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Gupta, Nidhi
Publications (10 of 10) Show all publications
Hallman, D., Niklas, K., Thorsten Jensen, M., Gupta, N., Birk Jørgensen, M. & Holtermann, A. (2019). Objectively measured sitting and standing in workers: Cross-sectional relationship with autonomic cardiac modulation. International Journal of Environmental Research and Public Health, 16(4), Article ID 650.
Open this publication in new window or tab >>Objectively measured sitting and standing in workers: Cross-sectional relationship with autonomic cardiac modulation
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2019 (English)In: International Journal of Environmental Research and Public Health, ISSN 1661-7827, E-ISSN 1660-4601, Vol. 16, no 4, article id 650Article in journal (Refereed) Published
Abstract [en]

Excessive sitting and standing are proposed risk factors for cardiovascular diseases (CVDs), possibly due to autonomic imbalance. This study examines the association of objectively measured sitting and standing with nocturnal autonomic cardiac modulation. The cross-sectional study examined 490 blue-collar workers in three Danish occupational sectors. Sitting and standing during work and leisure were assessed during 1–5 days using accelerometers. Heart rate (HR) and heart rate variability (HRV) were obtained during nocturnal sleep as markers of resting autonomic modulation. The associations of sitting and standing still (h/day) with HR and HRV were assessed with linear regression models, adjusted for age, gender, body mass index, smoking, and physical activity. More sitting time during leisure was associated with elevated HR (p = 0.02), and showed a trend towards reduced HRV. More standing time at work was associated with lower HR (p = 0.02), and with increased parasympathetic indices of HRV (root mean squared successive differences of R-R intervals p = 0.05; high-frequency power p = 0.07). These findings, while cross-sectional and restricted to blue-collar workers, suggest that sitting at leisure is detrimental to autonomic cardiac modulation, but standing at work is beneficial. However, the small effect size is likely insufficient to mitigate the previously shown detrimental effects of prolonged standing on CVD.

Keywords
age; accelerometer; cardiovascular disease; heart rate variability; occupational health; physical activity
National Category
Occupational Health and Environmental Health
Identifiers
urn:nbn:se:hig:diva-29312 (URN)10.3390/ijerph16040650 (DOI)
Available from: 2019-02-19 Created: 2019-02-19 Last updated: 2019-02-25Bibliographically approved
Gupta, N., Mathiassen, S. E., Mateu-Figueras, G., Heiden, M., Hallman, D., Birk Jørgensen, M. & Holtermann, A. (2018). A comparison of standard and compositional data analysis in studies addressing group differences in sedentary behavior and physical activity. International Journal of Behavioral Nutrition and Physical Activity, 15(1), Article ID 53.
Open this publication in new window or tab >>A comparison of standard and compositional data analysis in studies addressing group differences in sedentary behavior and physical activity
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2018 (English)In: International Journal of Behavioral Nutrition and Physical Activity, ISSN 1479-5868, E-ISSN 1479-5868, Vol. 15, no 1, article id 53Article in journal (Refereed) Published
Abstract [en]

Background. Data on time spent in physical activity, sedentary behavior and sleep during a day is compositional in nature, i.e. they add up to a constant value, typically 100% time. Compositional data have fundamentally different properties from unconstrained data in real space, and require other processing and analysis procedures, referred to as compositional data analysis (CoDA). Most physical activity and sedentary behavior studies, however, still apply analytical procedures adapted to data in real space, which can lead to misleading results. The present study describes a comparison of time spent sedentary and in physical activity between age groups and sexes, and investigates the extent to which results obtained by CoDA differ from those obtained using standard analytical procedures.

Methods. Time spent sedentary, standing, and in physical activity (walking/running/stair climbing/cycling) during work and leisure was determined for 1-4 days among 677 blue-collar workers using accelerometry. Differences between sexes and age groups were tested using MANOVA, using both a standard approach and a CoDA approach based on isometric log-ratio transformed data.  

