Sensorymotor Synergies: Fusion of Cutaneous Touch and Proprioception in the Perceived Hand Kinematics

2016 ◽  
pp. 87-98 ◽  
Author(s):  
Alessandro Moscatelli ◽  
Matteo Bianchi ◽  
Alessandro Serio ◽  
Antonio Bicchi ◽  
Marc O. Ernst
Keyword(s):  
Hand Kinematics

INVESTIGATION OF HAND KINEMATICS TOWARDS FRONT CRAWL SWIMMING USING NON-INVASIVE REAL-TIME MONITORING SYSTEM

2014 ◽  
Author(s):  
Rozaimi Ghazali ◽  
◽  
Asiah Mohd Pilus ◽  
Wan Mohd Bukhari Wan Daud ◽  
Mohd Juzaila Abd Latif ◽  
...  
Keyword(s):  
Real Time ◽  
Monitoring System ◽  
Real Time Monitoring ◽  
Front Crawl ◽  
Non Invasive ◽  
Hand Kinematics

scholarly journals A deep Kalman filter network for hand kinematics estimation using sEMG

2021 ◽  
Vol 143 ◽  
pp. 88-94
Author(s):  
Tianzhe Bao ◽  
Yihui Zhao ◽  
Syed Ali Raza Zaidi ◽  
Shengquan Xie ◽  
Pengfei Yang ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Hand Kinematics

Hand kinematics during visually guided reaching in children with deprivation amblyopia

2021 ◽  
Vol 25 (4) ◽  
pp. e20-e21
Author(s):  
Krista R. Kelly ◽  
Reed M. Jost ◽  
Eileen E. Birch ◽  
Serena X. Wang ◽  
Jeffrey Hunter ◽  
...  
Keyword(s):  
Visually Guided ◽  
Visually Guided Reaching ◽  
Hand Kinematics

Professional and High-Level Gamers: Differences in Performance, Muscle Activity, and Hand Kinematics for Different Mice

2021 ◽  
pp. 1-16
Author(s):  
Guangchuan Li ◽  
Mengcheng Wang ◽  
Federico Arippa ◽  
Alan Barr ◽  
David Rempel ◽  
...  
Keyword(s):  
Muscle Activity ◽  
Hand Kinematics ◽  
High Level

scholarly journals Effect on hand kinematics when using assistive devices during activities of daily living

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e7806
Author(s):  
Alba Roda-Sales ◽  
Margarita Vergara ◽  
Joaquín L. Sancho-Bru ◽  
Verónica Gracia-Ibáñez ◽  
Néstor J. Jarque-Bou
Keyword(s):  
Activities Of Daily Living ◽  
Daily Living ◽  
Peak Velocity ◽  
Assistive Devices ◽  
Joint Angles ◽  
Kinematic Parameters ◽  
Hand Kinematics ◽  
Instrumented Glove ◽  
Design Characteristics ◽  
Selection Of

Assistive devices (ADs) are products intended to overcome the difficulties produced by the reduction in mobility and grip strength entailed by ageing and different pathologies. Nevertheless, there is little information about the effect that the use of these devices produces on hand kinematics. Thus, the aim of this work is to quantify this effect through the comparison of kinematic parameters (mean posture, ROM, median velocity and peak velocity) while performing activities of daily living (ADL) using normal products and ADs. Twelve healthy right-handed subjects performed 11 ADL with normal products and with 17 ADs wearing an instrumented glove on their right hand, 16 joint angles being recorded. ADs significantly affected hand kinematics, although the joints affected differed according to the AD. Furthermore, some pattern effects were identified depending on the characteristics of the handle of the ADs, namely, handle thickening, addition of a handle to products that initially did not have one, extension of existing handles or addition of handles to apply higher torques. An overview of the effects of these design characteristics on hand kinematics is presented as a basis for the selection of the most suitable AD depending on the patient’s impairments.

