Movement Insights Laboratory: Advancing Metrology in Wearable-based Activity Monitoring
Overview
The Movement Insights Laboratory (MI-Lab) aims to advance the metrology of physical activity and sedentary behaviour, leveraging wearable technology for accurate and reliable measurement. Our research aims to develop sophisticated physical activity measurement methodologies to advance our understanding of the interplay between physical activity, sedentary behaviour, and health.
Key Research Areas
- Metrological characterisation of accelerometer-based wearable devices.
- Method validation of wearable sensors for monitoring physiological outcomes.
- Investigating the impact of physical activity and sedentary behaviour on public health.
Academic and Industry Partners (Past and Present)
Ongoing Research Work
Learning Network for Advanced Behavioural Data Analysis (LABDA) – A European Union (EU) Marie Skłodowska-Curie Actions (MSCA) doctoral network project under Horizon Europe, that aims to establish novel methods for advanced 24/7 movement behaviour data analysis of sensor-based data and to facilitate the use and interpretability of the advanced methods for application in science, policy, and society. LABDA Project 101072993 Grant (Esliger, Sherar, Kingsnorth) €263,146.
SMArT WORK: Stand More At Work – Changing sitting time by providing an environment that makes sitting less likely and standing/moving easier could have significant health benefits. This randomised controlled trial evaluates the effectiveness of providing inexpensive workstations that allow workers to stand, as well as sit, while working on a computer depending on their preference. Department of Health PRP Initiative on Physical Activity (Biddle, Munir, Esliger) £598,885.
Sedentary behaviour in older adults: Investigating a New Therapeutic Paradigm – This grant focuses on investigating the impact of sitting in older adults. This research will inform larger studies and public health initiatives aimed at reducing sitting time in the future. MRC Lifelong Health and Wellbeing (Esliger, Biddle) £853,099.
Non-invasive health and movement sensors – Wearable technology to monitor the time you spend being sedentary could encourage changes in behaviour that helps improve health. However, our research into the growing number of devices which allow individuals to self-monitor their physical activity and/or sedentary behaviour (sitting behaviour), has found that the latter is under-represented in the wearable tech market. EPSRC Small Equipment Grant (Esliger, Sherar, King) £48,000. This funding was part of a larger institutional award.
Current Triaxial Accelerometer Metrology Protocol
List of Accelerometer-based Wearable Devices tested in the laboratory
| Company | Device/s |
|---|---|
| ActiGraph, LLC (USA) | GT3X+, wGT3X-BT, GT9X Link, LEAp |
| ActivInsights Ltd (UK) | GENEActiv, AX3 |
| SENS Innovation ApS (Denmark) | SENS motion device |
| MyZone, Inc. (UK) | MZ3 Tile |
| Apple, Inc. (USA) | Series 7 |
| Fitbit, Inc. (USA) | Charge 3 |
| Google LLC (USA) | Pixel Watch |
| Garmin LLC (USA) | Forerunner 920XT |
| Oura Health Oy (Finland) | Oura Ring |
| Samsung Electronics Co., Ltd (South Korea) | Galaxy Watch |
Featured Publications
- Sherar, L.B., Griew P., Esliger D.W., Cooper A., Ekelund U., Judge K., Riddoch, C.J. International Children’s Accelerometry Database (ICAD): Design and methods, BMC Public Health. 11:485, 2011.
- Esliger, D.W., Rowlands, A.V., Hurst, T.L., Catt, M., Murray, P., Eston, R.G. Validation of the GENEA accelerometer. Med. Sci. Sports Exerc. 43(6): 1085-1093, 2011.
- Takken, T., Stephens, S., Balemans, A., Tremblay, M.S., Esliger, D.W., Schneiderman, J., Biggar, D., Longmuir, P., Wright, V., McCrindle, B., Hendricks, M., Abad, A., van der Net, J., Feldman, B.M. Validation of the Actiheart activity monitor for measurement of activity energy expenditure in children and adolescents with chronic disease. Eur. J. Clin. Nutr. 64(12): 1494-1500, 2010.
- Silva, P., Esliger, D.W., G., Welk, J., Mota. Technical reliability assessment of the Actigraph GT1M accelerometer. Meas. Phys. Ed. Exerc. Sci. 14: 79-91, 2010.
- Esliger, D.W. and M.S. Tremblay. Physical activity and inactivity profiling: The next generation. Can. J. Public Health 98(Suppl. 2) / Appl. Physiol. Nutr. Metab. 32(Suppl. 2E): S195-S207, 2007.
- Esliger, D.W., A. Probert, S. Connor Gorber, S. Bryan, M. Laviolette, and M.S. Tremblay. Validity of the Actical accelerometer step count function. Med. Sci. Sports Exerc. 39(7): 1200-1204, 2007.
- Esliger, D.W. and M.S. Tremblay. Technical reliability assessment of three accelerometer models in a mechanical setup. Med. Sci. Sports Exerc. 38(12): 2171-2181, 2006.
- Esliger, D.W., J.L. Copeland, J.D. Barnes, and M.S. Tremblay. Standardizing and optimizing the use of accelerometer data for free-living physical activity monitoring. J. Phys. Activ. Health 2(3):366-383, 2005.
- Kingsnorth, A.P., Whelan, M.E., Sanders, J.P., Sherar, L.B., & Esliger, D.W. Using digital health technologies to understand the association between movement behaviors and interstitial glucose: exploratory analysis. JMIR mHealth and uHealth 6(5):e9471, 2018.
- Magistro, D., Sessa, S., Kingsnorth, A.P., Loveday, A., Simeone, A., Zecca, M., & Esliger, D.W. A novel algorithm for determining the contextual characteristics of movement behaviors by combining accelerometer features and wireless beacons: development and implementation. JMIR mHealth and uHealth 6(4), e8516, 2018.
- Edwardson, C.L., Yates, T., Biddle, S.J., Davies, M.J., Dunstan, D.W., Esliger, D.W., … & Munir, F. Effectiveness of the Stand More AT (SMArT) Work intervention: cluster randomised controlled trial. BMJ, 363, 2018.
- Atkin, A.J., Biddle, S.J., Broyles, S.T., Chinapaw, M., Ekelund, U., Esliger, D.W., … & van Sluijs, E.M.. Harmonising data on the correlates of physical activity and sedentary behaviour in young people: Methods and lessons learnt from the international Children’s Accelerometry database (ICAD). International Journal of Behavioral Nutrition and Physical Activity, 14, 1-12, 2017.
- Bakrania, K., Yates, T., Rowlands, A.V., Esliger, D.W., Bunnewell, S., Sanders, J., … & Edwardson, C.L. Intensity thresholds on raw acceleration data: Euclidean norm minus one (ENMO) and mean amplitude deviation (MAD) approaches. PloS one, 11(10), e0164045, 2016.
- Stephens, S., Takken, T., Esliger, D.W., Pullenayegum, E., Beyene, J., Tremblay, M., … & Feldman, B. Validation of accelerometer prediction equations in children with chronic disease. Pediatric exercise science, 28(1), 117-132, 2016.