scholarly journals Geometry-based finger kinematic models for joint rotation configuration and parameter estimation

2020 ◽  
Vol 17 (4) ◽  
pp. 172988142093057
Author(s):  
Jong-Seob Won ◽  
Seonhun Lee
Keyword(s):  
Degrees Of Freedom ◽  
Effective Means ◽  
Model Development ◽  
Circular Cross Section ◽  
Model Parameters ◽  
Joint Rotation ◽  
Optical Motion ◽  
Kinematic Models ◽  
Geometric Relation ◽  
Optical Motion Capture

In this work, geometry-based finger kinematic models for joint rotation configuration are proposed. The purpose of the work is to provide an effective means of describing an individual-specific finger motion during flexion or extension movements as precisely as possible. Based on the finger’s geometric postures that are observed when fingers naturally grasp a cylindrical object with a circular cross-section, its geometric relation between each phalanx of a finger and the object is extracted, and forms of contact between them are taken into consideration to secure more degrees of freedom for representing finger motions and are parameterized in the model development. A parameter identification approach is adopted to find model parameters that can be used to describe an individual-specific grasping style. For the validation of the proposed models, a set of optical motion capture experiments is performed. From the simulation study, one can see that the models provide one of the feasible and viable solutions to imitate the human finger’s flexion and/or extension movements.

BATMAV: Development and Testing of a SMA-Based Bio-Inspired Flapping Platform

2010 ◽  
Author(s):  
Gheorghe Bunget ◽  
Stefan Seelecke
Keyword(s):  
Degrees Of Freedom ◽  
Kinematic Model ◽  
Biologically Inspired ◽  
Joint Rotation ◽  
Systematic Analysis ◽  
Trailing Edges ◽  
Aerial Vehicle ◽  
Kinematic Models ◽  
Bat Wing ◽  
Thrust Forces

The overall objective of the BATMAV project is the development of a biologically-inspired Micro Aerial Vehicle (MAV) with flexible and foldable wings for flapping flight. This paper presents a platform that features bat-inspired wings which are able to mimic the folding motion of the elbow and wrist joints of the natural flyer. This flapping platform makes use of the dual roll of the Shape Memory Alloys (SMA) to mimic the flexible joints and flapping muscles of the natural wings. The approach of this project was to learn from the natural flyer through a systematic analysis of their flight and to mimic their flapping mechanisms. A systematic study of the bat flight kinematics helped to identify the required joint angles as relevant degrees of freedom for wing actuation. Kinematic models of wings with 2 and 3-DOFs have been developed with the intention of mimicking the wing trajectories of the natural flier Plecotus auritus. A further kinematic model for the joint rotation angle has been developed in order to determine the attachment locations of SMA ‘muscle-wires’ as well as their routes along the wing ‘bones’. As part of this study individual elbow-joint systems were designed, fabricated and used to experimentally validate the above model’s prediction. The elastic skin membrane of the bat wing has been reproduced using a thin-film silicon membrane which has been suitably prestrained and shaped to mimic the leading and trailing edges of the bat wing. To measure the aerodynamic forces developed by the flapping platform, a test stand consisting of two load cells was assembled, and the dynamic tests were performed for a 2-DOF flapping wings. The lift and thrust forces as well as the flapping amplitude were measured.

Rigid Body Guidance of Human Gait as Constrained TRS Serial Chain

2014 ◽  
Author(s):  
Gim Song Soh
Keyword(s):  
Degrees Of Freedom ◽  
Point Of View ◽  
Human Gait ◽  
Synthesis Process ◽  
Dimensional Synthesis ◽  
Two Degrees Of Freedom ◽  
Serial Chain ◽  
Optical Motion ◽  
Musculoskeletal Function ◽  
Optical Motion Capture

The motion of gait is a cyclical activity that requires the coordination between locomotion mechanism, motor control and musculoskeletal function. The basic assumption is that one stride is the same as the next. From a simplified kinematics point of view, the human gait can be considered as a TRS serial chain with six degrees-of-freedom driven by the pelvis rotational and tilting motion during walking. This paper presents a dimensional synthesis procedure for the design of two degrees-of-freedom of spatial eight-bar linkages by mechanically constraining a TRS serial chain. The goal is to develop a methodology for the design of under-actuated lower limb walking devices or passively driven exoskeleton systems. The dimensional synthesis process starts with the specification of the links of a TRS chain according to the gait anthropometric data. We show the various ways how four TS constraints can be used to constrain the links of the this chain to obtain a two degrees-of-freedom spatial eight-bar linkage. We formulate and solve the design equations as well as analyze the resulting eight-bar linkage from the data we obtained from an optical motion capture system. An example demonstrates our results.