Results. When determining differences between sexes in time used for different activities at work, the effect size using standard analysis (η2=0.045, p<0.001) was 15% smaller than that obtained with CoDA (η2=0.052, p<0.001), although both approaches suggested a statistically significant difference. When determining corresponding differences between age groups, CoDA resulted in a 60% larger, and significant, effect size (η2=0.012, p=0.02) than that obtained with the standard approach (η2=0.008, p=0.07). During leisure, results with standard (age; η2=0.007, p=0.09; sex; η2=0.052, p<0.001) and CoDA (age; η2=0.007, p=0.09; sex; η2=0.051, p<0.001) analyses were similar.

Conclusion. Results and, hence, inferences concerning differences by age and sex in time spent sedentary and in physical activity at work differed between CoDA and standard analysis. We encourage researchers to use CoDA in similar studies, in order to adequately account for the compositional nature of data on physical activity and sedentary behavior

Keywords
CoDA, accelerometry, MANOVA, isometric log-ratio, gender, age groups
National Category
Occupational Health and Environmental Health
Identifiers
urn:nbn:se:hig:diva-25483 (URN)10.1186/s12966-018-0685-1 (DOI)000435403500001 ()29903009 (PubMedID)2-s2.0-85048626702 (Scopus ID)
Funder
Forte, Swedish Research Council for Health, Working Life and Welfare, 2009-1761
Note

Funding agencies:

- Danish government

- Danish Work Environment Research Fund grant no: 20150017496/4

Available from: 2017-11-02 Created: 2017-11-02 Last updated: 2019-03-12Bibliographically approved
Hulsegge, G., Gupta, N., Proper, K., von Lobenstein, N., IJzelenberg, W., Hallman, D., . . . van der Beek, A. (2018). Shift work is associated with reduced heart rate variability among men but not women. International Journal of Cardiology, 258, 109-114
Open this publication in new window or tab >>Shift work is associated with reduced heart rate variability among men but not women
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2018 (English)In: International Journal of Cardiology, ISSN 0167-5273, E-ISSN 1874-1754, Vol. 258, p. 109-114Article in journal (Refereed) Published
Abstract [en]

Background

Imbalance in the autonomic nervous system due to a disrupted circadian rhythm may be a cause of shift work-related cardiovascular diseases.

Objective

We aimed to determine the association between shift work and cardiac autonomic activity in blue-collar workers.

Methods

The study included 665 blue-collar workers aged 18–68 years in different occupations from two Danish cohort studies. Time and frequency domain parameters of heart rate variability (HRV) were measured during sleep using the Actiheart monitor, and used as markers of cardiac autonomic function. Multiple linear regression analyses were used to investigate differences in HRV between day and shift workers.

Results

Shift workers had no significantly different HRV parameters than day workers, except for a lower VLF (B: 0.21; 95% CI: −0.36–0.05). The lower VLF was only present among non-night shift workers (p < 0.05) and not among night shift workers (p > 0.05). Results differed significantly by gender (p for interaction < 0.10): among men, shift work was negatively associated with RMSSD (B: −7.83; 95% CI: −14.28–1.38), SDNN (B: −7.0; 95% CI: −12.27–1.78), VLF (B: −0.27; 95% CI: −0.46–0.09) and Total Power (B: −0.61; 95% CI: −1.20–0.03), while among women, shift work was only associated with the LF/HF ratio (B: −0.29; 95% CI: −0.54–0.03).

Conclusion

Shift work was particularly associated with lower HRV during sleep among men. This indicates that shift work causes imbalance in the autonomic nervous system among men, which might increase their risk of cardiovascular diseases.

