Masako Kanai-Pak

Design and evaluation of robot patient for nursing skill training in patient transfer

We developed a robot patient for patient transfer training for simulating a patient’s performance during patient transfer and for enabling nurses to practice their nursing skills on it. To realize the robot patient, we focused on addressing the problems of designing its limb actions to enable it to respond to nurses’ operations. RC servos and electromagnetic brakes were installed in the joints to enable the robot to simulate a patient’s limb actions, such as embracing and remaining standing. To enable the robot to automatically respond to nurses’ operations, an identification method for these operations was developed that used voice commands and the features of the limbs’ posture measured by angle sensors installed in the robot’s joints. The robot patient’s performance was examined by a control test in which four experienced nursing teachers performed patient transfer with the robot patient and a human-simulated patient. The results revealed that the robot patient could successfully simulate the actions of a patient’s limbs according to the nursing teachers’ operations and that it is suitable for nursing skill training.

A measurement and evaluation method of a support system to teach how to improve transferring patients

This is an examination of a teacher support system used for measuring and evaluating nursing students involved in the transfer of patients. Evaluation of nursing student is very complex task but we propose the Method using some simple values which can be automatically extracted from motion data. In this study, we present the following: 1. Guidelines for the evaluation of motion 2. Simple measurement system for evaluation. 3. Relation between evaluated values by the system and teachers estimation. 4. Motion of students become close to that of teacher after teaching.

Robot Patient for Nursing Self-training in Transferring Patient from Bed to Wheel Chair

In this paper, we proposed a robot patient for the nursing training in patient transfer. The robot patient was developed to reproduce the performance of the patients who are suffering from mobility problems. We targeted on the reproduction of movement of the patient’s limbs (arms and legs) with the consideration of physical and voice interaction between the patient and nurse. The robot patient had 15 joints including 2 active joints installed with motors, 4 passive joints installed with electric brakes and 9 passive joints without any actuators. To realize the physical interaction, potentiometer type angle sensors was utilized to detect the rotation angle of the joints of shoulders, elbows and knees. In addition, follow-up control approach was applied to the shoulder joint. By this way the robot could react accordingly when the trainees moved its limbs. A voice recognition module was applied to enable the robot to interact with the trainee by voice. An experiment was performed by a nursing teacher for examine the robot’s performance. The robot patient successfully reproduced the patient’s movement with physical and voice interaction, including embracing, keeping embracing, standing up, keeping standing and sitting down.

Recognition of nursing activity with accelerometers and RFID

Purpose – This paper aims to construct a recognition system of nursing activities. Design/methodology/approach – The authors used accelerometers and radio frequency identification (RFID) tags to ensure patient privacy in practical nursing care environments. The accelerometers were attached to the body of the nurse, and the RFID was attached to apparatuses and objects. In addition, a pattern classification algorithm using a support vector machine and filtering methodology were applied. Findings – The accuracy using accelerometers and RFID was 73 percent. When the filtering algorithm was applied, the results were 79 percent. The results showed that activities with short execution times or those that resembled others in posture had low recognition accuracy. Research limitations/implications – Activities requiring only a short period of time tend to be misrecognized. Practical implications – It is possible to construct a training system for nursing activities with the system that recognizes the sequence of nu...

Robot Patient Design to Simulate Various Patients for Transfer Training

To improve the patient transfer skill of nursing education students, we developed a robot patient that can simulate three categories of patients: 1) patients whose movements are affected by paralysis; 2) patients whose movements are sensitive to pain with painful expression; and 3) patients whose movements are constrained by medical devices. By practicing with the robot patient, nursing students can learn the skills required for interacting with various patients. To simulate trunk movements of these different patients, novel waist and hip joints with hardware-inherent compliance and force-sensing capability were proposed. In addition, control methods were developed and the parameters were tuned based on actual patient videos. To evaluate the developed robot, nursing teachers performed trials of transferring the robot patient as they would transfer an actual patient. The nursing teachers scored the robot patients based on a checklist. Moreover, subjective evaluations of a questionnaire were performed by the nursing teachers. The results showed that the nursing teachers performed most of the required skills of the checklist and agreed regarding the learning effectiveness of the robot. They recommended training nursing students using the robot patient in the questionnaire. Finally, hugging speed comparison showed that the nurses slow down the speed when dealing with a robot patient with painful expression.

