PHYS.IO: Wearable hand tracking device

Silva, Lucas F. M. da; Dantas, Rummenigge Rudson; Diniz, Paula Rejane Beserra; Jeronimo, Victor; Bueno, Luque; Dutra, Thiago Assis

doi:10.1109/civemsa.2016.7524320

Cited by 3 publications

(3 citation statements)

References 17 publications

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“…Simple mechanical frameworks are adopted to capture the moment and are generally equipped with some connections and electrochemical transducers such as a potentiometer to follow the motion. There are also other methods for tracking the movements of the body such as [101][102][103][104][105][106]: (a) Magnetic-based strategy is used wherein magnetic sensors are deployed at different parts of the body and as the body moves, the sensor tracks the movement of the body and records its position; (b) In radio-frequency identification (RFID)-based strategies, the radio-frequency tags and sensors are used to gather the movements of the body; (c) Image sensors are also strategised to catch an image at stipulated period, and then it is processed to evaluate the position/motion of the body; (d) Capacitive-based techniques are also used to capture the body movement with the deployment of capacitive sensor arrays, placed in proximity to the body. Here, a parallel plate of the capacitance concept is used between the body and sensors, noting a change in capacitance as the body moves, and many more.…”

Section: Kinematic Sensorsmentioning

confidence: 99%

A Survey of the Tactile Internet: Design Issues and Challenges, Applications, and Future Directions

2021

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The Tactile Internet (TI) is an emerging area of research involving 5G and beyond (B5G) communications to enable real-time interaction of haptic data over the Internet between tactile ends, with audio-visual data as feedback. This emerging TI technology is viewed as the next evolutionary step for the Internet of Things (IoT) and is expected to bring about a massive change in Healthcare 4.0, Industry 4.0 and autonomous vehicles to resolve complicated issues in modern society. This vision of TI makes a dream into a reality. This article aims to provide a comprehensive survey of TI, focussing on design architecture, key application areas, potential enabling technologies, current issues, and challenges to realise it. To illustrate the novelty of our work, we present a brainstorming mind-map of all the topics discussed in this article. We emphasise the design aspects of the TI and discuss the three main sections of the TI, i.e., master, network, and slave sections, with a focus on the proposed application-centric design architecture. With the help of the proposed illustrative diagrams of use cases, we discuss and tabulate the possible applications of the TI with a 5G framework and its requirements. Then, we extensively address the currently identified issues and challenges with promising potential enablers of the TI. Moreover, a comprehensive review focussing on related articles on enabling technologies is explored, including Fifth Generation (5G), Software-Defined Networking (SDN), Network Function Virtualisation (NFV), Cloud/Edge/Fog Computing, Multiple Access, and Network Coding. Finally, we conclude the survey with several research issues that are open for further investigation. Thus, the survey provides insights into the TI that can help network researchers and engineers to contribute further towards developing the next-generation Internet.

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Section: Kinematic Sensorsmentioning

confidence: 99%

A Survey of the Tactile Internet: Design Issues and Challenges, Applications, and Future Directions

2021

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“…where Q and R represent the process noise covariance and measurement noise covariance respectively. The sequential steps of Kalman filter, in each iteration, are as follows (13)(14)(15)(16).…”

Section: Sensor Fusion -Kalman Filtermentioning

confidence: 99%

“…The systems in place can be preliminarily classified as vision based and non-vision based tracking systems. Vision based tracking uses cameras [1][2][3][4][5] or other optical devices like the Kinect sensor [6][7][8][9], Leap motion controller [10][11][12], etc., whereas non-vision based systems often use wearable interfaces [13][14][15][16] to estimate the position and orientation of the hand.…”

Section: Introductionmentioning

confidence: 99%

Sensor Fusion of Leap Motion Controller and Flex Sensors Using Kalman Filter for Human Finger Tracking

Ponraj

Ren

2018

IEEE Sensors J.

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In our daily life, we, human beings use our hands in various ways for most of our day-to-day activities. Tracking the position, orientation and articulation of human hands has a variety of applications including gesture recognition, robotics, medicine and health care, design and manufacturing, art and entertainment across multiple domains. However, it is an equally complex and challenging task due to several factors like higher dimensional data from hand motion, higher speed of operation, self-occlusion, etc. This paper puts forth a novel method for tracking the finger tips of human hand using two distinct sensors and combining their data by sensor fusion technique.

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