Posture study for self-training system of patient transfer

Huang, Zhifeng; Nagata, Ayanori; Kanai‐Pak, Masako; Maeda, Jukai; Kitajima, Yasuko; Nakamura, Mitsuhiro; Aida, Kyoko; Kuwahara, Noriaki; Ogata, Taiki; Ota, Jun

doi:10.1109/robio.2012.6491073

Cited by 5 publications

(7 citation statements)

References 18 publications

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“…This paper extends the studies of [21]- [23] by (a) including the evaluation of motions segmentation's accuracy for a more detailed assessment of the evaluation accuracy and (b) increasing the number of experimental subjects (10) to examine the evaluation accuracy of all evaluation items (20) of patient transfer.…”

Section: Introductionmentioning

confidence: 88%

Automatic Evaluation of Trainee Nurses' Patient Transfer Skills Using Multiple Kinect Sensors

Huang

Nagata

Kanai‐Pak

et al. 2014

IEICE Trans. Inf. & Syst.

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SUMMARYTo help student nurses learn to transfer patients from a bed to a wheelchair, this paper proposes a system for automatic skill evaluation in nurses' training for this task. Multiple Kinect sensors were employed, in conjunction with colored markers attached to the trainee's and patient's clothing and to the wheelchair, in order to measure both participants' postures as they interacted closely during the transfer and to assess the correctness of the trainee's movements and use of equipment. The measurement method involved identifying body joints, and features of the wheelchair, via the colors of the attached markers and calculating their 3D positions by combining color and depth data from two sensors. We first developed an automatic segmentation method to convert a continuous recording of the patient transfer process into discrete steps, by extracting from the raw sensor data the defining features of the movements of both participants during each stage of the transfer. Next, a checklist of 20 evaluation items was defined in order to evaluate the trainee nurses' skills in performing the patient transfer. The items were divided into two types, and two corresponding methods were proposed for classifying trainee performance as correct or incorrect. One method was based on whether the participants' relevant body parts were positioned in a predefined spatial range that was considered 'correct' in terms of safety and efficacy (e.g., feet placed appropriately for balance). The second method was based on quantitative indexes and thresholds for parameters describing the participants' postures and movements, as determined by a Bayesian minimum-error method. A prototype system was constructed and experiments were performed to assess the proposed approach. The evaluation of nurses' patient transfer skills was performed successfully and automatically. The automatic evaluation results were compared with evaluation by human teachers and achieved an accuracy exceeding 80%.

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Section: Introductionmentioning

confidence: 88%

Automatic Evaluation of Trainee Nurses' Patient Transfer Skills Using Multiple Kinect Sensors

Huang

Nagata

Kanai‐Pak

et al. 2014

IEICE Trans. Inf. & Syst.

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“…To indicate the accuracy of performance of the trainee against each evaluation item, we used our previously developed automatic skill evaluation method [41], [42]. As described in Section 2.1, the evaluation factors and corresponding motions for each item were different.…”

Section: Automatic Skill Evaluation Methods For Patient Transfermentioning

confidence: 99%

“…2 shows the hardware of the self-help skill training system prototype for patient transfer, which comprises a dual-Kinect sensor system, liquid crystal display, wireless mouse, and wireless keyboard. The dual-Kinect sensor system was designed to capture information on the posture of trainees and patients, and state of the wheelchair [41], [42]. The sensor system contains two Microsoft Kinect sensors, two personal computers (PCs), and a router.…”

Section: Hardware Of Self-help Skill Training Systemmentioning

confidence: 99%

“…After the system's hardware was set up, it was further calibrated to determine the exact position and posture of the bed on the floor. A set of points on a plane (e.g., the floor) (indicating the spatial position of the object being measured) was collected by the Kinect sensor, after which the least square method [42] was applied to calculate the parameters required for determining the plane.…”

Section: Hardware Of Self-help Skill Training Systemmentioning

confidence: 99%

“…The self-help skill training system consists of three parts: (1) a sensor system comprising Kinect sensors and color markers (which has been proposed in our previous studies) to measure and evaluate the performance of trainees [41], [42]; (2) a feedback method to help trainees check and correct their errors; and (3) an operation interface to enable trainees to operate the system by themselves.…”

Section: Introductionmentioning

confidence: 99%

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Self-Help Training System for Nursing Students to Learn Patient Transfer Skills

Huang

Nagata

Kanai‐Pak

et al. 2014

IEEE Trans. Learning Technol.

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This paper describes the construction and evaluation of a self-help skill training system for assisting student nurses in learning skills involving the transfer of patients from beds to wheelchairs. We have proposed a feedback method that is based on a checklist and video demonstrations. To help trainees efficiently check their performance and correct errors, the checklist was prepared with items specific to the performance of tasks related to individual body parts (e.g., the height of the waist). In this system, two Kinect RGB-D sensors were used for measuring the posture of the trainees and patients. An automatic skill evaluation method was used to designate the trainees' performance against each evaluation item as correct or incorrect. Furthermore, the system's operation interface was designed to enable self-operation by trainees. Control tests were performed to measure the training effectiveness of the system. The results of the tests on a control group (n ¼ 5) that used only a textbook and demonstration video but did not receive feedback were compared with those of the experimental group (n ¼ 5) that used the proposed system. The results of both subjective and objective evaluation demonstrated that the experimental group showed greater improvement in performing patient transfer than the control group ðp < 0:05Þ.

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