Keywords
Shift work, Night shift, Heart rate variability, Cardiovascular diseases, Autonomic nervous system
National Category
Occupational Health and Environmental Health
Identifiers
urn:nbn:se:hig:diva-26050 (URN)10.1016/j.ijcard.2018.01.089 (DOI)000427605700023 ()29433969 (PubMedID)2-s2.0-85041530029 (Scopus ID)
Available from: 2018-01-23 Created: 2018-01-23 Last updated: 2018-11-26Bibliographically approved
Straker, L., Hallman, D., Gupta, N., Mathiassen, S. E. & Holtermann, A. (2018). The Goldilocks Principle: Innovative work design for improved health. In: : . Paper presented at 20th Congress International Ergonomics Association, 26-30 augusti, 2018, Florens, Italy.
Open this publication in new window or tab >>The Goldilocks Principle: Innovative work design for improved health
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2018 (English)Conference paper, Oral presentation with published abstract (Refereed)
National Category
Occupational Health and Environmental Health
Identifiers
urn:nbn:se:hig:diva-27832 (URN)
Conference
20th Congress International Ergonomics Association, 26-30 augusti, 2018, Florens, Italy
Available from: 2018-09-04 Created: 2018-09-04 Last updated: 2018-09-07Bibliographically approved
Palm, P., Forsman, M., Mathiassen, S. E., Gupta, N. & Holtermann, A. (2018). Upper arm elevation in blue‐collar work with and without exclusion of arm elevation during sitting. In: : . Paper presented at 20th Congress International Ergonomics Association, 26-30 augusti, 2018, Florens, Italy.
Open this publication in new window or tab >>Upper arm elevation in blue‐collar work with and without exclusion of arm elevation during sitting
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2018 (English)Conference paper, Oral presentation with published abstract (Refereed)
National Category
Occupational Health and Environmental Health
Identifiers
urn:nbn:se:hig:diva-27830 (URN)
Conference
20th Congress International Ergonomics Association, 26-30 augusti, 2018, Florens, Italy
Available from: 2018-09-04 Created: 2018-09-04 Last updated: 2018-09-07Bibliographically approved
Gupta, N., Heiden, M., Mathiassen, S. E. & Holtermann, A. (2016). Improving questionnaire-based estimates of occupational physical activity of blue-collar workers by individual and work related information. In: : . Paper presented at Ninth International Conference on the Prevention of Work-Related Musculoskeletal Disorders (PREMUS), June 20-23, 2016, Toronto, Canada.
Open this publication in new window or tab >>Improving questionnaire-based estimates of occupational physical activity of blue-collar workers by individual and work related information
2016 (English)Conference paper, Published paper (Refereed)
Abstract [en]

Background. Questionnaire-based information of occupational physical activities is extensively used, but susceptible to systematic errors. Calibration modeling may reduce errors and improve precision of questionnaire-based information by transforming the selfreported data into more correct estimates of “true” exposure. We aimed (1) to determine the ability of unadjusted ratings of Saltin and Grimby’s Occupational Physical Activity (SGOPA) question to estimate objectively measured sedentary behaviour, physical activity and cardiovascular load, and (2) to develop and evaluate statistical models calibrating SGOPA ratings into expected values of objectively measured exposures.

Methods. 214 blue-collar workers responded to a questionnaire comprising the SGOPA question and questions on several individual and work-related factors. They wore two accelerometers measuring time spent in sedentary and in physical activities, and one Actiheart monitoring cardiovascular load (eventually expressed as %Heart Rate Reserve) for one to four days. Least-squares linear regression models were developed to predict each objectively measured exposure from SGOPA and additional self-reported individual and work-related predictors.

Results. SGOPA alone explained 22% (R2 adjusted=21%) of the variance between individuals in sedentary behaviour and physical activities, and 8% (R2 adjusted =7%) of the variance in high cardiorespiratory load. When adding predictors related to individual and work to the regression model, explained variance increased to 51% (R2 adjusted=46%) for both sedentary behaviour and physical activities, and to 27% (R2 adjusted=19%) for high cardiorespiratory load. Bootstrap validation suggested that explained variance would be reduced by 9-15% for the three exposures when using the model on other data sets.

Discussion. SGOPA itself shows only limited ability to predict objectively measured sedentary behaviour, physical activities and cardiovascular load at work, but the performance of a calibration model can be considerably improved by adding further self-reported predictors.

