  A practical way of detecting sleep stages has become more necessary as we
begin to learn about the vast effects that sleep has on people's lives. The
current methods of sleep stage detection are expensive, invasive to a person's
sleep, and not practical in a modern home setting. While the method of
detecting sleep stages via the monitoring of brain activity, muscle activity,
and eye movement, through electroencephalogram in a lab setting, provide the
gold standard for detection, this paper aims to investigate a new method that
will allow a person to gain similar insight and results with no obtrusion to
their normal sleeping habits. Ballistocardiography (BCG) is a non-invasive
sensing technology that collects information by measuring the ballistic forces
generated by the heart. Using features extracted from BCG such as time of
usage, heart rate, respiration rate, relative stroke volume, and heart rate
variability, we propose to implement a sleep stage detection algorithm and
compare it against sleep stages extracted from a Fitbit Sense Smart Watch. The
accessibility, ease of use, and relatively-low cost of the BCG offers many
applications and advantages for using this device. By standardizing this
device, people will be able to benefit from the BCG in analyzing their own
sleep patterns and draw conclusions on their sleep efficiency. This work
demonstrates the feasibility of using BCG for an accurate and non-invasive
sleep monitoring method that can be set up in the comfort of a one's personal
sleep environment.
