In hospital setting, calculation of EWSs has been shown to predict important clinical outcomes effectively, such as severe deterioration, likelyhood of ICU admission,
and mortality\autocite{subbe_validation_2001, buist_association_2004, paterson_prediction_2006, brekke_value_2019}.
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.
EWSs are also a viable tool for predicting deterioration outside of hospitals\cite{ehara_effectiveness_2019}, allowing for preemptive action to be taken.
Serveral IoT-based approaches have been proposed and implemented in an experimental setting\cite{sahu_vital_2022,sahu_cloud-based_2022,sahu_internet--things-enabled_2022}
Sahu et al. used the PM6750, an experimental vitals data monitoring device capable of continuous vitals data measurements, but requiring a large number of sensors and cables
being continuously attached to the patient and connected to a power outlet\cite{noauthor_pm6750_nodate}.
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}.
Setting up continuous monitoring systems used to be cumbersome as it involves connecting patients to sensor devices
with numerous electrodes and cables, which restrict patient activities to the bed area.
Also, data transmission were highly reliant on in-house telecommunication infrastructure.
In contrast, wearable device 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.
