Microsoft Kinect and the Leap Motion Controller were the most widely used COTS gesture-detection devices in surgical research, appearing in 50% and 36% of the 86 included studies respectively¶
Claim · All claims
Evidence · 1 study · reviewr2·q3
Currency · newest study 2019 · not yet checked against its sources · not reviewed by a person
Subclaims¶
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q3 i? Of 86 included studies, 43 (50%) concerned Microsoft Kinect and 31 (36%) the Leap Motion Controller, making these the two dominant COTS devices for gesture detection in surgery. → Alvarez-Lopez F 2019
Evidence¶
Alvarez-Lopez F 2019¶
Alvarez-Lopez F, Maina MF, Saigí-Rubió F. (2019). Use of Commercial Off-The-Shelf Devices for the Detection of Manual Gestures in Surgery: Systematic Literature Review. Journal of Medical Internet Research. https://doi.org/10.2196/11925
q3 · i? · review · r2
Systematic review searching six databases for articles published January 2000 to December 2017; 3180 studies were identified and 86 met the selection criteria. The review reports that "Microsoft Kinect (Microsoft Corp) and the Leap Motion Controller (Leap Motion Inc) were the most widely used COTS devices".
"A total of 3180 studies were identified, 86 of which met the search selection criteria. Microsoft Kinect (Microsoft Corp) and the Leap Motion Controller (Leap Motion Inc) were the most widely used COTS devices."
Discussion¶
Related Claims¶
- The most common use of gesture-based COTS devices in surgery was image manipulation in interventional radiology environments or the operating room (42 studies), followed by virtual or augmented reality for educational or interventional purposes (16 studies)
- In a 42-participant field study, Microsoft Kinect was found more useful and easier to use than the Leap Motion Controller, while the Leap Motion Controller was more accurate for manipulating CT images
- Finger-motion sensor (Leap Motion Controller) operation of angiographic and radiological images was significantly faster than mouse-based operation in observational studies with radiologists and dental students
- A Leap Motion Controller-based system discriminated expert from novice surgical knot-tying performance with 100% accuracy, supporting construct validity for objective dexterity assessment — related
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