was collected on 25 collegiate Division II women’s soccer players over an entire regular season (17 matches and 24 practices). Zephyr^TM BioHarnesses (BHs) were used to collect tri-axial acceleration information and GPS derived variables for all matches and practices. Acceleration data was used to calculate Impulse Load, a measure of mechanical load that includes only locomotor related accelerations. GPS was used to quantify total distance and distance in six speed zones. Internal Training Loads were assessed via sRPE. Mean Impulse Load, total distance, and sRPE during match play was 20,120 ± 8609 N·s, 5.48 ± 2.35 km, and 892.50 ± 358.50, respectively. Mean Impulse Load, total distance, and sRPE during practice was 12,410 ± 4067 N·s, 2.95 ± 0.95 km, and 143.30 ± 123.50, respectively. Several very large to nearly perfect correlations were found between Impulse Load and total distance (r = 0.95; p < 0.001), Impulse Load and sRPE (r = 0.84; p < 0.001), and total distance and sRPE (r = 0.82; p < 0.001). This study details the mechanical demands of Division II women’s soccer match play. This study also demonstrates that Impulse Load is a good indicator of total distance.

User acceptance of location-tracking technologies in health research: Implications for study design and data quality

Research regarding place and health has undergone a revolution due to the availability of consumer-focused location-tracking devices that reveal fine-grained details of human mobility. Such research requires that participants accept such devices enough to use them in their daily lives. There is a need for a theoretically grounded understanding of acceptance of different location-tracking technology options, and its research implications. Guided by an extended Unified Theory of Acceptance and Use of Technology (UTAUT), we conducted a 28-day field study comparing 21 chronically ill people's acceptance of two leading, consumer-focused location-tracking technologies deployed for research purposes: (1) a location-enabled smartphone, and (2) a GPS watch/activity tracker. Participants used both, and completed two surveys and qualitative interviews. Findings revealed that all participants exerted effort to facilitate data capture, such as by incorporating devices into daily routines and developing workarounds to keep devices functioning. Nevertheless, the smartphone was perceived to be significantly easier and posed fewer usability challenges for participants than the watch. Older participants found the watch significantly more difficult to use. For both devices, effort expectancy was significantly associated with future willingness to participate in research although prosocial motivations overcame some concerns. Social influence, performance expectancy and use behavior were significantly associated with intentions to use the devices in participants' personal lives. Data gathered via the smartphone was significantly more complete than data gathered via the watch, primarily due to usability challenges. To make longer-term participation in location tracking research a reality, and to achieve complete data capture, researchers must minimize the effort involved in participation; this requires usable devices. For long-term location-tracking studies using similar devices, findings indicate that only smartphone-based tracking is up to the challenge.

Assessment of accuracy, fix success rate, and use of estimated horizontal position error (EHPE) to filter inaccurate data collected by a common commercially available GPS logger

Global positioning system (GPS) technologies have improved the ability of researchers to monitor wildlife; however, use of these technologies is often limited by monetary costs. Some researchers have begun to use commercially available GPS loggers as a less expensive means of tracking wildlife, but data regarding performance of these devices are limited. We tested a commercially available GPS logger (i-gotU GT-120) by placing loggers at ground control points with locations known to < 30 cm. In a preliminary investigation, we collected locations every 15 minutes for several days to estimate location error (LE) and circular error probable (CEP). Using similar methods, we then investigated the influence of cover on LE, CEP, and fix success rate (FSR) by constructing cover over ground control points. We found mean LE was < 10 m and mean 50% CEP was < 7 m. FSR was not significantly influenced by cover and in all treatments remained near 100%. Cover had a minor but significant effect on LE. Denser cover was associated with higher mean LE, but the difference in LE between the no cover and highest cover treatments was only 2.2 m. Finally, the most commonly used commercially available devices provide a measure of estimated horizontal position error (EHPE) which potentially may be used to filter inaccurate locations. Using data combined from the preliminary and cover investigations, we modeled LE as a function of EHPE and number of satellites. We found support for use of both EHPE and number of satellites in predicting LE; however, use of EHPE to filter inaccurate locations resulted in the loss of many locations with low error in return for only modest improvements in LE. Even without filtering, the accuracy of the logger was likely sufficient for studies which can accept average location errors of approximately 10 m.

