scholarly journals A Linkage Representation of the Human Hand Skeletal System Using CT Hand Scan Images

2021 ◽  
Vol 11 (13) ◽  
pp. 5857
Author(s):  
Ying Cao ◽  
Xiaopeng Yang ◽  
Zhichan Lim ◽  
Hayoung Jung ◽  
Dougho Park ◽  
...  
Keyword(s):  
Regression Models ◽  
Wrist Joint ◽  
Middle Finger ◽  
Human Hand ◽  
Skeletal System ◽  
Bone Segment ◽  
Lower Maximum ◽  
Joint Center ◽  
Thumb Carpometacarpal ◽  
Hand Length

The present study proposed a method for establishing a linkage representation of the human hand skeletal system. Hand skeletons of 15 male subjects were reconstructed from computed tomography (CT) scans in 10 different postures selected from a natural hand-closing motion. The wrist joint center was estimated as the intersection of the centerline of the metacarpal of the middle finger and the distal wrist crease. The remaining joint centers were kinematically estimated based on the relative motion between the distal bone segment and the proximal bone segment of a given joint. A hand linkage representation was then formed by connecting the derived joint centers. Regression models for predicting internal hand link lengths using hand length as the independent variable were established. In addition, regression models for predicting the joint center coordinates of the thumb carpometacarpal (CMC) and finger metacarpophalangeal (MCP) joints using hand length or hand breadth were established. Our models showed higher R2 values and lower maximum standard errors than the existing models. The findings of the present study can be applied to hand models for ergonomic design and biomechanical modeling.

scholarly journals REGRESSION ANALYSIS TO DETERMINE STATURE FROM HAND ANTHROPOMETRY AMONG ILOCANO POPULATION IN PHILIPPINES FOR PERSON IDENTIFICATION

2021 ◽  
Vol 11 (1) ◽  
pp. 20
Author(s):  
T.Nataraja Moorthy
Keyword(s):  
Ring Finger ◽  
Middle Finger ◽  
Size Analysis ◽  
Human Hand ◽  
Regression Equations ◽  
Person Identification ◽  
Left Hand ◽  
Length Measurements ◽  
The Right ◽  
Hand Length

Stature determination aids the person identification during forensic investigation. The human hand research is the current topic of interest among forensic scientist, forensic medicine experts and anthropologists. Based on sample size analysis, the study involved consented 60 males and 60 females, age ranged from 18 to 55 years old. Stature and hand lengths measurements were made with Stadiometer and Vernier Calipers for analysis.  From each participant, ten hand length measurements, five from left and five from right hands were taken. The five length measurements in left hand are the inter-distance between the distal traverse crease of the wrist (LH) and tip of thumb (T), index finger (I), middle finger (M), ring finger (R) & little finger (L), as abbreviated LHT, LHI, LHM, LHR and LHL. Similarly, the right hand lengths indicated as RHT, RHI, RHM, RHR, and RHL.  The data were statistically analyzed by using SPSS software, version 23 and column chart. The information about age, gender, name, and place of origin of the participants was coded for easy reference. This study finally developed regression equations to determine stature from hand anthropometry among Ilocano population in Philippines for person identification

scholarly journals Relationship between anthropometrics and handgrip strength among Nigerian school children

2017 ◽  
Vol 9 (1) ◽  
pp. 51-56 ◽  
Author(s):  
Adebisi I. Hammed ◽  
Elvis I. Agbonlahor
Keyword(s):  
School Children ◽  
Handgrip Strength ◽  
Body Height ◽  
Middle Finger ◽  
Anthropometric Parameters ◽  
Moment Coefficient ◽  
Hand Length ◽  
Relationship Of ◽  
The Relationship ◽  
Nigerian School

