Anatomical parameters for musculoskeletal modeling of the hand and wrist

A musculoskeletal model of the hand and wrist can provide valuable biomechanical and neurophysiological insights, relevant for clinicians and ergonomists. Currently, no consistent data-set exists comprising the full anatomy of these upper extremity parts. The aim of this study was to collect a complete anatomical data-set of the hand and wrist, including the intrinsic and extrinsic muscles. One right lower arm, taken from a fresh frozen female specimen, was studied. Geometrical data for muscles and joints were digitized using a 3D optical tracking system. For each muscle, optimal fiber length and physiological cross-sectional area were assessed based on muscle belly mass, fiber length, and sarcomere length. A brief description of model, in which these data were imported as input, is also provided. Anatomical data including muscle morphology and joint axes (48 muscles and 24 joints) and mechanical representations of the hand are presented. After incorporating anatomical data in the presented model, a good consistency was found between outcomes of the model and the previous experimental studies

Anatomical parameters for musculoskeletal modeling of the hand and wrist

International audienceA musculoskeletal model of the hand and wrist can provide valuable biomechanical and neurophysiological insights, relevant for clinicians and ergonomists. Currently, no consistent data-set exists comprising the full anatomy of these upper extremity parts. The aim of this study was to collect a complete anatomical data-set of the hand and wrist, including the intrinsic and extrinsic muscles. One right lower arm, taken from a fresh frozen female specimen, was studied. Geometrical data for muscles and joints were digitized using a 3D optical tracking system. For each muscle, optimal fiber length and physiological cross-sectional area were assessed based on muscle belly mass, fiber length, and sarcomere length. A brief description of model, in which these data were imported as input, is also provided. Anatomical data including muscle morphology and joint axes (48 muscles and 24 joints) and mechanical representations of the hand are presented. After incorporating anatomical data in the presented model, a good consistency was found between outcomes of the model and the previous experimental studies

Understanding Finger Motor Control in Young And Elderly

status: publishe

Northren forests boundary mapping of Iran Using Landsat7 ETM+ data

For sustainable management of the Caspian Forests of Iran, a most appropriate and fastest method of data collection and combination is essential. Combination of Satellite digital data with field data, using Geographic Information Systems, (GIS) could be applied to obtain accurate information for multiple decision making which is influenced by different factors. In this study eight senses of Landsat 7ETM+ data accosted from Caspian Forests of Iran, June and July 2000, were used. Based on OIF index and statistical analysis of the ETM data, color composite 3,4 and 5 were selected for unsupervised classification. The ground observation information were collected from 3860 plots(30*30), using unsupervised map as a primary map. Overall, combining the ETM and the ground data throw the field information, using the supervised classification method, boundary of the Caspian Forests of Iran were achieved in six classes (Dense forest, Sparse forest, Rangeland, Farm land, Water and Bare soil). The classification accuracy assessment showed that the accuracy rates of the dense forest, sparse forast, rangaland, farmland, water and bara soil were 83, 78, 54, 76 and 98 percent, respectively

Understanding Finger Motor Control In Young And Elderly

Veeger, H.E.J. [Promotor]Jonkers, I. [Promotor]Maas, H. [Copromotor]Stegeman, D.F. [Copromotor

SubjectsData.mat

Raw data related to article "<br> p.p1 {margin: 0.0px 0.0px 0.0px 0.0px; font: 12.0px Helvetica} Timing and extent of finger force enslaving during a dynamic force task cannot be explained by EMG activity patterns"<div>Structure of Matlab file: <br><div>Rows: subjects (10)</div></div><div>Columns: force resistance levels 4,6 and 8 N. Ramp force build up and MVC during flexion and extension. </div><div><br></div

Similarity of different lifting techniques in trunk muscular synergies

Lifting is known to be a major reason for musculoskeletal injuries. In this way, lifting has a crucial effect on human musculoskeletal system and intensity of this impact depends slightly on the selection of techniques. Underlying mechanisms by which trunk muscles are executed during performing lifting are central to biomechanical study of lifting techniques. In the current study, the trunk muscular control mechanisms of lifting are investigated using the synergetic control analysis. Non-negative matrix factorization has been used to extract trunk muscles synergies from their activities – which are computed by a previously validated musculoskeletal model – during different lifting techniques aimed to investigate motor control strategies. Three lifting techniques are considered; stoop, squat and semi-squat. Three synergies account for variety among muscle activation of trunk muscles with related VAF (Variability Account For) of over 95%. Trunk muscle synergy weightings and related time-varying coefficients are calculated for each kind of lifting techniques considering three synergies. Paired correlation coefficients between muscle synergies are all greater than 0.91 (P < 0.05) suggesting that trunk muscle synergies are similar for examined techniques in spite of their kinematic diversity. This similarity can be a result of their common ultimate goal. The acquired results also elucidate the mechanisms of muscle activation patterns that can be exploited in future studies and ergonomic interventions

Analysing the land-use change effects on soil erosion and sediment in the North of Iran; a case study: Talar watershed

This research aims at predicting the future land-use and examining the effects of the land-use changes on the present and future soil erosion and sediment delivery. Then, Land Change Modeler (LCM) and Geo-spatial Water Erosion Prediction Project (GeoWEPP) were applied. Annual suspended sediment derived from sediment rating curves in Talar Watershed, Iran was used to evaluate the GeoWEPP. The predicted sediment load values of 2016 by GeoWEPP in the likely zone of 0.5 for Shirgah-Talar and Valikbon hydrometric stations were achieved respectively as 756094 and 62082.8 ton. Moreover, the mean annual sediment delivery per unit area of 2000, 2010, 2016 and 2030 were calculated respectively as 37.5, 43, 49.4 and 53.2 (t/ha.yr). The reason for the acquired incremental trend of the soil loss and sediment delivery was the land-use change. The results proved the acceptable performance of LCM combined by GeoWEPP to predict the nearby land-use and related sediment delivery