Introduction Gardiner, Cavalheri, Jenkins & Healy, 2015), mental illness

Introduction

The
adverse effects of sedentary behaviour and benefits of physical activity on
health have recently come to the fore. A number of studies support the fact
that physical activity can reduce effects of sedentary behaviours and the
interventions to increase physical activity become widespread (Swartz, Rote, Cho, Welch & Strath, 2014;
Aparicio-Ugarriza et al., 2015). Sedentary behaviour is associated with a wide
spectrum of chronic disorders, including chronic obstructive pulmonary disease
(Hill, Gardiner, Cavalheri, Jenkins & Healy, 2015), mental illness (Zhai, Zhang & Zhang, 2014; Hoare,
Milton, Foster & Allender, 2016), some types of cancer (Cong et al., 2013,
Schmid & Leitzmann, 2014), and cardiometabolic disorders and related
mortality (Hamilton, Hamilton & Zderic, 2014; Peterson, Charlson, Wells
& Altemus, 2014; Saunders, Chaput & Tremblay, 2014; Chau et al., 2015). For these reasons, it is of great importance to provide valid
methods for the assessment of physical activity and to better understand the
relationship between physical activity and health so that the success of
interventions can be determined. The ultimate goal is the identification of
optimal physical activity to reduce health risks in general population
(Ainsworth, Cahalin, Buman & Ross, 2015).

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There are various subjective and objective
methods to assess physical activity. Subjective methods, such as
questionnaires, diaries, interviews, and direct observation, are inexpensive
methods to assess physical activity in many situations and are commonly used in
studies with a large number of participants. However, the assessment results
might not be precise because they depend on subjective
observation and interpretation. On the other hand, objective
methods for the assessment of physical activities offer an opportunity to
obtain more accurate data about physical activity. These include direct and
indirect calorimetry, physiological measurements, such as Doubly Labelled Water
method, and mechanical and electronic monitors, including accelerometers, pedometers,
and heart-rate monitors (Hills, Mokhtar & Byrne, 2014). Still, the precise quantification of physical activity can be difficult,
and the choice of assessment method is influenced by different factors, such as
age, gender, and body weight. Also, type of physical activity, the objectivity
of the data, and a cost-efficiency should be taken into consideration (Sylvia,
Bernstein, Hubbard, Keating & Anderson, 2014).

The aim of this literature review is to provide
an overview of advantages and
disadvantages of motion sensors, as well as their
reliability and validity in the assessment of physical activity. This review will also provide information about the
use of motion sensors and possible interventions in clinical research studies.

 

Motion sensors in assessment physical activity

Subjective
assessments of physical activity have been used for a long time because they
are cost-effective, easily adaptable to different types of research, and
generally accepted. They provided significant information regarding the
relationship between physical activity and health. However, they are not very
precise and rely on subjective interpretations and consequently lead to underestimation
or overestimation of physical activity. The introduction of objective methods
to assess physical activity reduced human error and provided a more accurate
estimation of physical activity and energy expenditure (Ainsworth
et al. 2015).

Wearable
motion sensors (accelerometers and pedometers) are popular tools for objective
assessment. Pedometers are used to measure steps and distance while
accelerometers measure acceleration and movement (Strath
et al., 2013). Pedometers are motion sensors that record movement in
terms of steps taken. Early forms of pedometers used mechanical sensors that
identified steps based on the force generated during walking. Nowadays, with
the advancement of technologies, they use microelectromechanical systems to
identify steps which considerably increased their accuracy. Most of them are
hip-worn, but it is suggested that the more accurate position should be the
ankle. Furthermore, some recent models also allow measurement of energy
expenditure, acceleration, and sleep (Plasqui, Bonomi
& Westerterp, 2013). Accelerometers provide information about type,
frequency, intensity, and duration of physical activity, and, thus, they are
commonly used in research studies. Similar to
pedometers, they are typically hip-worn, but can also be fixed to ankles or
wrists. It is proposed that the more accurate position to wear accelerometers
is the lower back or hip, i.e. closer to the centre of the mass. They rely on
microelectromechanical systems to record acceleration and objectively capture
body movements. Thanks to the technology advancements, they can detect types of
physical activity and energy expenditure. There are many commercially available
accelerometers with different characteristics making the choice of the most
suitable accelerometer very difficult. (Plasqui et al.,
2013; Ainsworth et al., 2015)

Not
only that the use of accelerometers increases in recent years, but with
technology improvements, there is a tendency to insert them into smartphones as they are regularly used in everyday lives,
especially among adolescents. It is proposed that designed application for
mobile phones should be used with other objective assessment monitors, which
will improve the quality of collected data (Dunton et
al., 2014; Shoaib, Bosch, Incel, Scholten & Havinga, 2014). On the other
hand, there is a high inaccuracy of smartphone pedometer applications, which
suggests caution in the interpretation of smartphone application data (Orr et
al., 2015).

 

Advantages and disadvantages of motion sensors

The
use of wearable motion sensors, such as pedometers and accelerometers, in
physical activity assessment increases in research and clinical assessment.
However, the choice of the most adequate monitor will depend on several
factors: research goal, target population, physical activity characteristics,
cost-efficiency, and required measurement precision (Ainsworth
et al., 2015).

Pedometers
are inexpensive and present a low burden for participants. Further, they can be
used in studies with many participants and data obtained from pedometers are
easily processed.  But pedometers do not
measure intensity or duration of physical activity and are not accurate for
assessment of energy expenditure (Strath et al., 2013).
Pedometers also
fail to be accurate at slower walking speeds or when worn at pockets or wrists
and they cannot detect sedentary activities, posture, and energy expenditure
(Ainsworth et al., 2015).

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 a 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 a 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 the 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).

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 of 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. The
further problem that could occur with motion sensors is the 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 the 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, a
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 an intervention to improve glucose metabolism with an 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 the 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.