| Literature DB >> 32010456 |
Maik Sliepen1, Matthijs Lipperts2, Marianne Tjur3, Inger Mechlenburg3,4.
Abstract
Studies of the effectiveness of orthopaedic interventions do not generally measure physical activity (PA). Applying accelerometer-based activity monitoring in orthopaedic studies will add relevant information to the generally examined physical function and pain assessment.Accelerometer-based activity monitoring is practically feasible in orthopaedic patient populations, since current day activity sensors have battery time and memory to measure continuously for several weeks without requiring technical expertise.The ongoing development in sensor technology has made it possible to combine functional tests with activity monitoring.For clinicians, the application of accelerometer-based activity monitoring can provide a measure of PA and can be used for clinical comparisons before and after interventions.In orthopaedic rehabilitation, accelerometer-based activity monitoring may be used to help patients reach their targets for PA and to coach patients towards a more active lifestyle through direct feedback. Cite this article: EFORT Open Rev 2019;4:678-685. DOI: 10.1302/2058-5241.4.180041.Entities:
Keywords: accelerometry; activity monitoring; clinical outcome measure; orthopaedics; patient feedback
Year: 2020 PMID: 32010456 PMCID: PMC6986392 DOI: 10.1302/2058-5241.4.180041
Source DB: PubMed Journal: EFORT Open Rev ISSN: 2058-5241
Fig. 1An accelerometry-based activity sensor worn laterally on the thigh.
Validation studies on the physical activities identifiable by various algorithms
| Study | Year | Single sensor or multi-site system | Postures and activities |
|---|---|---|---|
| De Vries et al[ | 2011 | Single sensor | Sitting, standing, stairs, cycling, walking |
| Ermes et al[ | 2008 | Multi-site system | Lying, sitting, standing, (Nordic) walking, football, cycling, running |
| Khan et al[ | 2010 | Single sensor | Resting, stairs, walking, running, vacuuming |
| Nyan et al[ | 2006 | Multi-site system | Walking, climbing and descending stairs |
| Lipperts et al[ | 2017 | Single sensor | Sitting, standing, sit-stand transitions, cycling, climbing and descending stairs, step count |
| Fortune et al[ | 2014 | Multi-site system | Lying, sitting, standing, walking, jogging |
| O’Donoghue et al[ | 2014 | Single sensor | Sitting, standing, sit-stand transitions, walking, step count |
| Laudanski et al[ | 2015 | Multi-sensor system | Walking, climbing and descending stairs |
Example of identification algorithm output
| Start time (s) | Stop time (s) | Activity |
|---|---|---|
| 0.00 | 120.55 | Sitting |
| 120.55 | 128.05 | Walking |
| 128.05 | 150.00 | Standing |
| 150.00 | 165.00 | Walking |
| 165.00 | 173.00 | Stair climbing (up) |
Fig. 2An overview of activity sensors' wear locations.