Development of normative data for cylindrical grasp pressure

Normative data of grasp strength (GS) are commonly used in working and clinical environments. Squeezing two parallel bars of a handgrip instrument is a common method to measure GS. These instruments require the use of hook grasp position which differentiates from the other types of power grasp in terms of inclusion of the thumb. Therefore, strength performance measured with these types of dynamometers cannot be generalizable to the other types of power grasp. Although several studies have been conducted to form normative data of hook and spherical grasp strengths, a satisfactory cylindrical grasp strength norm has not been reported yet. The measurement of grasp pressure (GP) is another way of establishing the grasping capabilities of the hand and the preferred method for fragile and weak hands. The purposes of the study were to develop normative data of cylindrical GP in a healthy population and to analyze the changes in the means according to physical demands of the subjects’ jobs. 770 healthy subjects (382 females, 388 males) were found to be eligible to participate in the study. A custom-made adapted sphygmomanometer having a cylindrical air-filled bag was used to measure GP. Occupational categories of the subjects were determined based on the classification in the Dictionary of Occupational Titles. The subjects were accommodated to 12 age groups per gender of five-year intervals. The mean GP of the male subjects were higher than those of female subjects in each age group. There were significant differences between the dominant and non-dominant hands in both sexes. Subjects older than 70 years achieved the lowest values. The changes of the means over age were in compliance with the curvilinear function. Only age factor was found to be resulted in significant differences in GP means at both hands of the subjects. The minimum GP means were in the “sedentary” category at both sexes (F: 225, M: 315 mmHg in the dominant hands). Male subjects in the “very heavy” category produced the highest test means (M: 371 mmHg). Further analysis on 52 male subjects demonstrated that hand length, hand circumference and palm length had the highest correlations with GP scores in sequence.

Relevance to industry

Development of hand strength norms for a particular type of grasping is necessary for ergonomic evaluations and design purposes. By using this data, it is possible to estimate the relative load levels on a worker. Hand strength measurements are also important in determining the workers at risk and diagnosing some musculoskeletal problems.     

A biomimetic reach and grasp approach for mechanical hands

Reach and grasp are the two key functions of human prehension. The Central Nervous System controls these two functions in a separate but interdependent way. The choice between different solutions to reach and grasp an object–provided by multiple and redundant degrees of freedom (dof)–depends both on the properties and on the use (affordance) of the object to be manipulated. This same control paradigm, i.e. subdivision of prehension into reach and grasp as well as the corresponding multimodal (sensory/motor) information fusion schemes, can also be applied to a mechanical hand carried by a robotic arm. The robotic arm will then be responsible for positioning the hand with respect to the object, and the hand will then grasp and manipulate the object. In this article, we present a biomimetic sensory–motor control scheme in the aim of providing an object-dependent and intelligent reach and grasp ability to such systems. The proposed model is based on a multi-network architecture which incorporates multiple Matching Units trained by a statistical learning algorithm (LWPR). Matching Units perform a multimodal signal integration by correlating sensory and motor information analogous to that observed in cerebral neuronal networks. The simulated network of multiple Matching Units provided estimations of object-dependent 5-finger grasp configurations with endpoint positional errors in the order of a few millimeters. For validation, these estimations were then applied to the control of movement kinematics on an experimental robot composed of a 6 dof robot arm carrying a 16 dof mechanical 4-finger hand. Precision of the kinematics control was such that successful reach, grasp and lift was obtained in all the tests.     

OCOG: A common grasp computation algorithm for a set of planar objects

This paper addresses the problem of defining a simple End-Effector design for a robotic arm that is able to grasp a given set of planar objects. The OCOG (Objects COmmon Grasp search) algorithm proposed in this paper searches for a common grasp over the set of objects mapping all possible grasps for each object that satisfy force closure and quality criteria by taking into account the external wrenches (forces and torque) applied to the object. The mapped grasps are represented by feature vectors in a high-dimensional space. This feature vector describes the design of the gripper. A database is generated for all possible grasps for each object in the feature vector space. A search algorithm is then used for intersecting all possible grasps over all parts and finding a common grasp suitable for all objects. The search algorithm utilizes the kd-tree index structure for representing the database of the sets of feature vectors. The kd-tree structure enables an efficient and low cost nearest-neighbor search for common vectors between the sets. Each common vector found (feature vector) is the grasp configuration for a group of objects, which implies the future end-effector design. The final step classifies the grasps found to subsets of the objects, according to the common vectors found. Simulations and experiments are presented for four objects to validate the feasibility of the proposed algorithm. The algorithm will be useful for standardization of end-effector design and reducing its engineering time.     

