Instrumentation & Measurement Magazine 24-6 - 79

The Assessment of Cognitive and Physical
Well-Being Through Ambient Sensor Measures
of Movement Towards Longitudinal
Monitoring of Activities of Daily Living
Stephanie Bennett, Madison Cohen-McFarlane, Bruce Wallace,
Rafik Goubran, and Frank Knoefel
U
biquitous sensing technologies are a well recognized
concept these days. An individual with a
rudimentary understanding of technology intuitively
understands that their cell phone can track their
whereabouts, detect their activity and communicate with their
home devices. With the increased capability of technology,
measurements have become finer and communication between
devices has become faster and more efficient [1]. With
such sensitive, co-operative systems it seems natural to extend
this technology to measures of health and particularly measures
of health at home and in other enclosed environments.
This paper examines the role of sensor systems in the assessment
of cognitive and physical well-being by first establishing
the connections between well-being, cognition and mobility
before discussing the sensors used to measure these concepts.
Well-being can be defined as simply one's quality of life [2].
A more specific definition is the continuous, physical, mental
and social flourishing of individuals, communities and populations
where their economic needs are cared for within a
thriving ecological environment [3]. In measuring well-being,
there are many subjective and objective indicators used in
the literature as it is a ubiquitous concept, permeating many
aspects of an individual's life including community, culture,
education, economy, environment, government, among many
others [3]. While there is recognition of the importance of considering
well-being on a macroscopic level, measurement of
this concept begins at the individual level, specifically the use
of physical indicators as measured by ambient sensors, to assess
an individual's cognitive and physical well-being.
The assessment of cognitive and physical well-being
being is a multifactorial measurement that begins with understanding
the level to which one's body is functioning. This
is applicable to all ages but is particularly relevant when considering
an older population. There are many models for
measuring aging; one, well recognized measurement is the
frailty index (FI) [4]. The FI considers the body to be an operating
system involving cognition, mobility, function and
co-morbidity components, each with several redundancies.
The FI can be calculated from a health assessment dataset that
September 2021
contains at least 30 variables used to assess and represent the
facets of the operating system. When the system is damaged
through natural aging, illness or disease, there are a number
of other subsystems and redundancies to keep the operating
system running [4]. Over time, this system is subject to wear
and tear, resulting in the loss of redundancy. The degree of
wear and tear and resulting vulnerability to system failure can
be considered analogous to frailty, where loss of redundancy
is operationalized through deficit accumulation. A deficit is
considered to be 'something wrong' with an individual. Following
the extraction of at least 30 variables from a health data
set, a binary value is given for each variable for the individual
to assess if they have a deficit or not. For example, if the variable
indicates the presence or absence of cancer, the individual
would receive a deficit if cancer is present and not if there is
none. The frailty index can therefore be thought of as a simple
ratio of the number of deficits an individual has verses the
number of variables considered. The frailty hypothesis suggests
that critical loss of redundancy results in the failure of
higher order functions such as walking or cognitive multitasking
[4]. Thus, illness can have a direct impact on these higher
order functions that in turn can have a measurable impact on
movement and cognition [5].
The FI is not the only measure of frailty; there is another
highly accepted clinical frailty theory called the clinical
phenotype model. While these theories are fundamentally
different, both acknowledge functional decline as a key
symptom of worsening frailty [6]. These constructs, designed
to measure biological age, support long standing observations
of increased rates of falls and mobility disorders with
increased chronological age [7]. These measured observations
of functional decline have led to the development of
clinical assessment tools focused on assessing and monitoring
balance, mobility and strength in order to predict adverse
outcomes [8]. Some examples include: the timed-up-and-go
test, the Tinetti Balance and Mobility test, the Berg Balance
Scale, the functional reach test, the Edmonton Frail Scale, and
the Hierarchical Assessment of Balance and Mobility (HABAM)
[6], [8], [9]. While functional decline can sometimes be
IEEE Instrumentation & Measurement Magazine
1094-6969/21/$25.00©2021IEEE
79

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