National Category
Occupational Health and Environmental Health
Identifiers
urn:nbn:se:hig:diva-21911 (URN)
Conference
Ninth International Conference on the Prevention of Work-Related Musculoskeletal Disorders (PREMUS), June 20-23, 2016, Toronto, Canada
Available from: 2016-06-23 Created: 2016-06-23 Last updated: 2018-12-03Bibliographically approved
Hallman, D. M., Mathiassen, S. E., Heiden, M., Gupta, N., Birk Jørgensen, M. & Holtermann, A. (2016). Temporal patterns of sitting at work are associated with neck-shoulder pain in blue-collar workers: a cross-sectional analysis of accelerometer data in the DPHACTO study. International Archives of Occupational and Environmental Health, 89(5), 823-833
Open this publication in new window or tab >>Temporal patterns of sitting at work are associated with neck-shoulder pain in blue-collar workers: a cross-sectional analysis of accelerometer data in the DPHACTO study
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2016 (English)In: International Archives of Occupational and Environmental Health, ISSN 0340-0131, E-ISSN 1432-1246, Vol. 89, no 5, p. 823-833Article in journal (Refereed) Published
Abstract [en]

Background

Our aim was to examine the extent to which temporal patterns of sitting during occupational work and during leisure-time, assessed using accelerometry, are associated with intense neck–shoulder pain (NSP) in blue-collar workers.

Methods

The population consisted of 659 Danish blue-collar workers. Accelerometers were attached to the thigh, hip, trunk and upper dominant arm to measure sitting time and physical activity across four consecutive days. Temporal sitting patterns were expressed separately for work and leisure by the proportion of total time spent sitting in brief bursts (0–5 min), moderate (>5–20 min) and prolonged (>20 min) periods. The peak NSP intensity during the previous 3 months was assessed using a numerical rating scale (range 0–10) and dichotomized into a lower (≤4) and higher (>4) NSP score. Logistic regression analyses with multiple adjustments for individual and occupational factors were performed to determine the association between brief, moderate and prolonged sitting periods, and NSP intensity.

Results

Time in brief bursts of occupational sitting was negatively associated with NSP intensity (adjusted OR 0.68, 95 % CI 0.48–0.98), while time in moderate periods of occupational sitting showed a positive association with NSP (adjusted OR 1.32, 95 % CI 1.04–1.69). Time in prolonged periods of occupational sitting was not associated with NSP (adjusted OR 0.78, 95 % CI 0.78–1.09). We found no significant association between brief, moderate or prolonged sitting periods during leisure, and NSP.

Conclusion

Our findings indicate that the association between occupational sitting time and intense NSP among blue-collar workers is sensitive to the temporal pattern of sitting.

Keywords
neck pain, sedentary, time-pattern, physical activity, occupational health
National Category
Occupational Health and Environmental Health
Identifiers
urn:nbn:se:hig:diva-20204 (URN)10.1007/s00420-016-1123-9 (DOI)000376408900011 ()26935311 (PubMedID)2-s2.0-84959513588 (Scopus ID)
Projects
SitNeck
Note

Erratum to: Temporal patterns of sitting at work are associated with neck–shoulder pain in blue-collar workers: a cross-sectional analysis of accelerometer data in the DPHACTO study (International Archives of Occupational and Environmental Health, (2016),  http://dx.doi.org/10.1007/s00420-017-1208-0

ScopusId: 2-s2.0-85013041600ISI-id: 000403772400007

Available from: 2015-09-04 Created: 2015-09-04 Last updated: 2019-01-08Bibliographically approved
Gupta, N., Heiden, M., Aadahl, M., Korshøj, M., Birk Jørgensen, M. & Holtermann, A. (2016). What is the effect on obesity indicators from replacing prolonged sedentary time with brief sedentary bouts, standing and different types of physical activity during working days?: A cross-sectional accelerometer-based study among blue-collar workers. PLoS ONE, 11(5), Article ID e0154935.
Open this publication in new window or tab >>What is the effect on obesity indicators from replacing prolonged sedentary time with brief sedentary bouts, standing and different types of physical activity during working days?: A cross-sectional accelerometer-based study among blue-collar workers
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2016 (English)In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 11, no 5, article id e0154935Article in journal (Refereed) Published
Abstract [en]

Introduction

The aim of the study was to investigate if (a) substituting total sedentary time or long sedentary bouts with standing or various types of physical activity and (b) substituting long sedentary bouts with brief sedentary bouts; is associated with obesity indicators using a cross sectional isotemporal substitution approach among blue-collar workers.

