Automatic matching of surgeries to predict surgeons' next actions

OBJECTIVE

More than half a million surgeries are performed every day worldwide, which makes surgery one of the most important component of global health care. In this context, the objective of this paper is to introduce a new method for the prediction of the possible next task that a surgeon is going to perform during surgery.

MATERIAL AND METHOD

We formulate the problem as finding the optimal registration of a partial sequence to a complete reference sequence of surgical activities. We propose an efficient algorithm to find the optimal partial alignment and a prediction system using maximum a posteriori probability estimation and filtering. We also introduce a weighting scheme allowing to improve the predictions by taking into account the relative similarity between the current surgery and a set of pre-recorded surgeries.

RESULTS

Our method is evaluated on two types of neurosurgical procedures: lumbar disc herniation removal and anterior cervical discectomy. Results show that our method outperformed the state of the art by predicting the next task that the surgeon will perform with 95% accuracy.

CONCLUSIONS

This work shows that, even from the low-level description of surgeries and without other sources of information, it is often possible to predict the next surgical task when the conditions are consistent with the previously recorded surgeries. We also showed that our method is able to assess when there is actually a large divergence between the predictions and decide that it is not reasonable to make a prediction.

Humanoid assessing rehabilitative exercises

INTRODUCTION

This article is part of the Focus Theme of Methods of Information in Medicine on "New Methodologies for Patients Rehabilitation".

BACKGROUND

The article presents the approach in which the rehabilitative exercise prepared by healthcare professional is encoded as formal knowledge and used by humanoid robot to assist patients without involving other care actors.

OBJECTIVES

The main objective is the use of humanoids in rehabilitative care. An example is pulmonary rehabilitation in COPD patients. Another goal is the automated judgment functionality to determine how the rehabilitation exercise matches the pre-programmed correct sequence.

METHODS

We use the Aldebaran Robotics' NAO humanoid to set up artificial cognitive application. Pre-programmed NAO induces elderly patient to undertake humanoid-driven rehabilitation exercise, but needs to evaluate the human actions against the correct template. Patient is observed using NAO's eyes. We use the Microsoft Kinect SDK to extract motion path from the humanoid's recorded video. We compare human- and humanoid-operated process sequences by using the Dynamic Time Warping (DTW) and test the prototype.

RESULTS

This artificial cognitive software showcases the use of DTW algorithm to enable humanoids to judge in near real-time about the correctness of rehabilitative exercises performed by patients following the robot's indications.

CONCLUSION

One could enable better sustainable rehabilitative care services in remote residential settings by combining intelligent applications piloting humanoids with the DTW pattern matching algorithm applied at run time to compare humanoid- and human-operated process sequences. In turn, it will lower the need of human care.

Outcome quality assessment by surgical process compliance measures in laparoscopic surgery

OBJECTIVE

The effective and efficient assessment, management, and evolution of surgical processes are intrinsic to excellent patient care. Hence, in addition to economic interests, the quality of the outcome is of great importance. Process benchmarking examines the compliance of an intraoperative surgical process to another process that is considered as best practice. The objective of this work is to assess the relationship between the course and the outcome of surgical processes of the study.

MATERIALS AND METHODS

By assessing 450 skill practices on rapid prototyping models in minimally invasive surgery training, we extracted descriptions of surgical processes and examined the hypothesis that a significant relationship exists between the course of a surgical process and the quality of its outcome.

RESULTS

The results showed a significant correlation with Person correlation coefficients >0.05 between the quality of process outcome and process compliance for simple and complex suturing tasks in the study.

CONCLUSIONS

We conclude that high process compliance supports good quality outcomes and, therefore, excellent patient care. We also showed that a deviation from best training processes led to a decreased outcome quality. This is relevant for identifying requirements for surgical processes, for generating feedback for the surgeon with regard to human factors and for inducing changes in the workflow in order to improve the outcome quality.