Summary Study aim: Was to investigate the relationship of anthropometrics with handgrip strength (HGS) among Nigerian school children.Material and methods: A total of 200 school children participated in this study. An electronic handgrip dynamometer was used to measure handgrip strength (HGS) in kg. Body height and body weight were measured with a wall-mounted stadiometer in meters and a bathroom weighing scale in kg, respectively. Body mass index (BMI) was then calculated using the formula weight (kg)/height (m2). Also, hand span of both hands was measured from the tip of the thumb to the tip of the small finger with the hand opened as wide as possible. The distance from the distal wrist crease up to the base of the middle finger was taken for palm length and the distal wrist crease to the tip of the middle finger was considered for the measurement of hand length. However, the relationship between HGS and anthropometric parameters was analyzed using Pearson’s product moment coefficient of correlation.Results: The outcome of this study showed that hand and palm length correlated disproportionately and insignificantly (p > 0.05) with both dominant and non-dominant HGS. Also, hand span was found to be a disproportionate correlate of HGS, though such a correlation was only significant (p < 0.05) with dominant HGS. However, BMI and handedness were observed to associate proportionately and significantly (p < 0.05) with HGS.Conclusion: This study therefore concluded that the most important determinants of HGS among Nigerian school children are BMI, handedness and hand span, and thus could be considered as markers of nutritional and health status, as well as physical fitness of these individuals.

scholarly journals Comparable behaviour of ring and little fingers due to an artificial reduction in thumb contribution to hold objects

2020 ◽  
Author(s):  
Banuvathy Rajakumar ◽  
Varadhan SKM
Keyword(s):  
Normal Force ◽  
Safety Margin ◽  
Ring Finger ◽  
Middle Finger ◽  
Human Hand ◽  
Mechanical Advantage ◽  
Free Condition ◽  
Normal Forces ◽  
Fixed Condition ◽  
Little Finger

AbstractBackgroundThe human hand plays a crucial role in accomplishing activities of daily living. The contribution of each finger in the human hand is remarkably unique in establishing object stabilization. According to the mechanical advantage hypothesis, the little finger tends to exert a greater normal force than the ring finger during a supination moment production task to stabilize the object. Similarly, during pronation, the index finger produces more normal force when compared with the middle finger. Hence, the central nervous system employs the peripheral fingers for torque generation to establish the equilibrium as they have a mechanical advantage of longer moment arms for normal force. In our study, we tested whether the mechanical advantage hypothesis is supported in a task in which the contribution of thumb was artificially reduced. We also computed the safety margin of the individual fingers and thumb.MethodologyFifteen participants used five-finger prismatic precision grip to hold a custom-built handle with a vertical railing on the thumb side. A slider platform was placed on the railing such that the thumb sensor could move either up or down. There were two experimental conditions. In the “Fixed” condition, the slider was mechanically fixed, and hence the thumb sensor could not move. In the “Free” condition, the slider platform on which the thumb sensor was placed could freely move. In both conditions, the instruction was to grasp and hold the handle (and the platform) in static equilibrium. We recorded tangential and normal forces of all the fingers.ResultsThe distribution of fingertip forces and moments changed depending on whether the thumb platform was movable (or not). In the free condition, the drop in the tangential force of thumb was counteracted by an increase in the normal force of the ring and little finger. Critically, the normal forces of the ring and little finger were statistically equivalent. The safety margin of the index and middle finger did not show a significant drop in the free condition when compared to fixed condition.ConclusionWe conclude that our results does not support the mechanical advantage hypothesis at least for the specific mechanical task considered in our study. In the free condition, the normal force of little finger was comparable to the normal force of the ring finger. Also, the safety margin of the thumb and ring finger increased to prevent slipping of the thumb platform and to maintain the handle in static equilibrium during the free condition. However, the rise in the safety margin of the ring finger was not compensated by a drop in the safety margin of the index and middle finger.

scholarly journals Gender Differences in Capitate Kinematics are Eliminated After Accounting for Variation in Carpal Size

2008 ◽  
Vol 130 (4) ◽  
Author(s):  
Michael J. Rainbow ◽  
Joseph J. Crisco ◽  
Douglas C. Moore ◽  
Scott W. Wolfe
Keyword(s):  
Gender Differences ◽  
Wrist Joint ◽  
Carpal Bone ◽  
Ulnar Deviation ◽  
Rotation Axes ◽  
Flexion Extension ◽  
Optical Motion ◽  
Joint Center ◽  
Best Fit

