Validation of smartphone-derived metrics for prolonged unobtrusive monitoring of rest-activity patterns, fatigue and
sleepiness in sleep-disordered patients.

Background of the study:
Disturbances in the circadian rhythm and sleep have a severe effect on overall health and everyday functioning. This is particularly
observed in patients suffering from various sleep disorders which can cause excessive fatigue, sleepiness and a lack of attention
during the wake state. Unfortunately, there are very limited objective measures for these important complaints. As smartphones are
intensively used, smartphone-derived data, like keystroke logging and sensor data, offers the possibility to unobtrusively and
objectively measure patient’s rest-activity patterns and fatigue-related complaints during the wake phase. This innovative tool could
then be used for prolonged monitoring of these aspects, for example for treatment follow up.

Objective of the study:
To evaluate the use, reliability and validity of smartphone output data obtained with the Neurokeys App, for the detection and
monitoring of rest-activity patterns, fatigue and sleepiness in patients with various sleep disorders including such as insomnia.

Study design:
The study is an observational study that will take place in the tertiary sleep centre of Kempenhaeghe. Patients are referred for
diagnosis and treatment of possible sleep disorders and during the study will receive care as usual. Participants are asked to use the
Neurokeys App during their clinical follow up for six months and 2 weeks, and fill in 2-week sleep diary and questionnaires at several
time points

Study population:
Cohort of 200 patients with various sleep and circadian rhythm disorders, a minimum age of 18 years old and with daily smartphone
usage.

Primary study parameters/outcome of the study:
The rest-activity patterns (based on timing of the rest and active period), assessed with self-reports and objectively with last
smartphone-based keyboard interaction before and the first keyboard interaction after the longest time interval without keyboard
interaction (i.e., keystroke-absence period) during the subjective night;

Secundary study parameters/outcome of the study (if applicable):
Fatigue and sleepiness, assessed with self-reports and objectively with keystroke dynamics features derived from patients’ keyboard
use on smartphones.

Smartphone derived metrics can be used to monitor rest-activity paterns,fatigue and
sleepiness in sleep-disordered patients.

Participants are asked to use the Neurokeys App during their clinical follow-up for six months and 2 weeks, and fill in 2-week sleep diary and questionnaires at three time points; after intake, after 3 months and after 6 months.