Impact of Using a Robot Patient for Nursing Skill Training in Patient Transfer

In the past few decades, simulation training has been used to help nurses improve their patient-transfer skills. However, the effectiveness of such training remains limited because it lacks effective ways of simulating patients’ actions realistically. It is difficult for nurses to use the skills learned from simulation training to transfer an actual patient. Therefore, we developed a robot patient that could simulate the behavior of patients’ limbs for patient-transfer training. This study examined the performance of the robot used in training and evaluated its training effectiveness. Four nursing teachers individually transferred the robot patient and then scored the robot patients ability to simulate patients’ actions and its suitability for skill training. An experiment using pre-post control group design was carried out to examine the robot patients training effectiveness compared with the human simulated patient. The participants were 20 nursing students and one nursing teacher who was responsible for scoring the students’ skills in the pre-test and post-test. All of the students were assigned to train with either the proposed robot patient or a healthy person simulating the patient. The results show that all four nursing teachers regarded the robot patients actions as realistic. In addition, all four teachers agreed that the robot patient was suitable for skill training. The results also show that the proposed robot patient is more challenging than the current method, which employs a healthy person to simulate the patient. Significant skill improvement (p < 0.01) was observed in the experimental group when transferring the robot patient.

Robot Patient Imitating Paralysis Patients for Nursing Students to Learn Patient Transfer Skill

This research aims to develop a robot to help nursing students learn how to physically transfer paralyzed patients. Our prior robotic prototype had only been designed to imitate a patient with weak lower limbs; it was unable to imitate the imbalance and instability of the trunk. Therefore, we developed and waist joint on the prototype robot and also the control system in order to emulate quadriplegic and hemiplegic patients’ tendency to fall over. The waist was designed with 2 DOF compliant joints. Evaluation of the robot showed that the robot was able to properly imitate the unstable waist movements of paralyzed patients.

Mannequin system for the self-training of nurses in the changing of clothes

Purpose – For self-training of nursing students, this paper developed a mannequin to simulate and measure the movement of a patient’s arms while nurses changed the patient’s clothes on a bed. In addition, using the mannequin the purpose of this paper is to determine the difference in the handling of a patient’s arms between nursing teachers and students. Design/methodology/approach – The target patient was an old man with complete paralysis. Three-degrees-of-freedom (DOF) shoulder joints and one-DOF elbow joints were applied to the mannequin. The angles of all joints were measured using a potentiometer, and those angles were transmitted to a computer via Bluetooth. Findings – In a preliminary experiment, the two nursing teachers confirmed that the mannequin arms simulated the motion of the arms of a paralyzed patient. In the experiment, two teachers and six students changed the clothes of the mannequin. The average joint angle of the left elbow and the moving frequency of the left elbow, right shoulder ad...

Robotics as a Tool in Fundamental Nursing Education

The main purpose of this study was to investigate whether the use of robotics can contribute to nursing education, using the training for wheelchair transfers. The most common and extensively used method for practical learning is role playing. However the nursing student cannot turn into a patient thoroughly. To solve this problem, we proposed the creation of a robot patient for wheelchair transfer techniques training.

Supporting system for self training of bed-making using image processing with color and distance information

The purpose of this paper was to develop a support system to help nursing trainees learn the skill of bed-making. The system consisted of three steps: measurement, evaluation, and feedback. This paper focused on the first two issues. First, the evaluation points of bed-making were determined. Next, a measurement system was constructed using color and distance information provided by Kinects and image processing. The system extracted specific segments of whole images depicting trainees, a bed, and necessary equipment. Finally, the procedure used by trainees in making beds was quantitatively evaluated using thresholds that were determined in advance by observing teachers and students involved in bed-making. Compared to the evaluation of nursing teachers, the accuracy of the evaluation system was as much as 70%.