Previous studies have found gender differences in carpal kinematics, and there are discrepancies in the literature on the location of the flexion∕extension and radio-ulnar deviation rotation axes of the wrist. It has been postulated that these differences are due to carpal bone size differences rather than gender and that they may be resolved by normalizing the kinematics by carpal size. The purpose of this study was to determine if differences in radio-capitate kinematics are a function of size or gender. We also sought to determine if a best-fit pivot point (PvP) describes the radio-capitate joint as a ball-and-socket articulation. By using an in vivo markerless bone registration technique applied to computed tomography scans of 26 male and 28 female wrists, we applied scaling derived from capitate length to radio-capitate kinematics, characterized by a best-fit PvP. We determined if radio-capitate kinematics behave as a ball-and-socket articulation by examining the error in the best-fit PvP. Scaling PvP location completely removed gender differences (P=0.3). This verifies that differences in radio-capitate kinematics are due to size and not gender. The radio-capitate joint did not behave as a perfect ball and socket because helical axes representing anatomical motions such as flexion-extension, radio-ulnar deviation, dart throwers, and antidart throwers, were located at distances up to 4.5mm from the PvP. Although the best-fit PvP did not yield a single center of rotation, it was still consistently found within the proximal pole of the capitate, and rms errors of the best-fit PvP calculation were on the order of 2mm. Therefore, the ball-and-socket model of the wrist joint center using the best-fit PvP is appropriate when considering gross motion of the hand with respect to the forearm such as in optical motion capture models. However, the ball-and-socket model of the wrist is an insufficient description of the complex motion of the capitate with respect to the radius. These findings may aid in the design of wrist external fixation and orthotics.

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.

The effect of individual isometric muscle loading on the alignment of the base of the thumb metacarpal: a cadaveric study

2015 ◽  
Vol 41 (4) ◽  
pp. 374-379 ◽  
Author(s):  
N. Mobargha ◽  
M. Esplugas ◽  
M. Garcia-Elias ◽  
A. Lluch ◽  
K. Megerle ◽  
...  
Keyword(s):  
Motion Tracking ◽  
Middle Finger ◽  
First Dorsal Interosseous ◽  
Thumb Carpometacarpal Joint ◽  
Distal Migration ◽  
First Dorsal Interosseous Muscle ◽  
Muscle Loading ◽  
Thumb Carpometacarpal ◽  
Isometric Muscle ◽  
Dorsal Interosseous Muscle

Stability of the thumb carpometacarpal joint relies upon equilibrium between its ligaments, muscular support and joint congruity. We wanted to identify the muscles important in preventing or increasing dorsoradial subluxation of this joint. In ten cadaveric hands, a Fastrak® motion tracking device was used to assess the effects of individual isometric muscle loading on the base of the thumb metacarpal relative to the radius and to the base of the middle finger metacarpal. We found that the first dorsal interosseous muscle caused the least dorsoradial translation and highest distal migration of the base of the first metacarpal, whereas abductor pollicis longus was the primary destabilizer, increasing dorsoradial misalignment. The findings show different impacts of these muscles on joint alignment and stability, which suggests that treatment should be targeted to enhance the action of the primary stabilizing muscle, the first dorsal interosseous muscle.

scholarly journals Activation of individual extrinsic thumb muscles and compartments of extrinsic finger muscles

2013 ◽  
Vol 110 (6) ◽  
pp. 1385-1392 ◽  
Author(s):  
J. Alexander Birdwell ◽  
Levi J. Hargrove ◽  
Todd A. Kuiken ◽  
Richard F. ff. Weir
Keyword(s):  
Neural Control ◽  
Muscular Activity ◽  
Middle Finger ◽  
The Other ◽  
Flexor Digitorum Profundus ◽  
Human Hand ◽  
Activity Levels ◽  
Extensor Pollicis Longus ◽  
Flexor Digitorum ◽  
Different Levels

Mechanical and neurological couplings exist between musculotendon units of the human hand and digits. Studies have begun to understand how these muscles interact when accomplishing everyday tasks, but there are still unanswered questions regarding the control limitations of individual muscles. Using intramuscular electromyographic (EMG) electrodes, this study examined subjects' ability to individually initiate and sustain three levels of normalized muscular activity in the index and middle finger muscle compartments of extensor digitorum communis (EDC), flexor digitorum profundus (FDP), and flexor digitorum superficialis (FDS), as well as the extrinsic thumb muscles abductor pollicis longus (APL), extensor pollicis brevis (EPB), extensor pollicis longus (EPL), and flexor pollicis longus (FPL). The index and middle finger compartments each sustained activations with significantly different levels of coactivity from the other finger muscle compartments. The middle finger compartment of EDC was the exception. Only two extrinsic thumb muscles, EPL and FPL, were capable of sustaining individual activations from the other thumb muscles, at all tested activity levels. Activation of APL was achieved at 20 and 30% MVC activity levels with significantly different levels of coactivity. Activation of EPB elicited coactivity levels from EPL and APL that were not significantly different. These results suggest that most finger muscle compartments receive unique motor commands, but of the four thumb muscles, only EPL and FPL were capable of individually activating. This work is encouraging for the neural control of prosthetic limbs because these muscles and compartments may potentially serve as additional user inputs to command prostheses.

