A Wearable and Wirelessly Powered System for Multiple Finger Tracking

Bellitti, Paolo; Angelis, Alessio De; Dionigi, Marco; Sardini, Emilio; Serpelloni, Mauro; Moschitta, Antonio; Carbone, Paolo

doi:10.1109/tim.2020.2969089

Cited by 30 publications

(12 citation statements)

References 27 publications

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“…The proposed algorithms allowed us to circumvent the limitations of inertial sensors described in the Introduction. Unlike [14,15,18,35], our method did not require magnetometers and, as a result, was not sensitive to changes in the magnetic field. Compared to [16,22], we used fewer inertial sensors, which thus simplified the design of the inertial glove.…”

Section: Discussionmentioning

confidence: 99%

“…The paper [17] was devoted to a finger motion tracking system, consisted of an IMU (Inertial Measurement Unit), for tracking the first phalange's motion, and a calibrated stretch sensor, for monitoring the flexion angle between the first and second phalanges. Later, [18] authors represented similar system, that used the same types of sensors for tracking motion of thumb and index fingers and recognized six predefined gestures.…”

Section: Related Workmentioning

confidence: 99%

“…The expressions (15), (18), and ( 19) define the final form of the filter. It is possible to use a non-constant value for parameter β, changing it depending on the current motion, decreasing by large values with spurious accelerations µ.…”

Section: Finger Rotation Estimationmentioning

confidence: 99%

See 2 more Smart Citations

Inertial Sensor Based Solution for Finger Motion Tracking

et al. 2020

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Hand motion tracking plays an important role in virtual reality systems for immersion and interaction purposes. This paper discusses the problem of finger tracking and proposes the application of the extension of the Madgwick filter and a simple switching (motion recognition) algorithm as a comparison. The proposed algorithms utilize the three-link finger model and provide complete information about the position and orientation of the metacarpus. The numerical experiment shows that this approach is feasible and overcomes some of the major limitations of inertial motion tracking. The paper’s proposed solution was created in order to track a user’s pointing and grasping movements during the interaction with the virtual reconstruction of the cultural heritage of historical cities.

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Section: Discussionmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

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Inertial Sensor Based Solution for Finger Motion Tracking

et al. 2020

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“…Alpha and Beta coronaviruses have different symptoms, especially in humans. There are some viruses such as HCoV-229E, HCoV-HKU1, HCoV-OC43 with milder symptoms [6][7][8]. However, viruses such as SARS-CoV and MERS-CoV can cause fatal infections [9,10].…”

Section: Introductionmentioning

confidence: 99%

An automated Covid-19 respiratory sound classification method based on novel local symmetric Euclidean distance pattern and ReliefF iterative MRMR feature selector

Tuncer

Aydemir

Özyurt

et al. 2021

International Advanced Researches and Engineering Journal

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Covid-19 is a new variety of coronavirus that affects millions of people around the world. This virus infected millions of people and hundreds of thousands of people have passed away. Due to the panic caused by Covid-19, recently several researchers have tried to understand and to propose a solution to Covid-19 problem. Especially, researches in machine learning (ML) have been proposed to detect Covid-19 by using X-ray images. In this study, 10 classes of respiratory sounds, including respiratory sounds diagnosed with Covid-19 disease, were collected and ML methods were used to tackle this problem. The proposed respiratory sound classification method has been proposed in this study from feature generation network through hybrid and iterative feature selection to classification phases. A novel multileveled feature generating network is presented by gathering multilevel one-dimensional wavelet transform and a novel local symmetric Euclidean distance pattern (LSEDP). An automated hybrid feature selection method is proposed using ReliefF and ReliefF Iterative Maximum Relevancy Minimum Redundancy (RIMRMR) to select the optimal number of features. Four known classifiers were used to test the capability of our approach for lung disease detection in respiratory sounds. K nearest neighbors (kNN) method has achieved an accuracy of 91.02%.

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“…Another wellknown application, even of considerable commercial interest, is lifelike computer graphics and animation [10]- [12]. As a human-machine interface, hand tracking can be used also to control industrial equipments and robots in real-time [13], [14], even remotely [15]. In combination with machine learning techniques, robots can be taught to perform specific tasks by the repeated observation of human gestures [16].…”

Section: Introductionmentioning

confidence: 99%

MagIK: a Hand Tracking Magnetic Positioning System based on a Kinematic Model of the Hand

Santoni¹,

Angelis²,

Moschitta³

et al. 2021

Preprint

Self Cite

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In this paper we present a hand tracking system based on magnetic positioning. A single magnetic node is mounted on each fingertip, and two magnetic nodes on the back side of the hand. A fixed array of receiving coils is used to detect the magnetic field, from which it is possible to infer position and orientation of each magnetic node. A kinematic model of the whole hand has been developed. Starting from the positioning data of each magnetic node, the kinematic model can be used to calculate position and flexion angle of each finger joint, plus the position and orientation of the hand in space. Relying on magnetic fields, the hand tracking system can work also in nonline-of-sight conditions. The gesture reconstruction is validated by comparing it with a commercial hand tracking system based on a depth camera. The system requires a small amount of electronics to be mounted on the hand. This would allow building a light and comfortable data glove that could be used for several purposes: human-machine interface, sign language recognition, diagnostics, and rehabilitation.

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A Wearable and Wirelessly Powered System for Multiple Finger Tracking

Cited by 30 publications

References 27 publications

Inertial Sensor Based Solution for Finger Motion Tracking

Inertial Sensor Based Solution for Finger Motion Tracking

An automated Covid-19 respiratory sound classification method based on novel local symmetric Euclidean distance pattern and ReliefF iterative MRMR feature selector

MagIK: a Hand Tracking Magnetic Positioning System based on a Kinematic Model of the Hand

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