Age differences in the control of a precision reach to grasp task within a desktop virtual environment

The purpose of this experiment is to investigate the fine motor performance of young and older adults on a reach to grasp task in a desktop virtual environment with increasing precision requirements. Aging brings about potential loss of an individual's function due to disease, injury, or the degenerative nature of aging itself. Three-dimensional virtual environments have been identified as systems with good potential to ameliorate such problems in older individuals, and precise fine motor skills represent an important class of functional skills. Two groups of participants (Young, n=10, mean age 21.3 years, range 20–24, senior, n=10, mean age 70.7 years, range 60–85) performed a reach to grasp in a desktop virtual environment with simple, low contrast graphics. Results indicate that visual feedback of the hand for sensory guidance of movement did not improve motor performance for either group, and that as precision requirements of the task increased, age group differences in movement time and peak grasp aperture also increased. These findings extend the literature on age group differences in human motor control across the lifespan and differ from previous studies which showed presence of visual feedback of the hand improved motor performance in young adults. Differences in luminance contrast levels in past studies and the current one suggest that control over this feature of the visual scene is an important design consideration for all end-users and warrants additional investigation. Additional recommendations for age-specific design of three dimensional user interfaces include usage of tangibles that are sufficient in size to limit detrimental effects for older adults.     

Contributions and co-ordination of individual fingers in multiple finger prehension

The contributions and co-ordination of external ringer grip forces were examined during a lifting task with a precision grip using multiple fingers. The subjects ( n = 10) lifted a force transducer-equipped grip apparatus. Grip force from each of the five fingers was continuously measured under different object weight (200 g, 400 g, and 800 g) and surface structure (plastic and sandpaper) conditions. The effect of five-, four-, and three-finger grip modes was also examined. It was found that variation of object weight or surface friction resulted in change of the total grip force magnitude; the largest change in finger force, was that for the index finger, followed by the middle, ring, and little fingers. Percentage contribution of static grip force to the total grip force for the index, middle, ring, and little fingers was 420%, 27·4%, 17·6% and 12·9%, respectively. These values were fairly constant for all object weight conditions, as well as for all surface friction conditions, suggesting that all individual finger force adjustments for light loads less than 800 g are controlled comprehensively simply by using a single common scaling value. A higher surface friction provided faster lifting initiation and required lesser grip force exertion, indicating advantageous effect of a non-slippery surface over a slippery surface. The results indicate that nearly 40% force reduction can be obtained when a non-slippery surface is used. Variation in grip mode changed the total grip force, i.e., the fewer the number of fingers, the greater the total grip force. The percent value of static grip force for the index, middle, and ring fingers in the four-finger grip mode was 42·7%, 32·5%, and 24·7%, respectively, and that for the index and middle fingers in the three-finger grip mode was 43·0% and 56·9%, respectively. Therefore, the grip mode was found to influence the force contributions of the middle and ring fingers, but not of the index finger.     

A multi-view vision-based hand motion capturing system

Vision-based hand motion capturing approaches play a critical role in human computer interface owing to its non-invasiveness, cost effectiveness, and user friendliness. This work presents a multi-view vision-based method to capture hand motion. A 3-D hand model with structural and kinematical constraints is developed to ensure that the proposed hand model behaves similar to an ordinary human hand. Human hand motion in a high degree of freedom space is estimated by developing a separable state based particle filtering (SSBPF) method to track the finger motion. By integrating different features, including silhouette, Chamfer distance, and depth map in different view angles, the proposed motion tracking system can capture the hand motion parameter effectively and solve the self-occlusion problem of the finger motion. Experimental results indicate that the hand joint angle estimation generates an average error of 11°.     

Virtual surfaces and the influence of cues to surface shape on grasp

This research compared grasps to real surfaces with grasps to virtual surfaces, and used virtual surfaces to examine the role of cues to surface shape in grasp. The first experiment investigated the kinematics of overhand grasps to real and virtual objects. The results showed that, compared with grasps to real surfaces, grasps to virtual objects were different in the deceleration phase of the grasp movement and were more variable in their endpoint position. The second experiment used several measures to examine the relationship between the visual perception of a surface and the decision to grasp the surface with either an over-or underhand grasp. It was found that visual perception of the surface was consistent with the grasping decision. The third experiment used virtual surfaces to examine how the removal of visual cues to shape affected the decision to switch from over- to underhand grasp. Results showed that the orientation at which the decision switched was dependent on the visual information content. Overall, the results showed that subtle differences existed between the reach to grasp movements towards real and virtual surfaces and that the decision to choose between grasp types was dependent on the visual information used to depict the virtual surface. These results are discussed in relation to the design and use of input devices to enable manipulation of three-dimensional objects in virtual worlds.     

