An Analysis on Serious Games and Stakeholders’ Needs for Vocal Training Game Development

Xiaopeng Yang(양샤오펑),Edwina Dwi Sadika(에드위나 사디카),Gradiyan Budi Pratama(그라디안 프라타),Younggeun Choi(최영근),Yu-Kyung Kim(김유경),Ji-Yun Lee(이지윤),Yunju Jo(조윤주),Giwook Kim(김기욱),Jin-Kook Lee(이진국),Min-Jung Yu(유민정),M 한국언어청각임상학회 2019 Communication Sciences and Disorders Vol.24 No.3

배경 및 목적: 본 연구는 발성훈련에 대한 언어치료 환자의 치료 동기와 참여를 향상시키기 위한 기능성 게임에 대한 요구사항과 개발방향을 파악하기 위해 수행되었다. 방법: 문헌조사, 이해당사자 요구조사, 기존 3가지 발성훈련 게임(Visi Pitch, Dr. Speech, Vox System)의 벤치마킹 분석이 수행되었다. 결과: 문헌조사를 통해 13가지 게임 사용자 경험 척도들(유용성, 서사성, 몰입, 즐거움, 창의성, 오디오 심미성, 개인적 충족감, 사회적 연결성, 시각적 심미성, 정확성, 개인 맞춤형 분석, 게임 분석, 치료 연속성)이 파악되었다. 사용자 경험 척도들 중 기존 언어치료게임에서 일반적으로 미흡한 속성들로는 창의성(평균 만족도=2.5-4.3; Likert 7점 척도 사용), 사회적 연결성(2.4-4.4), 치료 연속성(1.7-4.7), 그리고 개인 맞춤형(2.5-5.0)이 파악되었다. 논의 및 결론: 본 연구의 사용자 경험 척도들은 발성훈련 기능성 게임을 평가하는 데 유용하게 활용될 수 있으며, 기존의 게임들이 상대적으로 미흡한 사용성 경험 척도를 보완하는 새로운 기능성 게임 개발이 필요하다. Objectives: The present study intended to identify the needs and development directions of a serious vocal training game for better motivation and commitment of patients with voice disorder to voice therapy. Methods: A literature review, a survey of stakeholders’ needs, and a benchmarking analysis of three vocal training games (Visi Pitch, Dr. Speech, and Vox System) was conducted. Results: From the literature review, thirteen game user experience scales (usability, narratives, play engrossment, enjoyment, creative freedom, audio aesthetics, personal gratification, social connectivity, visual aesthetics, accuracy, customization, game analytics, and therapy continuity) were identified for vocal training games and then applied to evaluation of the existing games. From the user experience scales, features not commonly implemented in the existing games include creative freedom (average satisfaction score, 2.5 to 4.3 out of 7), social connectivity (2.4 to 4.4), therapy continuity (1.7 to 4.7), and customization (2.5 to 5.0). Conclusion: The user experience scales would be of use to assess vocal training games, and new serious games need to be developed to complement the existing games in terms of the four scales found relatively lacking.

A User-Centered Virtual Liver Surgery Planning System

Xiaopeng Yang,Wonsup Lee,Younggeun Choi,Heecheon You,Ji Hyun Kim,Hee Chul Yu,Baik Hwan Cho 대한인간공학회 2012 대한인간공학회 학술대회논문집 Vol.2012 No.11

The present study is intended to develop a user-centered virtual liver surgery planning system called Dr. Liver which has clinical applicability and effectiveness to support liver surgery. Existing virtual surgery systems needs to be customized to liver surgery and improved for better usability and time efficiency. A use scenario of a virtual liver surgery planning system was established through literature review, benchmarking, and interviews with surgeons. Based on the use scenario, detailed liver surgery planning procedures were defined. The major functions of Dr. Liver include (1) extraction of the liver, vessels, and tumors from abdominal CT images, (2) estimation of the standard liver volume of a patient, (3) volumetry of the extracted liver, vessels, and tumors, (4) segmentation of the liver into 8 segments based on structures of the extracted portal and hepatic veins, and (5) support of surgery planning. Novel algorithms were developed and implemented into Dr. Liver for accuracy and time efficiency. Various user-friendly features such as a procedural interface of virtual liver surgery planning were integrated into Dr. Liver for better usability. Dr. Liver would be applied to safe and rational planning of liver surgery.

