Frequency based assessment of surgical activities

In hospitals the duration of surgeries plays a decisive role in many areas, such as patient safety or financial aspects. By utilizing accurate automated online prediction efficient surgical patient care and effective resource management can be attained. In this work several surgical activities during an intervention were examined for their potential to forecast the remaining intervention time. The method used was based on analysing in the frequency domain of time series which represented the status of surgical activities during an intervention. A nonparametric estimation of power spectral density was calculated for single surgical tasks during an intervention. The power spectral densities (PSD) of different surgical activities were compared in a leave-one-out cross validation of forty surgical workflow recordings of lumbar discectomies. The results showed that the activity irrigate with a mean prediction error of 26 min 23 s is best-suited for determining the remainder of the intervention. To construct a scheduling support for a wider range of surgery types the actions conducted by the surgeon’s right and left hand would eminently be more suitable; the error of the action right hand was 41 min 39 s, yet. In conclusion sophistication into the presented frequency based method might support time and resource management in a general manner