The spatial accuracy of geographic ecological momentary assessment (GEMA): Error and bias due to subject and environmental characteristics

BACKGROUND

Geographic ecological momentary assessment (GEMA) combines ecological momentary assessment (EMA) with global positioning systems (GPS) and geographic information systems (GIS). This study evaluates the spatial accuracy of GEMA location data and bias due to subject and environmental data characteristics.

METHODS

Using data for 72 subjects enrolled in a study of urban adolescent substance use, we compared the GPS-based location of EMA responses in which the subject indicated they were at home to the geocoded home address. We calculated the percentage of EMA locations within a sixteenth, eighth, quarter, and half miles from the home, and the percentage within the same tract and block group as the home. We investigated if the accuracy measures were associated with subject demographics, substance use, and emotional dysregulation, as well as environmental characteristics of the home neighborhood.

RESULTS

Half of all subjects had more than 88% of their EMA locations within a half mile, 72% within a quarter mile, 55% within an eighth mile, 50% within a sixteenth of a mile, 83% in the correct tract, and 71% in the correct block group. There were no significant associations with subject or environmental characteristics.

CONCLUSIONS

Results support the use of GEMA for analyzing subjects' exposures to urban environments. Researchers should be aware of the issue of spatial accuracy inherent in GEMA, and interpret results accordingly. Understanding spatial accuracy is particularly relevant for the development of 'ecological momentary interventions' (EMI), which may depend on accurate location information, though issues of privacy protection remain a concern.

Characterizing and quantifying human movement patterns using GPS data loggers in an area approaching malaria elimination in rural southern Zambia

In areas approaching malaria elimination, human mobility patterns are important in determining the proportion of malaria cases that are imported or the result of low-level, endemic transmission. A convenience sample of participants enrolled in a longitudinal cohort study in the catchment area of Macha Hospital in Choma District, Southern Province, Zambia, was selected to carry a GPS data logger for one month from October 2013 to August 2014. Density maps and activity space plots were created to evaluate seasonal movement patterns. Time spent outside the household compound during anopheline biting times, and time spent in malaria high- and low-risk areas, were calculated. There was evidence of seasonal movement patterns, with increased long-distance movement during the dry season. A median of 10.6% (interquartile range (IQR): 5.8-23.8) of time was spent away from the household, which decreased during anopheline biting times to 5.6% (IQR: 1.7-14.9). The per cent of time spent in malaria high-risk areas for participants residing in high-risk areas ranged from 83.2% to 100%, but ranged from only 0.0% to 36.7% for participants residing in low-risk areas. Interventions targeted at the household may be more effective because of restricted movement during the rainy season, with limited movement between high- and low-risk areas.

How can GPS technology help us better understand exposure to the food environment? A systematic review

Purpose

Global Positioning Systems (GPS) are increasingly being used to objectively assess movement patterns of people related to health behaviours. However research detailing their application to the food environment is scarce. This systematic review examines the application of GPS in studies of exposure to food environments and their potential influences on health.

Methods

Based on an initial scoping exercise, published articles to be included in the systematic review were identified from four electronic databases and reference lists and were appraised and analysed, the final cut-off date for inclusion being January 2015. Included studies used GPS to identify location of individuals in relation to food outlets and link that to health or diet outcomes. They were appraised against a set of quality criteria.

Results

Six studies met the inclusion criteria, which were appraised to be of moderate quality. Newer studies had a higher quality score. Associations between observed mobility patterns in the food environment and diet related outcomes were equivocal. Findings agreed that traditional food exposure measures overestimate the importance of the home food environment.

Conclusions

The use of GPS to measure exposure to the food environment is still in its infancy yet holds much potential. There are considerable variations and challenges in developing and standardising the methods used to assess exposure.

•

Since 2011 just 6 studies have been published employing GPS to quantify exposure to food environments.

•

The studies were generally only of moderate quality.

•

There were significant variations and challenges in the methods and techniques used.