scholarly journals Comparable behaviour of ring and little fingers due to an artificial reduction in thumb contribution to hold objects

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e9962
Author(s):  
Banuvathy Rajakumar ◽  
Varadhan SKM
Keyword(s):  
Normal Force ◽  
Safety Margin ◽  
Ring Finger ◽  
Middle Finger ◽  
Human Hand ◽  
Mechanical Advantage ◽  
Free Condition ◽  
Normal Forces ◽  
Fixed Condition ◽  
Little Finger

Background The human hand plays a crucial role in accomplishing activities of daily living. The contribution of each finger in the human hand is remarkably unique in establishing object stabilization. According to the mechanical advantage hypothesis, the little finger tends to exert a greater normal force than the ring finger during a supination moment production task to stabilize the object. Similarly, during pronation, the index finger produces more normal force when compared with the middle finger. Hence, the central nervous system employs the peripheral fingers for torque generation to establish the equilibrium as they have a mechanical advantage of longer moment arms for normal force. In our study, we tested whether the mechanical advantage hypothesis is supported in a task in which the contribution of thumb was artificially reduced. We also computed the safety margin of the individual fingers and thumb. Methodology Fifteen participants used five-finger prismatic precision grip to hold a custom-built handle with a vertical railing on the thumb side. A slider platform was placed on the railing such that the thumb sensor could move either up or down. There were two experimental conditions. In the “Fixed” condition, the slider was mechanically fixed, and hence the thumb sensor could not move. In the “Free” condition, the slider platform on which the thumb sensor was placed could freely move. In both conditions, the instruction was to grasp and hold the handle (and the platform) in static equilibrium. We recorded tangential and normal forces of all the fingers. Results The distribution of fingertip forces and moments changed depending on whether the thumb platform was movable (or not). In the free condition, the drop in the tangential force of thumb was counteracted by an increase in the normal force of the ring and little finger. Critically, the normal forces of the ring and little finger were statistically equivalent. The safety margin of the index and middle finger did not show a significant drop in the free condition when compared to fixed condition. Conclusion We conclude that our results does not support the mechanical advantage hypothesis at least for the specific mechanical task considered in our study. In the free condition, the normal force of little finger was comparable to the normal force of the ring finger. Also, the safety margin of the thumb and ring finger increased to prevent slipping of the thumb platform and to maintain the handle in static equilibrium during the free condition. However, the rise in the safety margin of the ring finger was not compensated by a drop in the safety margin of the index and middle finger.

The Control Method for the Robot Hand Based on the Fuzzy Theory

1992 ◽  
Vol 4 (4) ◽  
pp. 262-267 ◽  
Author(s):  
Masafumi Uchida ◽  
◽  
Hideto Ide
Keyword(s):  
Control Method ◽  
Index Finger ◽  
Fuzzy Theory ◽  
Middle Finger ◽  
Human Hand ◽  
Robot Hand ◽  
Production Rules ◽  
Living Body ◽  
Physical Conditions ◽  
State Of Mind

By moving muscles, the myogenic potential (Electromyogram: EMG) is observed on the surface of the living body. It is considered that the EMG is useful for controlling a robot hand. However, the EMG depends on physical conditions, the state of mind and so on. So, the original EMG will be not used for controlling the robot hand directly. In this study, it is considered that the EMG relating the motion of the human hand is analyzed by the fuzzy theory for making the robot hand performs the same motion as the human hand. EMG were measured under the following conditions. (1) opening the hand, (2) bending the thumb, (3) bending the middle finger, (4) bending the index finger, (5) closing the hand, (6) not move. Six production rules were made with fuzzificate data resulted from fourier transforming the EMG (30-band 1/3 octave analysis). Also the EMG measured by experimental motion of the human hand was transformed into the fuzzificate date. Rates of recognitions were calculated in comparison with the six production rules and the experimental data. And one production rule with highest rate of recognition was used for recognition of movement of the human hand in the computer. From the experimental results, about 90% of movement were recognized by the computer. The results were applied to control the robot hand.

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