A neural model for the integration of stereopsis and motion parallax in structure from motion

We introduce a model for the computation of structure from motion based on the physiology of visual cortical areas MT and MST. The model assumes that the perception of depth from motion is related to the firing of a subset of MT neurons tuned to both velocity and disparity. The model's MT neurons are connected to each other laterally to form modulatory receptive-field surrounds that are gated by feedback connections from area MST. This allows the building up of a depth map from motion in area MT, even in absence of disparity in the input. Depth maps from motion and from stereo are combined by a weighted average at a final stage. The model's predictions for the interaction between motion and stereo cues agree with previous psychophysical data, both when the cues are consistent with each other or when they are contradictory. In particular, the model shows nonlinearities as a result of early interactions between motion and stereo before their depth maps are averaged. The two cues interact in a way that represents an alternative to the “modified weak fusion” model of depth–cue combination.     

A heuristic approach to automatic grasp planning for a 3-fingered hand

This paper presents the core of a software system able to determine a good grasp configuration on 3D objects for a three-fingered hand. The grasp planning problem has been studied considering both the constraints due to the stability and accessibility conditions, and the ones related to functionality. Physical, geometrical, spatial and task-related knowledge for solving the grasp planning problem have been properly modelled to support a heuristic-based reasoning process. A series of heuristic rules and geometric tests are used to scan the solution space, searching for a good grasp. In fact, when considering the three-dimensional case, a purely analytical and exhaustive approach appears too complex because of the dimension of the search space. This approach results in an incremental and modular model of grasp reasoning, that has been implemented using the Flex expert system shell. This work has been developed and demonstrated within the Esprit 2 project CIM-PLATO No. 2202.     

基于加速度计的手指运动姿态检测

针对动态测量手指关节角度的需要,设计了一种基于MEMS加速度计的手指运动姿态检测方法。在该方法中,通过固定于手指上的三轴加速度计ADXL330的各个敏感轴感受到的重力加速度分量的大小来检测手指的关节角度。为了验证该方法的可行性,设计了一步进电机控制的能在竖直平面内转动的装置,通过同步检测传感器的输出和电机转动的角度,评估传感器在动态条件下的测量精度,结果表明:在动态条件下,其绝对误差为1°～2.5°,相对误差为3%～6%。在此基础上,将传感器用于测量手指关节的运动姿态,采集手指敲击键盘时传感器的输出,通过数据处理获得食指MCP关节、PIP关节和DIP关节随时间的变化关系。实验结果表明:加速度计可以有效地检测手指的运动姿态。     

Effects of age and gender on maximum voluntary range of motion of the upper body joints

The maximum voluntary range of motion (ROM) of the major joints of the upper body was studied in a seated position and compared between young and elderly subjects. A total of 41 subjects (22 young male and female subjects aged 25 to 35 years, 19 elderly male and female subjects aged 65 to 80 years) took part in the experiment. In total, 13 maximum voluntary joint motions were performed by each subject. Age was found to have a non-uniform effect on the ROM of the joints investigated in this study. Its effect on ROM was joint specific and motion specific. The highest loss in ROM was observed in the neck and trunk, especially for neck extension, lateral flexion and axial rotation as well as for trunk lateral flexion and axial rotation. No significant age differences were observed in the elbow and wrist joint ROMs. The effect of gender on joint ROM was much weaker than that of age. Only four among the 26 joint ROMs investigated in this study were significantly different between the two gender groups.     

Maximum reach envelope for the seated and standing male and female for industrial workstation design

Maximum reach envelopes for the 5th, 50th and 95th percentile reach lengths of males and females in seated and standing work positions were determined. The use of a computerized potentiometric measurement system permitted functional reach measurement in 15 min for each subject. The measurement system captured reach endpoints in a dynamic mode while the subjects were describing their maximum reach envelopes. An unbiased estimate of the true reach distances was made through a systematic computerized data averaging process. The maximum reach envelope for the standing position was significantly (p < 0.05) larger than the corresponding measure in the seated position for both the males and females. The average reach length of the female was 13.5% smaller than that for the corresponding male. Potential applications of this research include designs of industrial workstations, equipment, tools and products.     