Development of a User-Centered Virtual Liver Surgery System

Xiaopeng Yang,Wonsup Lee,Younggeun Choi,Heecheon You,Ji Hyun Kim,Hee Chul Yu,Baik Hwan Cho 대한인간공학회 2011 대한인간공학회 학술대회논문집 Vol.2011 No.5

Objective: The present study is to develop a user-centered virtual surgery system called Dr. Liver which has clinical applicability and effectiveness to support liver surgery. Materials and methods: The major functions of Dr. Liver include (1) extraction of the liver, vessels, and tumors from abdominal CT images, (2) estimation of the standard liver volume of a patient, (3) volumetry of the extracted liver, vessels, and tumors, (4) segmentation of the liver based on the portal vein structure, and (5) support of surgery planning. A novel semi-automatic liver extraction algorithm was developed and implemented to Dr. Liver for time efficiency and accuracy of extraction. Dr. Liver was evaluated using MDCT data of three patients and compared to the OsriX system in terms of time and accuracy. Results: Dr. Liver was found significantly better than the OsriX system by showing an average (SD) time of liver extraction = 4.4 (2.4) min and an average difference between the volume of a manually extracted liver and that of the corresponding semi-automatically extracted liver = 4.2 (8.9) ml. Furthermore, various user-friendly features such as a procedural interface of virtual surgery planning were implemented into Dr. Liver for usability. Conclusions: It is concluded that Dr. Liver is a clinically effective tool to support liver surgery planning. More sophisticated features and functions are being developed and implemented to Dr. Liver to provide a surgeon with effective information for rational planning of liver surgery.

A Usability Test for Dr. Liver, a 3D Virtual Liver Surgical Planning System

Xiaopeng Yang,Younggeun Choi,Wonsup Lee,Baojian Wang,Jaedo Yang,Hongpil Hwang,Ji Hyun Kim,Jisoo Song,Hee Chul Yu,Baik Hwan Cho,Heecheon You 대한인간공학회 2013 대한인간공학회 학술대회논문집 Vol.2013 No.5

A usability test was performed for a 3D virtual liver surgical planning system, named Dr. Liver. The system consists of five modules including (1) (1) Liver Extraction, (2) Vessel Extraction, (3) Tumor Extraction, (4) Liver Segmentation, and (5) Liver Surgery Planning. Various performance and preference measures were applied and opinions of the participants regarding likes, dislikes, and suggestions were collected. Three medical doctors participated in the usability test, consisting of five test modules. The system received a high score of satisfaction (mean = 6.5, S.D. = 0.8) as measured using a 7-point Likert scale throughout the five test modules. Based on the evaluation results, recommendations were made for better usability of the system. The present study would help practitioners to evaluate the usability of a system and identify potential usability problems in a systematic manner.

Automatic Segmentation of Liver and Vessels from CT Images for Liver Surgery Planning

( Xiaopeng Yang ),( Younggeun Choi ),( Jae Do Yang ),( Hong Pil Hwang ),( Sung Woo Ahn ),( Ji Hyun Kim ),( Hee Cheon You ),( Hee Chul Yu ) 대한간학회 2017 춘·추계 학술대회 (KASL) Vol.2017 No.1

