Leap Motion Technology In Learning

Drăgoi, George

doi:10.15405/epsbs.2017.05.02.126

Cited by 8 publications

(2 citation statements)

References 5 publications

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“…More recently, sensible optic tracking systems such as the Leap Motion Controller® (Ultraleap) 18 capable of tracking movements of small objects and particularly of the hands are available. 19 , 20 …”

Section: Introductionmentioning

confidence: 99%

Neurodata Tracker: Software for computational assessment of hand motor skills based on optical motion capture in a virtual environment

et al. 2023

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Objectives Deficits affecting hand motor skills negatively impact the quality of life of patients. The NeuroData Tracker platform has been developed for the objective and precise evaluation of hand motor deficits. We describe the design and development of the platform and analyse the technological feasibility and usability in a relevant clinical setting. Methods A software application was developed in Unity (C#) to obtain kinematic data from hand movement tracking by a portable device with two cameras and three infrared sensors (leap motion®). Four exercises were implemented: (a) wrist flexion-extension (b) finger-grip opening-closing (c) finger spread (d) fist opening-closing. The most representative kinematic parameters were selected for each exercise. A script in Python was integrated in the platform to transform real-time kinematic data into relevant information for the clinician. The application was tested in a pilot study comparing the data provided by the tool from ten healthy subjects without any motor impairment and ten patients diagnosed with a stroke with mild to moderate hand motor deficit. Results The NeuroData Tracker allowed the parameterization of kinematics of hand movement and the issuance of a report with the results. The comparison of the data obtained suggests the feasibility of the tool for detecting differences between patients and healthy subjects. Conclusions This new platform based on optical motion capturing provides objective measurement of hand movement allowing quantification of motor deficits. These findings require further validation of the tool in larger trials to verify its usefulness in the clinical setting.

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Section: Introductionmentioning

confidence: 99%

Neurodata Tracker: Software for computational assessment of hand motor skills based on optical motion capture in a virtual environment

et al. 2023

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“…This project is a hand gesture attempt to control a drone. It involves the development of an application using a Leap Motion [1] to recognize the user's hand gestures. This means that hand gestures must be recognized first.…”

Section: Introductionmentioning

confidence: 99%

Flying Drone Controller by Hand Gesture Using Leap Motion

Mutalib¹

2020

IJATCSE

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The Leap Motion is the mechanism to Flying Drone Controller by Hand Gesture Using Leap Motion. It has a sensor for hand gesture to fly a drone. This undertaking consists of a few hardware and software that are microcontroller Arduino, drone-like SYMA X5SC Explorer 2, Microsoft Visual Studio 2019, gesture sensor Leap motion and digital to analog MCP 4725. Leap Motion is taught by the manual motion and the Arduino instruction. Arduino receives the Leap Motion instructions, and the remote controller receives data from Arduino and sends signal to a drone immediately. Based on the hand gesture instruction, Drone flies into the air. There are three instructional conditions: throttle, pitch and roll. This system is designed to create a hand gesture instruction and to develop the program code of the features of the Leap Mo-tion using the Microsoft Visual Studio 2019. This technology has been explored and researched and many new things can be learned. Leap Motion was selected to operate a drone with a touchless condition for this task. There were three purposes in this task after investigations of the control system of hand gesture were made, particularly for drones. The planning is designed to ensure that the system fulfills its goals. It is suitable for farming, photography and military applications. Therefore, drone handling can be improved in future without shifting the key or pressing any control button.

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