•

GIS neighbourhoods may not well represent food environment exposures based on GPS data.

Adolescents who engage in active school transport are also more active in other contexts: A space-time investigation

BACKGROUND

Although active school travel (AST) is important for increasing moderate-to-vigorous physical activity (MVPA), it is unclear how AST is related to context-specific physical activity and non-school travel. This study investigated how school travel is related to physical activity and travel behaviours across time- and space-classified domains.

METHODS

A total of 196 adolescents wore a Global Positioning System receiver and an accelerometer for 7 days. All data were classified into one of four domains: home, school, transport, or leisure. Generalized linear mixed models were used to compare domain-specific PA and non-school trips between active and passive school travellers.

RESULTS

Active travellers accumulated 13 and 14 more min of MVPA on weekdays and weekend days, respectively. They also spent 15min less time in vehicular travel during non-school trips, and accrued an additional 9min of MVPA while walking on weekend days. However, those with no AST still achieved most of their MVPA in the transport domain.

CONCLUSIONS

AST is related to out-of-school physical activity and transportation, but transport is also important for those who do not use AST. As such, future studies should consider overall mobility and destinations other than school when assessing travel and physical activity behaviours.

Benefits of Mobile Phone Technology for Personal Environmental Monitoring

Background

Tracking individuals in environmental epidemiological studies using novel mobile phone technologies can provide valuable information on geolocation and physical activity, which will improve our understanding of environmental exposures.

Objective

The objective of this study was to assess the performance of one of the least expensive mobile phones on the market to track people's travel-activity pattern.

Methods

Adults living and working in Barcelona (72/162 bicycle commuters) carried simultaneously a mobile phone and a Global Positioning System (GPS) tracker and filled in a travel-activity diary (TAD) for 1 week (N=162). The CalFit app for mobile phones was used to log participants’ geographical location and physical activity. The geographical location data were assigned to different microenvironments (home, work or school, in transit, others) with a newly developed spatiotemporal map-matching algorithm. The tracking performance of the mobile phones was compared with that of the GPS trackers using chi-square test and Kruskal-Wallis rank sum test. The minute agreement across all microenvironments between the TAD and the algorithm was compared using the Gwet agreement coefficient (AC1).

Results

The mobile phone acquired locations for 905 (29.2%) more trips reported in travel diaries than the GPS tracker (P<.001) and had a median accuracy of 25 m. Subjects spent on average 57.9%, 19.9%, 9.0%, and 13.2% of time at home, work, in transit, and other places, respectively, according to the TAD and 57.5%, 18.8%, 11.6%, and 12.1%, respectively, according to the map-matching algorithm. The overall minute agreement between both methods was high (AC1 .811, 95% CI .810-.812).

Conclusions

The use of mobile phones running the CalFit app provides better information on which microenvironments people spend their time in than previous approaches based only on GPS trackers. The improvements of mobile phone technology in microenvironment determination are because the mobile phones are faster at identifying first locations and capable of getting location in challenging environments thanks to the combination of assisted-GPS technology and network positioning systems. Moreover, collecting location information from mobile phones, which are already carried by individuals, allows monitoring more people with a cheaper and less burdensome method than deploying GPS trackers.

The impact of children's exposure to greenspace on physical activity, cognitive development, emotional wellbeing, and ability to appraise risk

INTRODUCTION

The current study utilised objective techniques to investigate the relationship between children's time spent in greenspace (open land covered in grass or other vegetation) with various physical and psychological variables. Potential relationships between physical activity and greenspace with body composition, emotional wellbeing, sensation seeking tendencies, ability to appraise risk, and cognitive development are investigated.

METHODS

108 participants aged 11-14 years from three intermediate schools in Auckland, New Zealand, were assessed. Moderate-to-vigorous physical activity (MVPA) and geolocational data were recorded using accelerometers and portable global positioning system (GPS) receivers (respectively) over a 7-day period in September-December 2014. Body mass index (BMI) and waist-to-height ratio (WHtR) were calculated from height, weight, and waist circumference. Participants also completed online cognitive testing, a computerised risk appraisal tool, and a questionnaire for assessing emotional wellbeing and sensation seeking characteristics. Data analysis took place during February to May 2015. Generalised linear mixed models were used to quantify the associations between MVPA, greenspace exposure, and secondary outcome variables.

