Use of a gesture user interface as a touchless image navigation system in dental surgery: Case series report

Rosa, Guillermo M.; Elizondo, María Lidia

doi:10.5624/isd.2014.44.2.155

Cited by 56 publications

(42 citation statements)

References 4 publications

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“…Only five (12%) of the 42 studies that evaluated the MK identified disadvantages related with a longer latency time, difficulty in recreating an image when compared with a keyboard or mouse [6], limited gesture recognition, interference between the movements of different people in environments with small areas [71,77,107], and the preference of users for the mouse in a comparative study [46]. Various studies have highlighted the inaccuracy of the MK in detecting finger movements [6,19,77,110], and the system also requires the use of large format screens [14,23,58,77,81].…”

Section: Discussionmentioning

confidence: 99%

“…It has three infrared emitters and two infrared cameras [14,47,79,111,112]. The LMC interaction zone is an inverted cone of approximately 0.23 m³, and the motion detection range fluctuates between 20 mm and 600 mm [67,106].…”

Section: Discussionmentioning

confidence: 99%

“…Natural user interfaces (NUIs) were first developed in the 1990s, so that natural human movements could interact with the computer and manipulate radiological images in sterile surgical environments [14]. One variant is gesture-based interfaces (GBI) [15], which manipulated using the hands without contact and promised to be a viable solution in ORs and autopsy suites [10,[16][17][18][19].…”

Section: Introductionmentioning

confidence: 99%

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Use of commercial off-the-shelf devices for detection of manual gestures in surgery. A Systematic Literature Review (Preprint)

Alvarez-Lopez¹,

Maina²,

Saigí-Rubió³

2018

Preprint

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Background. The increasingly pervasive presence of technology in the operating room (OR) raises the need to study the interaction between the surgeon and the computer system. A new generation of tools known as commercial off-the-shelf (COTS) devices that enable non-contact gesture-based human-computer interaction (HCI) are currently being explored as a solution in surgical environments. The aim of this systematic review was to provide an account of the state-of-the-art of COTS devices in the detection of manual gestures in surgery, and to identify their use as a simulation tool for teaching motor skills in minimally invasive surgery (MIS). Methods. A systematic literature review was conducted in PubMed, Embase, ScienceDirect and IEEE for articles published between January 2000 and 2016 on the use of COTS devices for gesture detection in surgical environments, and in simulation for surgical skills learning in MIS. Results. A total of 2709 studies were identified, 76 of which met the search selection criteria. The Microsoft KinectTM and the Leap Motion ControllerTM were the most widely used COTS devices. The most common intervention was image manipulation in surgical and interventional radiology environments, followed by interaction with virtual reality environments for educational or interventional purposes; the possibility of using this technology to develop portable, low-cost simulators for skills learning in MIS was also examined. Given that the vast majority of articles found in this systematic review were proof-of-concept or prototype user and feasibility testing, we can conclude that this is a field that is still in the exploration phase in areas that require touchless manipulation in environments and settings that must adhere to asepsis and antisepsis protocols, such as angiography suites and operating rooms. Conclusions: COTS devices applied to hand and instrument GBIs in the field of simulation for skills learning and training in MIS could open up a promising field to achieve the ubiquitous training and pre-surgical warm-up.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Use of commercial off-the-shelf devices for detection of manual gestures in surgery. A Systematic Literature Review (Preprint)

Alvarez-Lopez¹,

Maina²,

Saigí-Rubió³

2018

Preprint

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“…As can be seen, the most common system application for touchless, gesture-driven interfaces has been various forms of image navigation, closely aligned with the OR and interventional radiology contexts listed above. Medical image navigation is the goal in seventeen papers, [4][5][6][7][8][9]11,14,[16][17][18][19][20][21][22][23][24] with the more specific subset of magnetic resonance imaging (MRI) image navigation being the goal in six papers. 5,7,8,9,14,16 Task context was also significant in identifying tasks for testing the systems implemented, such as measuring a lesion on MRI images.…”

Section: Context Of Usementioning

confidence: 99%

Touchless computer interfaces in hospitals: A review

Cronin¹,

Doherty

2018

Health Informatics J

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The widespread use of technology in hospitals and the difficulty of sterilising computer controls has increased opportunities for the spread of pathogens. This leads to an interest in touchless user interfaces for computer systems. We present a review of touchless interaction with computer equipment in the hospital environment, based on a systematic search of the literature. Sterility provides an implied theme and motivation for the field as a whole, but other advantages, such as hands-busy settings, are also proposed. Overcoming hardware restrictions has been a major theme, but in recent research, technical difficulties have receded. Image navigation is the most frequently considered task and the operating room the most frequently considered environment. Gestures have been implemented for input, system and content control. Most of the studies found have small sample sizes and focus on feasibility, acceptability or gesture-recognition accuracy. We conclude this article with an agenda for future work.

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“…With the benefits of natural and intuitive interactions, and free from sanitation problems in public spaces, the applications of mid-air hand gestures included interactive navigation systems in museum or virtual museum [3,4], medical or surgical imaging system [5,6,7,8], large display interactions [9], interactive and public display [10], and 3D modelling [11,12,13,14]. Based on previous research, mid-air hand gestures could be analyzed in five gesture types: pointing, semaphoric, pantomimic, iconic, and manipulation [15].…”

Section: Literature Reviewmentioning

confidence: 99%

Identifying the Usability Factors of Mid-Air Hand Gestures for 3D Virtual Model Manipulation

Chen

Cheng

Chu

et al. 2017

Universal Access in Human–Computer Interaction. Designing Novel Interactions

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Abstract. Although manipulating 3D virtual models with mid-air hand gestures had the benefits of natural interactions and free from the sanitation problems of touch surfaces, many factors could influence the usability of such an interaction paradigm. In this research, the authors conducted experiments to study the visionbased mid-air hand gestures for scaling, translating, and rotating a 3D virtual car displayed on a large screen. An Intel RealSense 3D Camera was employed for hand gesture recognition. The two-hand gesture with grabbing then moving apart/close to each other was applied to enlarging/shrinking the 3D virtual car. The one-hand gesture with grabbing then moving was applied to translating a car component. The two-hand gesture with grabbing and moving relatively along the circumference of a horizontal circle was applied to rotating the car. Seventeen graduate students were invited to participate in the experiments and offer their evaluations and comments for gesture usability. The results indicated that the width and depth of detection ranges were the key usability factors for two-hand gestures with linear motions. For dynamic gestures with quick transitions and motions from open to close hand poses, ensuring gesture recognition robustness was extremely important. Furthermore, given a gesture with ergonomic postures, inappropriate control-response ratio could result in fatigue due to repetitive exertions of hand gestures for achieving the precise controls of 3D model manipulation tasks.

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Use of a gesture user interface as a touchless image navigation system in dental surgery: Case series report

Cited by 56 publications

References 4 publications

Use of commercial off-the-shelf devices for detection of manual gestures in surgery. A Systematic Literature Review (Preprint)

Use of commercial off-the-shelf devices for detection of manual gestures in surgery. A Systematic Literature Review (Preprint)

Touchless computer interfaces in hospitals: A review

Identifying the Usability Factors of Mid-Air Hand Gestures for 3D Virtual Model Manipulation

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