Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Editorial
. 2023 Apr 19;23(8):4091.
doi: 10.3390/s23084091.

Sensors for Human Physical Behaviour Monitoring

Malcolm Granat  1 , Andreas Holtermann  2 , Kate Lyden  3
Affiliations
Editorial

Sensors for Human Physical Behaviour Monitoring

Malcolm Granat et al. Sensors (Basel). .

Abstract

The understanding and measurement of physical behaviours that occur in everyday life are essential not only for determining their relationship with health, but also for interventions, physical activity monitoring/surveillance of the population and specific groups, drug development, and developing public health guidelines and messages [...].

PubMed Disclaimer

Conflict of interest statement

The authors declare no conflict of interest.

References

    1. Mellema M., Gjovaag T. Reported Outcome Measures in Studies of Real-World Ambulation in People with a Lower Limb Amputation: A Scoping Review. Sensors. 2022;22:2243. doi: 10.3390/s22062243. - DOI - PMC - PubMed
    1. Ahmadi M.N., Pavey T.G., Trost S.G. Machine Learning Models for Classifying Physical Activity in Free-Living Preschool Children. Sensors. 2020;20:4364. doi: 10.3390/s20164364. - DOI - PMC - PubMed
    1. Russell B., McDaid A., Toscano W., Hume P. Predicting Fatigue in Long Duration Mountain Events with a Single Sensor and Deep Learning Model. Sensors. 2021;21:5442. doi: 10.3390/s21165442. - DOI - PMC - PubMed
    1. Griffiths B., Diment L., Granat M.H. A Machine Learning Classification Model for Monitoring the Daily Physical Behaviour of Lower-Limb Amputees. Sensors. 2021;21:7458. doi: 10.3390/s21227458. - DOI - PMC - PubMed
    1. Hettiarachchi P., Aili K., Holtermann A., Stamatakis E., Svartengren M., Palm P. Validity of a Non-Proprietary Algorithm for Identifying Lying Down Using Raw Data from Thigh-Worn Triaxial Accelerometers. Sensors. 2021;21:904. doi: 10.3390/s21030904. - DOI - PMC - PubMed

Publication types