RESULTS

Findings confirmed that greenspace exposure is positively associated with MVPA in children (B=0.94; p<0.05). Furthermore, both greenspace exposure and MVPA were related to greater emotional wellbeing, with the former exhibiting a stronger relationship than the latter. Risk-taking and sensation seeking scores were positively associated with MVPA, but not with greenspace exposure. No associations were detected between BMI, WHtR, cognitive domains, and either MVPA or greenspace exposure.

CONCLUSIONS

Findings support the theory that for children, greenspaces are an important environmental influence on physical activity and emotional wellbeing.

Children's GPS-determined versus self-reported transport in leisure time and associations with parental perceptions of the neighborhood environment

Background

This study aimed to examine both GPS-determined and self-reported walking, cycling and passive transport in leisure time during week- and weekend-days among 10 to 12-year old children. Comparisons between GPS-determined and self-reported transport in leisure time were investigated. Second, associations between parental perceptions of the neighborhood environment and GPS-determined walking, cycling and passive transport in leisure time were studied.

Methods

Children (10 to 12-years old; n = 126) wore a GPS device and an accelerometer for 7 consecutive days to assess objectively measured transport in leisure time and filled out a diary to assess self-reported transport in leisure time. Parents completed a questionnaire to assess parental perceptions of the neighborhood environment. Pearson correlations and t-tests were used to test for concurrent validity and differences between GPS-determined and self-reported transport in leisure time. Generalized linear models were used to determine the associations between the parental perceptions of the neighborhood environment and GPS-determined transport in leisure time.

Results

Overall, children under-reported their walking and cycling in leisure time, compared to GPS-determined measures (all p values <0.001). However, children reported their passive transport in leisure time during weekend days quite accurate. GPS-determined measures revealed that children walked most during weekdays (M = 3.96 trips/day; 26.10 min/day) and used passive transport more frequently during weekend days (M = 2.12 trips/day; 31.39 min/day). Only a few parental perceived environmental attributes of the neighborhood (i.e. residential density, land use mix access, quality and availability of walking and cycling facilities, and aesthetics) were significantly associated with children’s GPS-determined walking, cycling or passive transport in leisure time.

Conclusions

To accurately assess children’s active transport in leisure time, GPS measures are recommended over self-reports. More research using GPS with a focus on children’s transport in leisure time and investigating the associations with parental perceptions of the neighborhood environment is needed to confirm the results of the present study.

Electronic supplementary material

The online version of this article (doi:10.1186/s12942-016-0045-9) contains supplementary material, which is available to authorized users.

Quantifying Distance Overestimation From Global Positioning System in Urban Spaces

OBJECTIVES

To investigate accuracy of distance measures computed from Global Positioning System (GPS) points in New York City.

METHODS

We performed structured walks along urban streets carrying Globalsat DG-100 GPS Data Logger devices in highest and lowest quartiles of building height and tree canopy cover. We used ArcGIS version 10.1 to select walks and compute the straight-line distance (Geographic Information System-measured) and sum of distances between consecutive GPS waypoints (GPS-measured) for each walk.

RESULTS

GPS distance overestimates were associated with building height (median overestimate = 97% for high vs 14% for low building height) and to a lesser extent tree canopy (43% for high vs 28% for low tree canopy).

CONCLUSIONS

Algorithms using distances between successive GPS points to infer speed or travel mode may misclassify trips differentially by context. Researchers studying urban spaces may prefer alternative mode identification techniques.

