  Effective visualizations were evaluated to reveal relevant health patterns
from multi-sensor real-time wearable devices that recorded vital signs from
patients admitted to hospital with COVID-19. Furthermore, specific challenges
associated with wearable health data visualizations, such as fluctuating data
quality resulting from compliance problems, time needed to charge the device
and technical problems are described. As a primary use case, we examined the
detection and communication of relevant health patterns visible in the vital
signs acquired by the technology. Customized heat maps and bar charts were used
to specifically highlight medically relevant patterns in vital signs. A survey
of two medical doctors, one clinical project manager and seven health data
science researchers was conducted to evaluate the visualization methods. From a
dataset of 84 hospitalized COVID-19 patients, we extracted one typical COVID-19
patient history and based on the visualizations showcased the health history of
two noteworthy patients. The visualizations were shown to be effective, simple
and intuitive in deducing the health status of patients. For clinical staff who
are time-constrained and responsible for numerous patients, such visualization
methods can be an effective tool to enable continuous acquisition and
monitoring of patients' health statuses even remotely.