加移动因子的C-V模型

在变分水平集方法中,C-V模型的优点之一是能够提取以非梯度形式定义的图像边界,然而,在提取该类型边界时,模型仅考虑了图像各区域的均值信息而没有考虑图像的局部信息,因此尽管C-V模型能够得到渐进型边界图像的分割结果,但是存在分割误差。将移动因子引入到C-V模型以解决上述问题。其中移动因子定义为图像局部凸凹性的函数,通过该因子可以调整模型0-水平面的高度,进而使得解平面与目标所在平面更加接近或重合,以达到消除分割误差的目的。文中给出了偏微分形式的模型,并通过实验验证了模型的有效性。     

基于可分级视频编码的双向双维运动信息可分级*

为进一步提高基于一种运动信息可分级模型的可分级视频编码的编码效率,减小运动信息可分级的最低码率限制,对该运动可分级模型的二维多向性进行了具体研究与改进,更新了运动估计的流程,提出了多向上的两个运动可分级维度的运动分级等级一致性原则以及二维数据的渐进式存储存取结构,从而实现了二维多向上的运动可分级。实验测试结果证明该二维多向的运动信息模型优于不可分级的运动信息,能有效提高可分级视频编码系统的效率。     

ABSTRACTING SERVICE

The accuracy with which subjects can judge the coordinates of a mark within an uncalibrated square cell was recorded. A sample of military pilots was able to report both coordinates to the nearest tenth of a cell dimension in approximately 88 per cent of the cases. The number of errors exceeding one-tenth was negligible.     

A pilot study of a method for assessing the reach capability of wheelchair users for safety belt design

A method was developed to assess the reach capability of people seated in wheelchairs for purposes of establishing design and placement requirements for safety belts used by vehicle occupants who are seated in wheelchairs. The method uses simple technology and is intended to be readily implemented in the field. Participants use a marker to draw their acceptable reach zone on a vertical surface placed adjacent to the wheelchair. A pilot study with 10 wheelchair users showed that the method generates easily interpreted data quickly. Even with a small number of participants, the results from the pilot study provide useful information for designers of restraint systems for wheelchair-seated vehicle occupants.     

A non-linear model of shape and motion for tracking finger spelt American sign language

This work presents a piecewise linear approximation to non-linear Point Distribution Models for modelling the human hand. The work utilises the natural segmentation of shape space, inherent to the technique, to apply temporal constraints, which can be used with CONDENSATION to support multiple hypotheses and discontinuous jumps within shape space. This paper presents a novel method by which the one-state transitions of the English Language are projected into shape space for tracking and model prediction using an HMM like approach. The paper demonstrates that this model of motion provides superior results to that of other tracking approaches.     

3D fingerprint reconstruction system using feature correspondences and prior estimated finger model

The paper studies a 3D fingerprint reconstruction technique based on multi-view touchless fingerprint images. This technique offers a solution for 3D fingerprint image generation and application when only multi-view 2D images are available. However, the difficulties and stresses of 3D fingerprint reconstruction are the establishment of feature correspondences based on 2D touchless fingerprint images and the estimation of the finger shape model. In this paper, several popular used features, such as scale invariant feature transformation (SIFT) feature, ridge feature and minutiae, are employed for correspondences establishment. To extract these fingerprint features accurately, an improved fingerprint enhancement method has been proposed by polishing orientation and ridge frequency maps according to the characteristics of 2D touchless fingerprint images. Therefore, correspondences can be established by adopting hierarchical fingerprint matching approaches. Through an analysis of 440 3D point cloud finger data (220 fingers, 2 pictures each) collected by a 3D scanning technique, i.e., the structured light illumination (SLI) method, the finger shape model is estimated. It is found that the binary quadratic function is more suitable for the finger shape model than the other mixed model tested in this paper. In our experiments, the reconstruction accuracy is illustrated by constructing a cylinder. Furthermore, results obtained from different fingerprint feature correspondences are analyzed and compared to show which features are more suitable for 3D fingerprint images generation.     

The three-dimensional measurement of unconstrained motion using a model-matching method

The measurement of motion is a basic technique for the quantitative mechanical analysis of human movement. However, previous methods of motion measurement using goniometry and surface markers have several associated problems: goniometers constrain human motion; and surface markers are missed, etc. To resolve these problems, a new technique of motion measurement using image processing is proposed. In this method, movements of the whole body are captured as image information, and a geometric model of a human body is fitted onto the contours of the image sequences. The joint angles are then estimated from the model. Usually, every segment has to be coloured separately so as to fit the geometric model automatically into the images; furthermore, this takes a very long time to process. Therefore, we reduced the processing time using the information in the overlap area between the models and images, instead of contour information. We estimated the joint angles of hidden segments with the grey scale image information. Thus there is no need to colour segments and attach surface markers; and unconstrained motion can be measured. Using the method developed, three-dimensional motion of the fingers including 21 segments was measured in 3–5?min per frame by a personal computer. The errors are 2° maximally.