Advantages sitting, standing, walking, running, and cycling

Advantages
of using accelerometers include detailed data about intensity, frequency, and
duration of physical activity, they are relatively inexpensive, small, and
non-invasive. The memory capacity increases nowadays, so data can be collected
over longer period of time. However, they are not suitable for all physical
activities, especially those that require the activity of the upper body parts.
Also, data are not measured in commonly used units and transformation of units
is time demanding (Strath et al., 2013). One of
the important advantages of accelerometers is the possibility to detect seated
postures and transitions between seated and standing postures. Yet, only few of
them can measure light-intensity physical activity and sedentary behaviour
(Ainsworth et al., 2015).

There
is a number of motion sensors commercially available for the assessment of
physical activity. Plasqui et al. (2013) compared validity of accelerometers
used in 15 different validation studies and proposed the necessity of
validation of accelerometers against doubly labelled water method. Although
accelerometers provide daily data in the assessment of physical activity and
doubly labelled water provides a measure of energy expenditure over a period of
time and both methods are prone to the error, for the most accurate measures of
physical activity both methods should be used complementarily (Plasqui et al., 2013).
In the study of Lee et al. (2014), eight different types
of motion sensors were investigated for the accuracy to estimate energy
expenditure. Participants wore all of them at the same time during activity
routine of 13 different activities categorized into sedentary, walking, running
and moderate-to vigorous activities. Devices were validated against ActiGraph, as the one most commonly used and almost
all of them showed good potential for the assessment of physical activity (Lee, Kim and Welk, 2014).

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The
technology development provides opportunities to improve physical activity
assessment methods and overcome disadvantages of current methods. Pedometers
and most of accelerometers detect movements in the vertical plane. But some
accelerometers are sensitive to two or three planes and able to detect
different physical activities (McCarthy & Grey,
2015). Triaxial accelerometers show a high
sensitivity for sitting, standing, walking, running, and cycling (Skotte,
Korshøj, Kristiansen, Hanisch & Holtermann, 2014). Gatti et al. (2015)
found excellent reliability and validity of a triaxial accelerometer placed at
the waist and shank during running and pedal-revolution counts during bicycling
(Gatti, Stratford, Brenneman & Maly, 2015). They also have a
potential to be used to measure upper extremity physical activity, especially
if worn on wrists. That way they monitor arm usage and even detect differences
in slow arm movements, suggesting the importance in their usage during
rehabilitation (Lawinger, Uhl, Abel & Kamineni,
2015). Still, Pediši? and Bauman (2014) suggest that the use of motion sensors
is general population studies is still limited due to different study designs,
validity, between-study comparability and simplicity. Further
problem that could occur with motion sensors is limitation in cooperation with
participants. Participants could easily forget or refuse to wear them, and they
usually remove them during sleep and water-related activities (Dunton et al.,
2014).

 

The
use of motion sensors in clinical studies

Sedentary
behaviour increases the risk of chronic diseases and it is now identified as
one of the leading causes of global mortality. For this reason, physical
activity has important benefits in the general population and the World Health
Organisation (WHO) recognises its importance in health. Research in this area
provides important information about the dose-response relationship between
physical activity and health. This, together with the valid methods for the
assessment of physical activity, offers necessary information to make an
intervention plan to reduce sedentary behaviour (WHO, 2010). It is required to
address physical inactivity and develop specific interventions and implement
them at the national levels to increase physical activity among population and,
thus, decrease the burden of disease (Bauman, Merom,
Bull, Buchner & Fiatarone Singh, 2016).

Understanding
the consequence of lifestyle and not only genetic factors in the development of
many diseases, current recommendations for their prevention include physical
activity. Motion sensors can be used to examine at which levels physical
activity can affect metabolic changes in
diabetic patients and be clinically beneficial (Herzig
et al. 2013). By using a motion sensor among patients with diabetes, low
levels of physical activity in patients, in term of total energy expenditure,
number of steps, and duration of physical activity, are observed (Fagour et al., 2013). Similarly, low levels physical
activity are detected among people with depressive and anxiety disorders,
measured by using accelerometer. Grounding the results on accelerometer
measures, it is recommended that for this type of patients, light physical
activity is more efficient than high-intensity physical activity in reducing
the disorders manifestation (Helgadóttir, Forsell &
Ekblom, 2015).

By recognizing the consequences of sedentary behaviour
in the development of diseases and the importance of physical activity to
improve health outcomes, motion sensors become very important monitoring and
interventional tools. It is reported that they can be used as intervention to
improve glucose metabolism with increase in physical activity in diabetic
patients (Miyazaki & Kotani, 2015).
Pedometer-driven physical activity is used as an intervention to increase
physical activity and consequently improve health. This is confirmed for
several diseases, such as diabetes (Guglani, Shenoy and
Sandhu, 2014), obesity (Cai et al., 2016),
mental illness (Helgadóttir et al., 2015), musculoskeletal
diseases (Mansi et al., 2014), and chronic
obstructive pulmonary disease (Mendoza et al., 2014).
Still, future studies are required for further clarification.

 

Conclusions

By
understanding the effect of physical inactivity on health, there is a need for
validated methods that measure physical activity and inactivity. There is no
gold standard for motion sensors and the choice of the optimal motion sensor is
complex. Motion sensors eliminate the problems of subjective methods, but they
are more money and time consuming and as discussed, they have their own
(dis)advantages. Motion sensors have the advantage of cost, non-invasiveness
and clear data. Still, there are lot limitations and it is suggested to use
them simultaneously with other physical assessment methods to improve the data
quality. A large heterogeneity in assessment of different types of motion
sensors across studies exists and data need to be interpreted with a caution. Yet,
they provide very important data in clinical studies. Not only that motion
sensors can be used in monitoring, but also in health intervention. The valid
interpretation of data in these studies can help in minimizing sedentary
behaviour and improve the assessment of health outcomes associated with
increased physical activity. Further research is necessary to support the use
of motion sensors interventions as long term interventions for chronic
diseases.