Abstract—Sit-to-stand (SiSt) analysis has been widely used in
clinical practice to assess the risk of falls in the older adult population.
This paper proposes automated algorithms for the unobtrusive
measurement of SiSt timing and symmetry using bed pressure
sensors. An integrated signal comprising all of the sensor outputs
was analyzed to measure both the bed-departure timing and the
timing of three clinical phases within the transfer. Data collected
in clinical trials, along with independent clinical video analysis,
verified the success of the bed-departure timing algorithm with a
mean error of 0.11 s. The phase measurement algorithm showed
significant differences (p < 0.001) between younger and older
adults in Phases II and III of the transfers, comparing well with
studies found in recent clinical literature. The sensor outputs were
then used to form sequences of pressure images, and an automated
region of interest (ROI) detection algorithm was designed
to extract regional signals from the hips and the hands. The final
algorithm was designed to measure the symmetry of the body
throughout the SiSt transfer from the extracted regional signals.
A system accuracy of 93.0% was obtained for the automated
symmetry classification of transfers. The techniques proposed in
this paper can increase the precision and efficiency in clinical SiSt
assessments. Their unobtrusive nature makes them particularly
suitable for integration into a continuous monitoring system such
as those required within the smart home environment.