scholarly journals Motion capture sensing techniques used in human upper limb motion: a review

Sensor Review ◽  
2019 ◽  
Vol 39 (4) ◽  
pp. 504-511 ◽  
Author(s):  
Muhammad Yahya ◽  
Jawad Ali Shah ◽  
Kushsairy Abdul Kadir ◽  
Zulkhairi M. Yusof ◽  
Sheroz Khan ◽  
...  
Keyword(s):  
Motion Capture ◽  
Upper Limb ◽  
Inertial Sensors ◽  
Sea Water ◽  
Outer Space ◽  
Navigation Systems ◽  
Human Machine Interaction ◽  
Special Effects ◽  
Content Type ◽  
Human Upper Limb

Purpose Motion capture system (MoCap) has been used in measuring the human body segments in several applications including film special effects, health care, outer-space and under-water navigation systems, sea-water exploration pursuits, human machine interaction and learning software to help teachers of sign language. The purpose of this paper is to help the researchers to select specific MoCap system for various applications and the development of new algorithms related to upper limb motion. Design/methodology/approach This paper provides an overview of different sensors used in MoCap and techniques used for estimating human upper limb motion. Findings The existing MoCaps suffer from several issues depending on the type of MoCap used. These issues include drifting and placement of Inertial sensors, occlusion and jitters in Kinect, noise in electromyography signals and the requirement of a well-structured, calibrated environment and time-consuming task of placing markers in multiple camera systems. Originality/value This paper outlines the issues and challenges in MoCaps for measuring human upper limb motion and provides an overview on the techniques to overcome these issues and challenges.

scholarly journals U-Limb: A multi-modal, multi-center database on arm motion control in healthy and post-stroke conditions

GigaScience ◽  
2021 ◽  
Vol 10 (6) ◽  
Author(s):  
Giuseppe Averta ◽  
Federica Barontini ◽  
Vincenzo Catrambone ◽  
Sami Haddadin ◽  
Giacomo Handjaras ◽  
...  
Keyword(s):  
Data Collection ◽  
Upper Limb ◽  
Brain Activity ◽  
Rehabilitation Robotics ◽  
Human Machine Interaction ◽  
Post Stroke ◽  
Upper Limb Movements ◽  
Arm Motion ◽  
And Control ◽  
Human Upper Limb

Abstract Background Shedding light on the neuroscientific mechanisms of human upper limb motor control, in both healthy and disease conditions (e.g., after a stroke), can help to devise effective tools for a quantitative evaluation of the impaired conditions, and to properly inform the rehabilitative process. Furthermore, the design and control of mechatronic devices can also benefit from such neuroscientific outcomes, with important implications for assistive and rehabilitation robotics and advanced human-machine interaction. To reach these goals, we believe that an exhaustive data collection on human behavior is a mandatory step. For this reason, we release U-Limb, a large, multi-modal, multi-center data collection on human upper limb movements, with the aim of fostering trans-disciplinary cross-fertilization. Contribution This collection of signals consists of data from 91 able-bodied and 65 post-stroke participants and is organized at 3 levels: (i) upper limb daily living activities, during which kinematic and physiological signals (electromyography, electro-encephalography, and electrocardiography) were recorded; (ii) force-kinematic behavior during precise manipulation tasks with a haptic device; and (iii) brain activity during hand control using functional magnetic resonance imaging.

scholarly journals Integration of emerging motion capture technologies and videogames for human upper-limb telerehabilitation: A systematic review

DYNA ◽  
2015 ◽  
Vol 82 (189) ◽  
pp. 68-75 ◽  
Author(s):  
Mauro Callejas Cuervo ◽  
Gloria M. Díaz ◽  
Andrés Felipe Ruíz-Olaya
Keyword(s):  
Systematic Review ◽  
Motion Capture ◽  
Upper Limb ◽  
Human Upper Limb

scholarly journals UPPER LIMB 3D MOTION CAPTURE BASED ON INERTIAL SENSORS

2016 ◽  
Author(s):  
Eduardo Morais Carvalho ◽  
Alcimar Barbosa Soares
Keyword(s):  
Motion Capture ◽  
Upper Limb ◽  
Inertial Sensors ◽  
3D Motion ◽  
3D Motion Capture

