Instrumentation & Measurement Magazine 24-6 - 62

Table 2 - Examples of sensors that can be introduced in SLEs
and related parameters and measurement range
Sensor type
Physiological sensors
Sensor
Blood pressure meter
Body weight scale
Oximeter
PIR
Light sensors
Door sensors
Thermal-hygrometer
Environmental sensors
Surface temperature sensor
Measured parameter
Blood pressure
Body weight
Oxygen saturation
Person presence
Light on/off
Door opening/closing
Air temperature
Air relative humidity
Floor temperature
Roof temperature
Wall temperature
Black globe radiant temperature Mean Radiant temperature
Air Velocity
Hot wire anemometer
CO2
sensor
Luxmeter
Comfort sensors
Smart fridge
Wearable devices
Smartwatch
CO2
concentration
Illuminance
Predicted Mean Vote
Fridge opening/closing
Heart Rate (HR)
Steps
Walked distance
Energy expenditure
influencing well-being and conversely those playing only a
marginal role, to realize a robust system that is able to provide
significant outputs. For example, housing quality surely influences
well-being, as well as social interactions and performed
activities [17]. Therefore, it is fundamental to monitor and try
to improve these aspects, as well as vital signs undoubtedly influencing
physiological well-being. Behavioral patterns can be
taken into account to classify the activities performed by the
dwellers, identifying any abnormalities in time to promptly
act (e.g., by means of a simple advice about activities to perform,
or by contacting the healthcare provider in case of a
health emergency). In this field, coaching is gaining more and
more interest to foster a healthy and autonomous lifestyle in
ageing people, setting progressive daily goals and providing
appropriate feedback [18].
It is fundamental to consider the accuracy of the obtained
indices, starting from the sensor uncertainty and its propagation
in the measurement chain, and involving also the
processing strategies (e.g., AI algorithms or features extraction
techniques [19]) adopted for the computation of the indices if
interest [20]. The required accuracy will surely depend on the
final application of the computed parameters [21]; for example,
it is unquestionable that higher accuracy is necessary to
take a medical decision than to give advice about a leisure activity
to improve the mental well-being.
62
Required accuracy
(f.s. stands for full scale)
< ±5% (f.s.)
< ±1% (f.s.)
<±1% (f.s.)
ON-OFF sensor
ON-OFF sensor
ON-OFF sensor
< ±0.1 °C
< ±5%
< ±0.15 °C
< ±0.15 °C
< ±0.15 °C
< ±0.15 °C
< ±0.05 m/s
< ±50 ppm
< ±5 %
±0.1
ON-OFF sensor
< ±10% (f.s.)
< ±5% (f.s.)
< ±5% (f.s.)
< ±10% (f.s.)
Starting from the mentioned well-being-related indices,
it is possible to foresee different services being provided to
the users, with the support of distinct actors (e.g., an informal
caregiver, a healthcare provider, or an emergency service),
depending on the topic of the alert and on the severity of the
alarm generated. Indeed, a SLE should give the dwellers the
possibility to keep in contact not only with informal caregivers
or a general practitioner, but also with different types of
healthcare providers, including medical specialists, for example,
a psychologist when a support of this type is necessary
(e.g., social isolation during a pandemic emergency).
The authors of this paper are involved in several national/
international projects in the field of ATs and Ambient Assisted
Living (AAL) where AI approaches are used (Table 3); since the
developed models and algorithms can appear vague, it is also
important to use explainable AI (XAI) models [22] that support
the decisions deriving from AI, thus increasing trust and usability
in medical and coaching fields.
Within the frame of the Health@Home project, AI algorithms
have been applied to measure the well-being
(considered as user's health and mental status based on personal
feelings/perceptions and daily physical activities
during their normal routine) in the case of multi-resident
housing, to try to discriminate among multiple dwellers [23].
The participants were asked to complete a daily survey based
IEEE Instrumentation & Measurement Magazine
September 2021

Instrumentation & Measurement Magazine 24-6

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