Aims: To present a method for automatic segmentation of liver and its vessels from computer tomography (CT) images for liver surgery planning. Methods: The proposed method consists of three steps: Firstly, the liver is automatically segmented based on histogram analysis and its geometric characteristics by a method which incorporates a fast-marching level-set method and a threshold-based level-set method, in which optimal values of parameters are determined by an exhaustive experiment. Secondly, liver vessels including PV and HV are automatically segmented by a region growing method based on histogram analysis of the image region inside the liver. PV and HV are then separated by a connected component analysis method. Lastly, the liver is divided into 8 segments according to the Couinaud classification by a nearest neighbor approximation method. Results: Experiments were conducted using a public liver database consisting of 20 training and 10 test datasets from the SLIVER07 competition. Optimal parameter values for segmentation were determined by an exhaustive experiment using the 20 training datasets, while performance of the segmentation method was evaluated by using the 10 test datasets. The proposed liver segmentation method was ranked as the 6th best segmentation method out of 104 submissions (2016). For liver vessel segmentation, no false positive errors were found for all datasets. False negative errors were identified at distal vessel branches due to small diameter and low contrast. The average (± S.D.) score of suitability of the segmented liver vessels for liver surgery planning assessed by an expert radiologist was 6.4 (± 0.7) out of 7. Conclusions: The proposed method achieved high performance in liver segmentation by quantitative onsite evaluation and satisfactory performance in liver vessel segmentation assessed by an expert radiologist. The proposed method can be applied to liver surgery planning.

Needs Analysis of Serious Games for Vocal Training in Speech Therapy

Xiaopeng Yang,Younggeun Choi,Hayoung Jung,Min-Jung Yu,Myoung-Hwan Ko,Jong-Kwan Park,Heecheon You 대한인간공학회 2018 대한인간공학회 학술대회논문집 Vol.2018 No.5

Development and Usability Testing of a User-Centered 3D Virtual Liver Surgery Planning System

Xiaopeng Yang,Hee Chul Yu,Younggeun Choi,Wonsup Lee,Jaedo Yang,Ji Hyun Kim,Baik Hwan Cho,Heecheon You 대한인간공학회 2014 대한인간공학회 학술대회논문집 Vol.2014 No.11

The present study developed a user-centered 3D virtual liver surgery planning system called Dr. Liver, which has clinical applicability and effectiveness to support liver surgery. Use scenarios of Dr. Liver were developed through literature review, benchmarking, and interviews with surgeons. User interfaces of Dr. Liver were designed with various user-friendly features such as hierarchical dropdown menus, hotkey menus provided on the screen, and 3D view indication box and resetting buttons. Novel image processing algorithms were developed and implemented into Dr. Liver for accurate and efficient liver surgery planning. Potential usability problems were identified by a preliminary usability testing at the early development stage and improvements were made for the identified usability problems. A usability testing showed that the improved Dr. Liver achieved higher time efficiency (= 21.8 ± 4.4 min) and overall user satisfaction (= 6.2 ± 0.7) than the previous version (time = 36.6 ± 1.7 min; overall satisfaction = 5.6 ± 0.5). The development and evaluation process of Dr. Liver in this study would help practitioners develop a user-friendly virtual surgery planning system.

Development and Usability Testing of a User-Centered 3D Virtual Liver Surgery Planning System

Xiaopeng Yang,Hee Chul Yu,Younggeun Choi,Jae Do Yang,Baik Hwan Cho,Heecheon You 대한인간공학회 2017 大韓人間工學會誌 Vol.36 No.1