Pedestrian navigation using inertial sensors and altitude error correction

Sensor Review ◽  
2015 ◽  
Vol 35 (1) ◽  
pp. 68-75 ◽  
Author(s):  
Wen Liu ◽  
Yingjun Zhang ◽  
Xuefeng Yang ◽  
Shengwei Xing
Keyword(s):  
Error Correction ◽  
Inertial Sensors ◽  
Angular Rate ◽  
Gait Recognition ◽  
Inertial Navigation ◽  
Navigation Systems ◽  
Content Type ◽  
Positioning Errors ◽  
Walking Motion ◽  
Dynamic Time

Purpose – The aim of this article is to present a PIN (pedestrian inertial navigation) solution that incorporates altitude error correction, which eliminates the altitude error accurately without using external sensors. The main problem of PIN is the accumulation of positioning errors due to the drift caused by the noise in the sensors. Experiment results show that the altitude errors are significant when navigating in multilayer buildings, which always lead to localization to incorrect floors. Design/methodology/approach – The PIN proposed is implemented over an inertial navigation systems (INS) framework and a foot-mounted IMU. The altitude error correction idea is identifying the most probable floor of each horizontal walking motion. To recognize gait types, the walking motion is described with angular rate measured by IMU, and the dynamic time warping algorithm is used to cope with the different dimension samples due to the randomness of walking motion. After gait recognition, the altitude estimated with INS of each horizontal walking is checked for association with one of the existing in a database. Findings – Experiment results show that high accuracy altitude is achieved with altitude errors below 5 centimeters for upstairs and downstairs routes in a five floors building. Research limitations/implications – The main limitations of the study is the assumption that accuracy floor altitude information is available. Originality/value – Our PIN system eliminates altitude errors accurately and intelligently, which benefits from the new idea of combination of gait recognition and map-matching. In addition, only one IMU is used which is different from other approach that use external sensors.

scholarly journals Architecture proposal for a support system to upper limb telerehabilitation by capturing biomechanical signals

2015 ◽  
Vol 24 (40) ◽  
pp. 41
Author(s):  
Mauro Callejas-Cuervo ◽  
Manuel Andrés Vélez-Guerrero ◽  
Andrés Felipe Ruíz-Olaya ◽  
Rafael María Gutiérrez-Salamanca
Keyword(s):  
Kalman Filter ◽  
Literature Review ◽  
Motion Capture ◽  
Upper Limb ◽  
Joint Angle ◽  
Inertial Sensors ◽  
Motor Disorders ◽  
Motion Capture System ◽  
Active Videogames ◽  
Therapy Service

<p>This article proposes a system for Telerehabilitation of people with motor disorders of the upper limb, by making a literature review about works related with the provision of the physical therapy service with ICT’s use. Likewise, there is a brief description of the modules integrating the system: motion capture system based on inertial sensors and motion capture with camera; joint angle estimator was implemented through Kalman filter; IT app which registers the electronic medical record and finally, the active videogames module.</p>

scholarly journals A 4-DOF Upper Limb Exoskeleton for Physical Assistance: Design, Modeling, Control and Performance Evaluation

2021 ◽  
Vol 11 (13) ◽  
pp. 5865
Author(s):  
Muhammad Ahsan Gull ◽  
Mikkel Thoegersen ◽  
Stefan Hein Bengtson ◽  
Mostafa Mohammadi ◽  
Lotte N. S. Andreasen Struijk ◽  
...  
Keyword(s):  
Upper Limb ◽  
Tracking Control ◽  
Degrees Of Freedom ◽  
Control Method ◽  
Mechanical Design ◽  
Trajectory Tracking Control ◽  
Upper Limb Exoskeleton ◽  
And Performance ◽  
Physically Disabled People ◽  
Human Upper Limb

Wheelchair mounted upper limb exoskeletons offer an alternative way to support disabled individuals in their activities of daily living (ADL). Key challenges in exoskeleton technology include innovative mechanical design and implementation of a control method that can assure a safe and comfortable interaction between the human upper limb and exoskeleton. In this article, we present a mechanical design of a four degrees of freedom (DOF) wheelchair mounted upper limb exoskeleton. The design takes advantage of non-backdrivable mechanism that can hold the output position without energy consumption and provide assistance to the completely paralyzed users. Moreover, a PD-based trajectory tracking control is implemented to enhance the performance of human exoskeleton system for two different tasks. Preliminary results are provided to show the effectiveness and reliability of using the proposed design for physically disabled people.

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