Methods

A total of 692 workers from transportation, manufacturing and cleaning sectors wore an Actigraph GT3X+ accelerometer on the thigh for 1–4 working days. The sedentary (sit and lie), standing, walking, and moderate to vigorous physical activity (MVPA) time on working days was computed using validated Acti4 software. The total sedentary time and uninterrupted sedentary time spent in brief (≤5 mins), moderate (>5 and ≤30 mins), and long (>30mins) bouts, were determined for the whole day and during work and non-work time separately. The obesity indicators, BMI (kg/m2), waist circumference (cm) and fat percentage were objectively measured. Isotemporal substitution modelling was utilized to determine the linear association with obesity indicators of replacing 30 min of total sedentary time or long sedentary bouts with standing, walking or MVPA and separately replacing 30 min of long sedentary bouts with brief sedentary bouts.

Results

Workers [mean (standard deviation, SD); age = 45.1 (9.9) years, BMI = 27.5 (4.9) kg/m2, %BF = 29.6 (9.5), waist circumference = 94.4 (13.0) cm] sat for 2.4 hours (~32% of the measured time, SD = 1.8 hours) across the day during work period and 5.5 hours (~62% of the measured time, SD = 1.5 hours) during non-work period. Most of the sedentary time was accrued in moderate bouts [work = 1.40 (SD = 1.09) hours] during work and in long bouts during non-work [2.7 (SD = 1.4) hours], while least in long sedentary bouts during work [work = 0.5 (SD = 0.9)] and in brief sedentary bouts [0.5 hours (SD = 0.3)] during non-work. Significant associations with all obesity indicators were found when 30 min of total sedentary time or long sedentary bouts were replaced with standing time (~1–2% lower) or MVPA (~4–9% lower) during whole day, work, and non-work periods. The exception was that a statistically significant association was not observed with any obesity indicator when replacing total sedentary time or long sedentary bouts with standing time during the work period. Significant beneficial associations were found when replacing the long sedentary bouts with brief sedentary bouts (~3–5% lower) during all domains.

Conclusion

Replacing total sedentary time and long sedentary bouts, respectively, not only with MVPA but also standing time appears to be beneficially associated with obesity indicators among blue-collar workers. Additionally, replacing long sedentary bouts with brief sedentary bouts was also beneficially associated with obesity indicators. Studies using prospective design are needed to confirm the findings.

National Category
Occupational Health and Environmental Health
Identifiers
urn:nbn:se:hig:diva-21509 (URN)10.1371/journal.pone.0154935 (DOI)000376282300014 ()27187777 (PubMedID)2-s2.0-84969131643 (Scopus ID)
Available from: 2016-05-19 Created: 2016-05-19 Last updated: 2018-12-03Bibliographically approved
Gupta, N., Storda Christiansen, C., Hallman, D., Korshøj, M., Gomes Carneiro, I. & Holtermann, A. (2015). Is Objectively Measured Sitting Time Associated with Low Back Pain?: A Cross-Sectional Investigation in the NOMAD study. PLoS ONE, 10(3), Article ID e0121159.
Open this publication in new window or tab >>Is Objectively Measured Sitting Time Associated with Low Back Pain?: A Cross-Sectional Investigation in the NOMAD study
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2015 (English)In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 10, no 3, article id e0121159Article in journal (Refereed) Published
Abstract [en]

Background: Studies on the association between sitting time and low back pain (LBP) have found contrasting results. This may be due to the lack of objectively measured sitting time or because socioeconomic confounders were not considered in the analysis.

Objectives: To investigate the association between objectively measured sitting time (daily total, and occupational and leisure-time periods) and LBP among blue-collar workers.

Methods: Two-hundred-and-one blue-collar workers wore two accelerometers (GT3X+ Actigraph) for up to four consecutive working days to obtain objective measures of sitting time, estimated via Acti4 software. Workers reported their LBP intensity the past month on a scale from 0 (no pain) to 9 (worst imaginable pain) and were categorized into either low (≤5) or high (>5) LBP intensity groups. In the multivariate-adjusted binary logistic regression analysis, total sitting time, occupational and leisure-time sitting were both modeled as continuous (hours/day) and categorical variables (i.e. low, moderate and high sitting time).