scholarly journals An Intelligent In-Shoe System for Gait Monitoring and Analysis with Optimized Sampling and Real-Time Visualization Capabilities

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2869
Author(s):  
Jiaen Wu ◽  
Kiran Kuruvithadam ◽  
Alessandro Schaer ◽  
Richie Stoneham ◽  
George Chatzipirpiridis ◽  
...  
Keyword(s):  
Real Time ◽  
Inertial Sensor ◽  
Neurological Diseases ◽  
Principal Component ◽  
Sampling Frequency ◽  
Powerful Analytical Tool ◽  
Optical Motion ◽  
Analysis System ◽  
Optical Motion Capture ◽  
Gait Monitoring

The deterioration of gait can be used as a biomarker for ageing and neurological diseases. Continuous gait monitoring and analysis are essential for early deficit detection and personalized rehabilitation. The use of mobile and wearable inertial sensor systems for gait monitoring and analysis have been well explored with promising results in the literature. However, most of these studies focus on technologies for the assessment of gait characteristics, few of them have considered the data acquisition bandwidth of the sensing system. Inadequate sampling frequency will sacrifice signal fidelity, thus leading to an inaccurate estimation especially for spatial gait parameters. In this work, we developed an inertial sensor based in-shoe gait analysis system for real-time gait monitoring and investigated the optimal sampling frequency to capture all the information on walking patterns. An exploratory validation study was performed using an optical motion capture system on four healthy adult subjects, where each person underwent five walking sessions, giving a total of 20 sessions. Percentage mean absolute errors (MAE%) obtained in stride time, stride length, stride velocity, and cadence while walking were 1.19%, 1.68%, 2.08%, and 1.23%, respectively. In addition, an eigenanalysis based graphical descriptor from raw gait cycle signals was proposed as a new gait metric that can be quantified by principal component analysis to differentiate gait patterns, which has great potential to be used as a powerful analytical tool for gait disorder diagnostics.

AN ARTIFICIAL INTELLIGENT APPROACH TO TRAFFIC ACCIDENT ESTIMATION: MODEL DEVELOPMENT AND APPLICATION

Transport ◽  
2009 ◽  
Vol 24 (2) ◽  
pp. 135-142 ◽  
Author(s):  
Ali Payıdar Akgüngör ◽  
Erdem Doğan
Keyword(s):  
Genetic Algorithm ◽  
Model Development ◽  
Back Propagation ◽  
Linear Functions ◽  
Model Parameters ◽  
Ann Model ◽  
Back Propagation Algorithm ◽  
Estimation Model ◽  
Average Growth ◽  
Feed Forward Back Propagation

This study proposes an Artificial Neural Network (ANN) model and a Genetic Algorithm (GA) model to estimate the number of accidents (A), fatalities (F) and injuries (I) in Ankara, Turkey, utilizing the data obtained between 1986 and 2005. For model development, the number of vehicles (N), fatalities, injuries, accidents and population (P) were selected as model parameters. In the ANN model, the sigmoid and linear functions were used as activation functions with the feed forward‐back propagation algorithm. In the GA approach, two forms of genetic algorithm models including a linear and an exponential form of mathematical expressions were developed. The results of the GA model showed that the exponential model form was suitable to estimate the number of accidents and fatalities while the linear form was the most appropriate for predicting the number of injuries. The best fit model with the lowest mean absolute errors (MAE) between the observed and estimated values is selected for future estimations. The comparison of the model results indicated that the performance of the ANN model was better than that of the GA model. To investigate the performance of the ANN model for future estimations, a fifteen year period from 2006 to 2020 with two possible scenarios was employed. In the first scenario, the annual average growth rates of population and the number of vehicles are assumed to be 2.0 % and 7.5%, respectively. In the second scenario, the average number of vehicles per capita is assumed to reach 0.60, which represents approximately two and a half‐fold increase in fifteen years. The results obtained from both scenarios reveal the suitability of the current methods for road safety applications.

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