This research project was finished.
Digital Patient - Response Model & Pain Detection
When patients go under dental and/or otolaryngological treatments and surgical procedures, they tend to be nervous and uneasy. One of the reasons is that patients are aware of vibrations, noise, and pain that can not be suppressed by anesthesia. In this research, with the cooperation of patients who are undergoing actual surgery...
- we quantify surgical operations and patients' reactions, analyze the cause and effect of their relationship and model the interactions, and...
- then model a cardiorespiratory response model for patient's pain and stress detection.
Cardiorespiratory Response Model for Pain and Stress Detection during Endoscopic Sinus Surgery under Local Anesthesia
- The effect of surgical procedure on respiratory movement and the effect of characteristics of respiratory movement on changes in heart rate and blood pressure during actual endoscopic nasal surgery were analyzed using analysis of variance and Bayesian network modeling.
- As the result, the probabilistic causal relationship between respiratory irregularities, increasing blood pressure and patient's complaint of pain was found.
- Indices representing the characteristic shapes on the respiratory waveform showed the ability to predict direction of changes in blood pressure, and its coincident rate was over 80%.
- This result is expected to be used as patient pain and stress detection method without discomfort during actual surgery under local anesthesia.
Surgical Procedure - Response Model for Surgical Training
At the National Institute of Advanced Industrial Science and Technology (AIST), the Institute for Human Science and Biomedical Engineering (HSBE) has been the center for developing a procedural training model for endoscopic surgeries. By using this model, the training for operational techniques of surgical tools, such as endoscopes and forceps, became possible.
Digital Human Research Center is studying the modeling of various interactions between surgeons and patients during surgery.
- The reproducible model of patients' reactions to surgical
reproduces vital patients' reactions, such as pain occurrence and fluctuation of blood pressure, to surgical operations, including removal of polyps and mucous membrane, destruction of bony walls, and aspiration.
- Action-Response pattern model of how experienced surgeons respond
to patients' reactions:
timing of when to take preventive measures (supplemental anesthesia) for pain, and the action-response pattern model for actions taken after pain occurs (length of rest, etc.).
By reproducing the possible patients' reactions that occur during surgery, we are developing a skill acquisition system that carries surgical procedures forward while keeping a the patient at ease.
Endoscopic Sinus Surgery
- In this research, we are focusing on endoscopic sinus surgeries performed under local anesthesia. In this type of surgery, nasal polyps, abnormal mucous and extraneous bony walls are removed using surgical tools such as endoscopes and forceps (Figure 1). This procedure is intended to clear nasal blockages.
- This surgery is performed under local anesthesia. Inside nasal cavity and sinuses, polyps and bony walls are obstructing the passage that is connected deep inside a cylindrical, bamboo-like structure with nodes. The surgery starts with the removal of polyps and bony walls. Repeated, supplemental anesthesia will then be administered to the newly opened areas as the surgical phases proceed (Figure 2).
- The surgeon will administer supplemental anesthesia in a timely manner by checking the progress of the surgery and the patient's condition. Also, the resting time given when supplemental anesthesia is administered is adjusted accordingly. For example, less time when the patient is stabilized, more time when the patient is in pain.
Findings of Study
The Measurement of Progress of Surgical Procedure and Patients'
An endoscopic video, an operating room video, and a bio monitor are used to measure the progress of a surgical procedure. As a record of progress in surgical procedures, types of operations, positions, tools and quantity of operations, conversation between surgeon, patient, and nurses (complaint of pains and instruction for administering supplemental anesthesia, etc.) are logged. As an index of a patient's mental stress, heart rate, blood pressure level, perspiration caused by mental anxiety, and breathing movements is recorded.
Results of Analysis:
At this time, we have conducted analysis based on the measurement data of 6 patients.
Figure 3 shows that when pain did not exist, patients' reactions varied depending on the type of operation. More specifically, when a forceps was inserted into the nasal cavities and the opening procedure started, patients were on guard. Consequently, their breathing was repressed, causing a decrease in heart rate. As the surgeon proceeded to aspiration and packing, breathing movements and heart rate were both found to increase.
On the other hand, when pain occurred (Figure 4), heart rate increased during the opening process. Also, as for frequency of pain occurrence based on regions, the sensation of pressure and pain occurred more both at the inside of middle nasal concha (MT-IS) and around the superior nasal concha (SRT) - perhaps since the surgical tools had difficulty reaching inside. Frequency of pain occurrence was highest at the maxillary sinus (MS) as it is located in proximity to the dental nerve. At ethmoidal sinuses (ES), the occurrence of pain was seen particularly while operating in the lower areas.
Modeling: Reproducible Model of Patients' Responses
Based on the results of the analysis, we constructed a reproducible model of patients' reactions toward surgical operations (Figure 6).
This model was developed using a probabilistic model, Bayesian network, and BayoNet, the Bayesian network construction system (developed by AIST; distributed by Mathematical System, Inc.).
We are also making a prototype of a patient simulator that works together with aforementioned model for surgical training (Figure 7).