Objective: The present study developed a user-centered 3D virtual liver surgery planning (VLSP) system called Dr. Liver to provide preoperative information for safe and rational surgery. Background: Preoperative 3D VLSP is needed for patients" safety in liver surgery. Existing systems either do not provide functions specialized for liver surgery planning or do not provide functions for cross-check of the accuracy of analysis results. Method: Use scenarios of Dr. Liver were developed through literature review, benchmarking, and interviews with surgeons. User interfaces of Dr. Liver with various user-friendly features (e.g., context-sensitive hotkey menu and 3D view zavigation box) was designed. Novel image processing algorithms (e.g., hybrid semi-automatic algorithm for liver extraction and customized region growing algorithm for vessel extraction) were developed for accurate and efficient liver surgery planning. Usability problems of a preliminary version of Dr. Liver were identified by surgeons and system developers and then design changes were made to resolve the identified usability problems. Results: A usability testing showed that the revised version of Dr. Liver achieved a high level of satisfaction (6.1 ± 0.8 out of 7) and an acceptable time efficiency (26.7 ± 0.9 min) in liver surgery planning. Conclusion: Involvement of usability testing in system development process from the beginning is useful to identify potential usability problems to improve for shortening system development period and cost. Application: The development and evaluation process of Dr. Liver in this study can be referred in designing a user-centered system.

Design and Evaluation of a User-Centered Procedure with User-Friendly UIs for Computer-Aided Liver Segmentation

Xiaopeng Yang,Nahyeon Lee,Jaedo Yang,Hee Chul Yu,Heecheon You 대한인간공학회 2016 대한인간공학회 학술대회논문집 Vol.2016 No.06

Segmentation of liver and vessels from CT images and classification of liver segments for preoperative liver surgical planning in living donor liver transplantation

Yang, Xiaopeng,Yang, Jae Do,Hwang, Hong Pil,Yu, Hee Chul,Ahn, Sungwoo,Kim, Bong-Wan,You, Heecheon Elsevier 2018 COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE Vol.158 No.-

<P><B>Abstract</B></P> <P><B>Background and objective</B></P> <P>The present study developed an effective surgical planning method consisting of a liver extraction stage, a vessel extraction stage, and a liver segment classification stage based on abdominal computerized tomography (CT) images.</P> <P><B>Methods</B></P> <P>An automatic seed point identification method, customized level set methods, and an automated thresholding method were applied in this study to extraction of the liver, portal vein (PV), and hepatic vein (HV) from CT images. Then, a semi-automatic method was developed to separate PV and HV. Lastly, a local searching method was proposed for identification of PV branches and the nearest neighbor approximation method was applied to classifying liver segments.</P> <P><B>Results</B></P> <P>Onsite evaluation of liver segmentation provided by the SLIVER07 website showed that the liver segmentation method achieved an average volumetric overlap accuracy of 95.2%. An expert radiologist evaluation of vessel segmentation showed no false positive errors or misconnections between PV and HV in the extracted vessel trees. Clinical evaluation of liver segment classification using 43 CT datasets from two medical centers showed that the proposed method achieved high accuracy in liver graft volumetry (absolute error, AE = 45.2 ± 20.9 ml; percentage of AE, %AE = 6.8% ± 3.2%; percentage of %AE > 10% = 16.3%; percentage of %AE > 20% = none) and the classified segment boundaries agreed with the intraoperative surgical cutting boundaries by visual inspection.</P> <P><B>Conclusions</B></P> <P>The method in this study is effective in segmentation of liver and vessels and classification of liver segments and can be applied to preoperative liver surgical planning in living donor liver transplantation.</P> <P><B>Highlights</B></P> <P> <UL> <LI> The present study developed an effective surgical planning method consisting of a liver extraction stage, a vessel extraction stage, and a liver segment classification stage based on abdominal computerized tomography (CT) images. </LI> <LI> An automatic seed point identification method, customized level set methods, and an automated thresholding method were applied in this study to extraction of the liver, portal vein (PV), and hepatic vein (HV) from CT images. </LI> <LI> A local searching method was proposed for identification of PV branches and the nearest neighbor approximation method was applied to classifying liver segments. </LI> <LI> Onsite evaluation of liver segmentation provided by the SLIVER07 website showed that the liver segmentation method achieved an average volumetric overlap accuracy of 95.2%. </LI> <LI> Clinical evaluation of liver segment classification showed that the intraoperative surgical cutting boundaries agreed with the classified segment boundaries. </LI> </UL> </P>