Relationship between Objectively Measured Transportation Behaviors and Health Characteristics in Older Adults

This study used objective Global Positioning Systems (GPS) to investigate the relationship between pedestrian and vehicle trips to physical, cognitive, and psychological functioning in older adults living in retirement communities. Older adults (N = 279; mean age = 83 ± 6 years) wore a GPS and accelerometer for 6 days. Participants completed standard health measures. The Personal Activity and Location Measurement System (PALMS) was used to calculate the average daily number of trips, distance, and minutes traveled for pedestrian and vehicle trips from the combined GPS and accelerometer data. Linear mixed effects regression models explored relationships between these transportation variables and physical, psychological and cognitive functioning. Number, distance, and minutes of pedestrian trips were positively associated with physical and psychological functioning but not cognitive functioning. Number of vehicle trips was negatively associated with fear of falls; there were no other associations between the vehicle trip variables and functioning. Vehicle travel did not appear to be related to functioning in older adults in retirement communities except that fear of falling was related to number of vehicle trips. Pedestrian trips had moderate associations with multiple physical and psychological functioning measures, supporting a link between walking and many aspects of health in older adults.

Physical activity intensity can be accurately monitored by smartphone global positioning system 'app'

Monitoring physical activity is important to better individualise health and fitness benefits. This study assessed the concurrent validity of a smartphone global positioning system (GPS) 'app' and a sport-specific GPS device with a similar sampling rate, to measure physical activity components of speed and distance, compared to a higher sampling sport-specific GPS device. Thirty-eight (21 female, 17 male) participants, mean age of 24.68, s = 6.46 years, completed two 2.400 km trials around an all-weather athletics track wearing GPSports Pro™ (PRO), GPSports WiSpi™ (WISPI) and an iPhone™ with a Motion X GPS™ 'app' (MOTIONX). Statistical agreement, assessed using t-tests and Bland-Altman plots, indicated an (mean; 95% LOA) underestimation of 2% for average speed (0.126 km·h(-1); -0.389 to 0.642; p < .001), 1.7% for maximal speed (0.442 km·h(-1); -2.676 to 3.561; p = .018) and 1.9% for distance (0.045 km; -0.140 to 0.232; p < .001) by MOTIONX compared to that measured by PRO. In contrast, compared to PRO, WISPI overestimated average speed (0.232 km·h(-1); -0.376 to 0.088; p < .001) and distance (0.083 km; -0.129 to -0.038; p < .001) by 3.5% whilst underestimating maximal speed by 2.5% (0.474 km·h(-1); -1.152 to 2.099; p < .001). Despite the statistically significant difference, the MOTIONX measures intensity of physical activity, with a similar error as WISPI, to an acceptable level for population-based monitoring in unimpeded open-air environments. This presents a low-cost, minimal burden opportunity to remotely monitor physical activity participation to improve the prescription of exercise as medicine.

Technologies That Assess the Location of Physical Activity and Sedentary Behavior: A Systematic Review

Background

The location in which physical activity and sedentary behavior are performed can provide valuable behavioral information, both in isolation and synergistically with other areas of physical activity and sedentary behavior research. Global positioning systems (GPS) have been used in physical activity research to identify outdoor location; however, while GPS can receive signals in certain indoor environments, it is not able to provide room- or subroom-level location. On average, adults spend a high proportion of their time indoors. A measure of indoor location would, therefore, provide valuable behavioral information.

Objective

This systematic review sought to identify and critique technology which has been or could be used to assess the location of physical activity and sedentary behavior.

Methods

To identify published research papers, four electronic databases were searched using key terms built around behavior, technology, and location. To be eligible for inclusion, papers were required to be published in English and describe a wearable or portable technology or device capable of measuring location. Searches were performed up to February 4, 2015. This was supplemented by backward and forward reference searching. In an attempt to include novel devices which may not yet have made their way into the published research, searches were also performed using three Internet search engines. Specialized software was used to download search results and thus mitigate the potential pitfalls of changing search algorithms.

Results

A total of 188 research papers met the inclusion criteria. Global positioning systems were the most widely used location technology in the published research, followed by wearable cameras, and radio-frequency identification. Internet search engines identified 81 global positioning systems, 35 real-time locating systems, and 21 wearable cameras. Real-time locating systems determine the indoor location of a wearable tag via the known location of reference nodes. Although the type of reference node and location determination method varies between manufacturers, Wi-Fi appears to be the most popular method.

Conclusions

The addition of location information to existing measures of physical activity and sedentary behavior will provide important behavioral information.