Results: The multivariate logistic regression analysis showed a significant positive association between total sitting time (hours) and high LBP intensity (odds ratio; OR=1.43, 95%CI=1.15-1.77, P=0.01). Similar results were obtained for leisure-time sitting (OR=1.45, 95%CI= 1.10-1.91, P=0.01), and a similar but non-significant trend was obtained for occupational sitting time (OR=1.34, 95%CI 0.99-1.82, P=0.06). In the analysis on categorized sitting time, high sitting time was positively associated with high LBP for total (OR=3.31, 95%CI= 1.18-9.28, P=0.03), leisure (OR=5.31, 95%CI= 1.57-17.90, P=0.01), and occupational (OR=3.26, 95%CI= 0.89-11.98, P=0.08) sitting time, referencing those with low sitting time.

Conclusion: Sitting time is positively associated with LBP intensity among blue-collar workers. Future studies using a prospective design with objective measures of occupational sitting time are recommended.

Keywords
Occupational and leisure-time sitting, accelerometer, Actigraph GT3X+, 24h measurements, sedentary lifestyle, leisure time
National Category
Occupational Health and Environmental Health
Identifiers
urn:nbn:se:hig:diva-17429 (URN)10.1371/journal.pone.0121159 (DOI)000351880000132 ()25806808 (PubMedID)2-s2.0-84926034896 (Scopus ID)
Projects
SitNeck
Available from: 2014-08-28 Created: 2014-08-28 Last updated: 2018-03-13Bibliographically approved
Hallman, D., Gupta, N., Mathiassen, S. E., Korshøj, M. & Holtermann, A. (2015). Temporal patterns of physical activity during work and leisure: exposure variation analysis of accelerometer recordings processed by the ACTI4 software. In: : . Paper presented at 4th International Conference on Ambulatory Monitoring of Physical Activity and Movement (ICAMPAM), June 10-12, 2015, Limerick, Ireland (pp. 11).
Open this publication in new window or tab >>Temporal patterns of physical activity during work and leisure: exposure variation analysis of accelerometer recordings processed by the ACTI4 software
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2015 (English)Conference paper, Published paper (Other academic)
Abstract [en]

Introduction

Previous studies have found substantial differences in the health effects of occupational (OPA) and leisure time physical activity (LTPA): LTPA is generally beneficial to health, while OPA may be detrimental. Why these differences occur is, however, so far not clear. Different time patterns of OPA and LTPA may be an explanation. Thus, we aimed to investigate the extent to which time patterns of OPA and LTPA differ in a population of blue-collar workers.

Methods

This study was conducted on a cross-sectional sample of 191 blue-collar workers from seven workplaces in Denmark. Physical activity and sedentary behavior were estimated using the Acti4 method on recordings from accelerometers (Actigraph GT3X+) worn on the thigh and trunk for four consecutive days. Time patterns of OPA and LTPA were retrieved separately for work and leisure using Exposure Variation Analysis (EVA), and expressed in terms of percentage time spent in uninterrupted periods of different durations (<1min, 1-5 min, 5-10 min, 10-30 min, 30-60 min and > 60 min) of sitting, standing, and walking. Differences between OPA and LTPA in selected EVA derivatives were tested using repeated measures ANOVA with adjustments for differences between work and leisure in total time for each activity.

Results

We found significant differences between work and leisure time for several EVA derivatives, with OPA showing a larger percentage time walking and standing in short periods (<5 min), and less percent time in prolonged sitting (>30 min) than LTPA. Apart from standing (p=.10), these differences remained significant even after adjusting for the difference between work and leisure in total time spent in each activity.

Conclusion

We found, among blue-collar workers, that the time patterns of OPA and LTPA were markedly different even after adjustment for total PA time. We suggest using EVA derivatives in future studies investigating potential associations of OPA and LTPA with health outcomes.

National Category
Occupational Health and Environmental Health
Identifiers
urn:nbn:se:hig:diva-19685 (URN)
Conference
4th International Conference on Ambulatory Monitoring of Physical Activity and Movement (ICAMPAM), June 10-12, 2015, Limerick, Ireland
Projects
SitNeck
Note

Symposium "A Holistic approach in measuring occupational physical activity: challenges and potentials"

Available from: 2015-06-16 Created: 2015-06-16 Last updated: 2018-12-03Bibliographically approved

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