A minimal limit-cycle model of hand kinematics in basket-ball-bouncing

2005 ◽  
Vol 382 (3) ◽  
pp. 201-205 ◽  
Author(s):  
Tlili Mohamed ◽  
Babault Nicolas ◽  
Mottet Denis
Keyword(s):  
Limit Cycle ◽  
Cycle Model ◽  
Hand Kinematics ◽  
Ball Bouncing

scholarly journals SEEDS, simultaneous recordings of high-density EMG and finger joint angles during multiple hand movements

2019 ◽  
Vol 6 (1) ◽  
Author(s):  
Ana Matran-Fernandez ◽  
Itzel Jared Rodríguez Martínez ◽  
Riccardo Poli ◽  
Christian Cipriani ◽  
Luca Citi
Keyword(s):  
High Density ◽  
Hand Movements ◽  
Joint Angles ◽  
Neural Drive ◽  
Data Glove ◽  
Hand Kinematics ◽  
Extensor Muscles ◽  
Electrode Selection ◽  
Methods Of Control

Abstract We present the SurfacE Electromyographic with hanD kinematicS (SEEDS) database. It contains electromyographic (EMG) signals and hand kinematics recorded from the forearm muscles of 25 non-disabled subjects while performing 13 different movements at normal and slow-paced speeds. EMG signals were recorded with a high-density 126-channel array centered on the extrinsic flexors of the fingers and 8 further electrodes placed on the extrinsic extensor muscles. A data-glove was used to record 18 angles from the joints of the wrist and fingers. The correct synchronisation of the data-glove and the EMG was ascertained and the resulting data were further validated by implementing a simple classification of the movements. These data can be used to test experimental hypotheses regarding EMG and hand kinematics. Our database allows for the extraction of the neural drive as well as performing electrode selection from the high-density EMG signals. Moreover, the hand kinematic signals allow the development of proportional methods of control of the hand in addition to the more traditional movement classification approaches.

scholarly journals Recognition of Sign Language Alphabets and Numbers based on Hand Kinematics using A Data Glove

2018 ◽  
Vol 133 ◽  
pp. 55-62 ◽  
Author(s):  
Nayan M. Kakoty ◽  
Manalee Dev Sharma
Keyword(s):  
Sign Language ◽  
Data Glove ◽  
Hand Kinematics

Design of Spatial Non-Anthropomorphic Articulated Systems Based on Arm Joint Constraint Kinematic Data for Human Interactive Robotics Applications

2015 ◽  
Author(s):  
Hyosang Moon ◽  
Nina P. Robson
Keyword(s):  
Degrees Of Freedom ◽  
Wrist Joint ◽  
Design Parameters ◽  
Human Hand ◽  
Link Length ◽  
Hand Motion ◽  
Motion Constraints ◽  
Hand Kinematics ◽  
Minimum Jerk ◽  
Articulated Systems

The design of human interactive robotic systems requires additional considerations compared to conventional robotic designs to take into account human factors. In this paper, a recently developed linkage kinematic synthesis incorporating higher order motion constraints is utilized to the synthesis of a five degree of freedom serial TS linkage for human interactive applications. The T represents a universal two degrees-of-freedom shoulder, while the S defines a spherical three degrees-of-freedom wrist joint. The desired hand kinematics and its time derivatives can be obtained by a motion capture system as well as from the hand-object/environment contact geometries at two task locations. In order to determine the design parameters (i.e., locations of the base/shoulder and moving/wrist pivots, as well as the link length connecting these joints), position, velocity and acceleration constraint equations of the TS linkage are solved in the vicinity of the initial and the final reaching locations. The entire robotic joint trajectories are formulated via minimum jerk theory to closely approximate human natural hand profile with an elbow joint constraint. In this manner, the TS linkage system can be designed to guarantee to reproduce the natural human hand kinematics with the minimum amount of information about the desired hand kinematic specifications. The applicability of the proposed technique was verified by designing a TS linkage system from a captured human data, and then comparing the generated end-effector trajectory with the human hand motion trajectory, which show promising results.

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