Analysis of movement and gesture recognition using Leap Motion Controller

Sharma, Anshul; Yadav, Aditya; Srivastava, Shivangi; Gupta, Ritu

doi:10.1016/j.procs.2018.05.008

Cited by 16 publications

(3 citation statements)

References 6 publications

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“…One of the interfaces that have demonstrated versatility to control multiple systems is the Leap Motion (LM) sensor [20], [21], [22], [23], [24], [25], [26]. This is a motion sensor that allows us to acquire and interpret gestures that we make with our hands in the workspace captured by the device.…”

Section: Introductionmentioning

confidence: 99%

Optimal Signal Processing for Steady Control of a Robotic Arm Suppressing Hand Tremors for EOD Applications

Chilo

Ccari

Supo³

et al. 2023

IEEE Access

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Teleoperated robotics in recent years has proven to be valuable support in EOD tasks; a remarkable improvement in the systems that control these robots has been the Natural User Interfaces (NUI); however, the research that implements this type of system does not focus on the stability of the robotic arm movements, necessary for this type of applications due to the danger of working with explosives. In this paper, we propose the implementation of an Optimal Signal Processing for a NUI interface based on the Leap Motion (LM) controller. The main objective of this research is to correctly identify the intentional movements of the operator, achieve high stability of the robotic gripper and suppress the physiological tremors from the hand of the operator, considering not to increase the mental workload and not decrease the usability of the system. The signal processing proposed in this paper is composed of three filtering algorithms: Kalman, FIR, and moving average with a threshold. In addition, the obtained results are compared with the most representative processing of recent research using LM for robotic arm control. To evaluate and validate the proposed signal processing, a target path tracking test, a stability analysis of the robotic gripper, and a performance analysis in the execution of Pick and Place tasks, NASA-TLX and SUS questionnaires are developed. Finally, the proposed Optimal Signal processing is implemented in the DOBOT-MAGICIAN and tested by police officers of the EOD Unit-Arequipa (UDEX-AQP); the results indicate a reduction of the average Vibration of 31.61% and the Target Path Tracking error of 67.57%.

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Section: Introductionmentioning

confidence: 99%

Optimal Signal Processing for Steady Control of a Robotic Arm Suppressing Hand Tremors for EOD Applications

Chilo

Ccari

Supo³

et al. 2023

IEEE Access

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show abstract

“…For that, 3D methods based on Leap Motion and Kinect promise fast, contactless hand tracking and diagnostics. Systems designed for gesture recognition [16,17] do not require separate markers on specific anatomical segments of the hand and allow measurements without touching the device. A non-contact examination is safer for the patient and does not cause pain or discomfort.…”

Section: Introductionmentioning

confidence: 99%

Hand Measurement System Based on Haptic and Vision Devices towards Post-Stroke Patients

Koter

Samowicz

Redlicka

et al. 2022

Sensors

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Diagnostics of a hand requires measurements of kinematics and joint limits. The standard tools for this purpose are manual devices such as goniometers which allow measuring only one joint simultaneously, making the diagnostics time-consuming. The paper presents a system for automatic measurement and computer presentation of essential parameters of a hand. Constructed software uses an integrated vision system, a haptic device for measurement, and has a web-based user interface. The system provides a simplified way to obtain hand parameters, such as hand size, wrist, and finger range of motions, using the homogeneous-matrix-based notation. The haptic device allows for active measurement of the wrist’s range of motion and additional force measurement. A study was conducted to determine the accuracy and repeatability of measurements compared to the gold standard. The system functionality was confirmed on five healthy participants, with results showing comparable results to manual measurements regarding fingers’ lengths. The study showed that the finger’s basic kinematic structure could be measured by a vision system with a mean difference to caliper measurement of 4.5 mm and repeatability with the Standard Deviations up to 0.7 mm. Joint angle limits measurement achieved poorer results with a mean difference to goniometer of 23.6º. Force measurements taken by the haptic device showed the repeatability with a Standard Deviation of 0.7 N. The presented system allows for a unified measurement and a collection of important parameters of a human hand with therapist interface visualization and control with potential use for post-stroke patients’ precise rehabilitation.

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“…Its companion algorithm enables the device (according to the manufacturer) to reach an accuracy level of ≈0.01 mm. Previous studies have also suggested the LMC can be a useful tool for translating sign language and hand gestures into sounds [ 14 , 15 , 16 ].…”

Section: Introductionmentioning

confidence: 99%

Intuitive Cognition-Based Method for Generating Speech Using Hand Gestures

Holdengreber

Yozevitch

Khavkin

2021

Sensors

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Muteness at its various levels is a common disability. Most of the technological solutions to the problem creates vocal speech through the transition from mute languages to vocal acoustic sounds. We present a new approach for creating speech: a technology that does not require prior knowledge of sign language. This technology is based on the most basic level of speech according to the phonetic division into vowels and consonants. The speech itself is expected to be expressed through sensing of the hand movements, as the movements are divided into three rotations: yaw, pitch, and roll. The proposed algorithm converts these rotations through programming to vowels and consonants. For the hand movement sensing, we used a depth camera and standard speakers in order to produce the sounds. The combination of the programmed depth camera and the speakers, together with the cognitive activity of the brain, is integrated into a unique speech interface. Using this interface, the user can develop speech through an intuitive cognitive process in accordance with the ongoing brain activity, similar to the natural use of the vocal cords. Based on the performance of the presented speech interface prototype, it is substantiated that the proposed device could be a solution for those suffering from speech disabilities.

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Analysis of movement and gesture recognition using Leap Motion Controller

Cited by 16 publications

References 6 publications

Optimal Signal Processing for Steady Control of a Robotic Arm Suppressing Hand Tremors for EOD Applications

Optimal Signal Processing for Steady Control of a Robotic Arm Suppressing Hand Tremors for EOD Applications

Hand Measurement System Based on Haptic and Vision Devices towards Post-Stroke Patients

Intuitive Cognition-Based Method for Generating Speech Using Hand Gestures

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