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\section{Background}

Early warning scores (EWS) have been widely adopted internationally to identify deteriorating patients\cite{downey_strengths_2017}.
A large body of scientific evidence validates the effectiveness of EWS in assessing severity of illness, and in predicting adverse clinical events,
such as severe deterioration, likelihood of ICU admission, and mortality, both on hospital wards\cite{subbe_validation_2001, buist_association_2004, paterson_prediction_2006, alam_exploring_2015, bilben_national_2016, brekke_value_2019}
and in ambulatory care \cite{ehara_effectiveness_2019, burgos-esteban_effectiveness_2022, paganelli_conceptual_2022}.

Two common implemetations are the \textit{National Early Warning Score 2} (NEWS2) and the
\textit{Modified Early Warning Score} (MEWS)\cite{burgos-esteban_effectiveness_2022}.
Both are calculated by capturing various vital parameters from the patient at a specific point in time, followed by numerical aggregation of the
captured data according to the specifically used score.
Traditionally, doctors and nursing staff perform collection and evaluation of the data manually, inputting data into an EWS-calculator by hand.
Frequency of scoring, miscalculations and practical integration are known setbacks of NEWS2 and other scores\cite{eisenkraft_developing_2023}.
% which is limited due to lack of resources\cite{shaik_remote_2023}.

Remote patient monitoring (RPM) can improve detection of deterioration\cite{shaik_remote_2023} by greatly reducing the
amount of human interaction required to take measurements and perform EWS calculations.
A number of studies have explored RPM combined with automated EWS calculation in hospitals\cite{filho_iot-based_2021, un_observational_2021, karvounis_hospital_2021, eisenkraft_developing_2023}.
With hospitals facing critical patient demand during the SARS-CoV-2 pandemic, interest in exploring remote patient monitoring options surged,
and NEWS2 emerged as an effective tool for predicting severe infection outcomes\cite{gidari_predictive_2020, otoom_iot-based_2020, filho_iot-based_2021, carr_evaluation_2021},
while reducing person-to-person contact during patient monitoring.
%Javanbakht et al. found that continuous vitals monitoring is more cost-effective than intermittent monitoring\cite{javanbakht_cost_2020}, however the findings of
%this study should be taken lightly due to potential bias reporting.
Since then, a variety of wearable medical sensors capable of continuously recording vital parameters have been developed and are
commercially available\cite{noauthor_visi_nodate, noauthor_equivital_nodate, noauthor_vitls_nodate, noauthor_caretaker_nodate, noauthor_medtronic_nodate}.

\section{Motivation}

While the application of EWS in ambulant care facilities and hospitals has been thoroughly investigated, very little research has been done to
assess their practicability for remote monitoring of at-risk patients at home.
Some studies have examined monitoring individual vital signs for abnormalities using wearables for at-home-patients in a laboratory setting,
however in most of them, no automated EWS calculations were made\cite{archip_iot_2016, azimi_medical_2016, chowdary_efficient_2018, yeri_iot_2020, lee_all-day_2020, athira_design_2020, phaltankar_curaband_2021, thippeswamy_prototype_2021}.
Anzanpour et al. developed a monitoring system which collects vitals data and calculates EWSs in 2015, however due to limited or nonexistent
availability of remotely operable sensors for all vital signs relevant to EWSs, the work was limited to using a laboratory prototype
requiring some manual interaction in transferring vitals data\cite{anzanpour_internet_2015}.
Sahu et al. documented their development of an EWS-supported digital early warning system using the PM6750\cite{sahu_internet--things-enabled_2022},
an experimental vitals data monitoring device capable of taking continuous measurements in a laboratory setting\cite{noauthor_pm6750_nodate}.
However, the methodology of real-time EWS calculation using data gathered in the laboratory is inconsistent and was not demonstrated.

Patients appreciate the face-to-face aspect of early warning score monitoring as it allows for reassurance, social interaction, and gives them further opportunity to ask questions about their medical care\cite{downey_patient_2018}.

Taking continuous measurements is superior to measuring intermittently\cite{gronbaek_continuous_2023, shaik_remote_2023}, but
setting up continuous monitoring systems is cumbersome as it involves connecting patients to sensor devices
with numerous electrodes and cables, which restrict patient activities to the bed area\cite{un_observational_2021}.
Also, data transmission is highly reliant on in-house telecommunication infrastructure.
In contrast, wearable devices such as armband or wristband incorporates multiple biosensors in a single form-factor,
which allows a higher degree of patient mobility without the constraints of physical wirings.
More importantly, data transmission through cellular network avoids the need of installing additional in-house
telecommunication infrastructure, allows rapid deployment, and provides versatile and scalable solutions.


\section{Objectives}


\section{Tasks}

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