Understanding and anxiety [15], and reduce quality of

Understanding the sleep quality of individuals after stroke is
critical because about 6.8 million Americans are living with chronic stroke 1, and up to 50% of those with chronic stroke report
sleep disturbances 2. Indeed, individuals
after stroke often suffer of sleep disturbances and changes in sleep patterns. Sleep-wake
disorders, including hypersomnia, excessive daytime sleepiness, fatigue and insomnia
are detected by up to 40% of individuals with chronic stroke (defined as more
than 6 months following stroke) and 70% of those with acute stroke 3. Sleep-related
movement disorders like restless leg syndrome and periodic limb movements, are
also common in post-stroke patients 4. After stoke the sleep
disturbances suffered by individuals can bring to short-term and long-term
negative patient outcomes 5 and increase the risk
of a recurrent stroke 6. Depression, medication
use, pain, sleep-disordered breathing, impaired mobility, and other
complications are factors that contribute to compromised sleep in post-stroke patients
7. Insomnia is the most
common sleep disorder with up to 22% of middle-aged and older Americans that suffer
of chronic stroke 8. Insomnia is
characterized by a complaint of difficulty staying asleep, falling asleep, non-restorative
sleep, early morning awakening 9. The diagnosis of
insomnia requires at least one associated daytime functional impairment (fatigue,
daytime sleepiness, irritability, memory, or concentration difficulties among
other complaints) 9. Moreover, sleep
disturbances and disorders in individuals with stroke can bring to an
additional stroke and may impact the ability to learn new motor skills 10.

Sleep issues also negatively impact functional outcomes and overall quality of
life in individuals with stroke 11.

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Furthermore, there is evidence that poor sleep quality and sleep disruptions
compromise the immune system 12,
alter the tissue healing process 13,
increase pain sensitivity 14,
contribute to depression and anxiety 15,
and reduce quality of life and functional well-being 16.

Since all of these pathological conditions are commonly endured
by people during the post-stroke period, monitoring the sleep quality is
essential in post-stroke patients. Under this context a research question is: What kind of parameters are essential to
evaluate, after the initial  acute phase
of stroke, in order to infer the patients health state?

The total sleep time considerably in 48% of the patients
during the acute phase of stroke. The daytime sleep significantly increase as
well as the number of awake. These characteristics are then correlated with reduced
quality of life and poor sleep quality 18. Several studies exploit
polysomnography (PSG) to examine sleep quality in patients with stroke 17
19 20. Decreased sleep efficiency (SE), reduced total sleep time (TST), and
increases in sleep latency are the main alteration noticed in patients with
stroke. Measuring the aforementioned parameters with the PSG technique is a
complicated task. Indeed, in general these studies were conducted on a single
night 21, while two nights of PSG recording is recommended since the first
night is referred to as the “adaptation” or “acclimation” night and is neglected
from the analysis and is considered not representative of the usual sleeping
patterns 22. Moreover, the PSG technique is costly and intrusive, which may
disturb sleep. Consequently, polysomnography is not suitable an uninterrupted sleep
quality analysis. Moreover, in 23 the authors show that evaluation of the
quality of sleep in hospital positively influenced patient outcomes at
discharge by 2.5-fold. This means that a day-by-day sleep quality monitoring at
home could help the doctors
to control the health state of the post-stroke patients after the discharge.

In this context, a system able to continuously monitoring the aforementioned
parameters in unobtrusive manner at home is useful and desirable. In recent
years, because of the development of ubiquitous technology in health care, the
research effort involving non-invasive sensors to assess and report sleep patterns
is actively progressing. A relevant source of information on sleeping is
represented by motion data coming from worn inertial sensors (i.e.,
accelerometers) embedded in smartphones or wristbands 24. Indeed, data coming from
worn devices has been thoroughly exploited in different scenarios aiming at monitoring human activities
25. The use of this kind
of information is the basis of the so-called actigraphy 26. In this paper we
want to use unobtrusive technology without taking into consideration wearable
solutions.

In 27, an unobtrusive system able to infer the
bed posture and the breathing signal is presented. The system is based on an
expensive technology which employs a sensor, called Kinotex, that was developed
by the Canadian Space Agency for tactile robotic sensing. Finally, in 28, an inexpensive system based on placing
above the mattress a capacity textile sensing technology is described. However,
the authors noticed problems on the reproducibility of the experiments, due to
the movement of the textile system, which necessitates a new calibration phase
each time.

To our knowledge, there are no studies about system able to assess
the sleep characteristics of individuals with chronic stroke merging the
inexpensive feature of 27 and the unobtrusive feature
of 28, placing under the
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