Estimation of the Abduction/Adduction Movement of the Metacarpophalangeal Joint of the Thumb

Thumb opposition is essential for grasping, and involves the flexion and abduction of the carpometacarpal and metacarpophalangeal joints of the thumb. The high number of degrees of freedom of the thumb in a fairly small space makes the in vivo recording of its kinematics a challenging task. For this reason, along with the very limited independence of the abduction movement of the metacarpophalangeal joint, many devices do not implement sensors to measure such movement, which may lead to important implications in terms of the accuracy of thumb models. The aims of this work are to examine the correlation between thumb joints and to obtain an equation that allows thumb metacarpophalangeal abduction/adduction movement to be estimated from the other joint motions of the thumb, during the commonest grasps used during activities of daily living and in free movement. The correlation analysis shows that metacarpophalangeal abduction/adduction movement can be expressed mainly from carpometacarpal joint movements. The model thus obtained presents a low estimation error (6.29°), with no significant differences between grasps. The results could benefit most fields that do not typically include this joint movement, such as virtual reality, teleoperation, 3D modeling, prostheses, and exoskeletons

A Systematic Review of EMG Applications for the Characterization of Forearm and Hand Muscle Activity during Activities of Daily Living: Results, Challenges, and Open Issues

The role of the hand is crucial for the performance of activities of daily living, thereby ensuring a full and autonomous life. Its motion is controlled by a complex musculoskeletal system of approximately 38 muscles. Therefore, measuring and interpreting the muscle activation signals that drive hand motion is of great importance in many scientific domains, such as neuroscience, rehabilitation, physiotherapy, robotics, prosthetics, and biomechanics. Electromyography (EMG) can be used to carry out the neuromuscular characterization, but it is cumbersome because of the complexity of the musculoskeletal system of the forearm and hand. This paper reviews the main studies in which EMG has been applied to characterize the muscle activity of the forearm and hand during activities of daily living, with special attention to muscle synergies, which are thought to be used by the nervous system to simplify the control of the numerous muscles by actuating them in task-relevant subgroups. The state of the art of the current results are presented, which may help to guide and foster progress in many scientific domains. Furthermore, the most important challenges and open issues are identified in order to achieve a better understanding of human hand behavior, improve rehabilitation protocols, more intuitive control of prostheses, and more realistic biomechanical models

Synergy-Based Sensor Reduction for Recording the Whole Hand Kinematics

Simultaneous measurement of the kinematics of all hand segments is cumbersome due to sensor placement constraints, occlusions, and environmental disturbances. The aim of this study is to reduce the number of sensors required by using kinematic synergies, which are considered the basic building blocks underlying hand motions. Synergies were identified from the public KIN-MUS UJI database (22 subjects, 26 representative daily activities). Ten synergies per subject were extracted as the principal components explaining at least 95% of the total variance of the angles recorded across all tasks. The 220 resulting synergies were clustered, and candidate angles for estimating the remaining angles were obtained from these groups. Different combinations of candidates were tested and the one providing the lowest error was selected, its goodness being evaluated against kinematic data from another dataset (KINE-ADL BE-UJI). Consequently, the original 16 joint angles were reduced to eight: carpometacarpal flexion and abduction of thumb, metacarpophalangeal and interphalangeal flexion of thumb, proximal interphalangeal flexion of index and ring fingers, metacarpophalangeal flexion of ring finger, and palmar arch. Average estimation errors across joints were below 10% of the range of motion of each joint angle for all the activities. Across activities, errors ranged between 3.1% and 16.8%

Sharing of hand kinematic synergies across subjects in daily living activities

The motor system is hypothesised to use kinematic synergies to simplify hand control. Recent studies suggest that there is a large set of synergies, sparse in degrees of freedom, shared across subjects, so that each subject performs each action with a sparse combination of synergies. Identifying how synergies are shared across subjects can help in prostheses design, in clinical decision-making or in rehabilitation. Subject-specific synergies of healthy subjects performing a wide number of representative daily living activities were obtained through principal component analysis. To make synergies comparable between subjects and tasks, the hand kinematics data were scaled using normative range of motion data. To obtain synergies sparse in degrees of freedom a rotation method that maximizes the sum of the variances of the squared loadings was applied. Resulting synergies were clustered and each cluster was characterized by a core synergy and different indexes (prevalence, relevance for function and within-cluster synergy similarity), substantiating the sparsity of synergies. The first two core synergies represent finger flexion and were present in all subjects. The remaining core synergies represent coordination of the thumb joints, thumb-index joints, palmar arching or fingers adduction, and were employed by subjects in different combinations, thus revealing different subject-specific strategies

Applying New Educational Methodologies in Overcrowded Groups: Experiences in Basic Mechanics

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Validity of a simple videogrammetric method to measure the movement of all hand segments for clinical purposes

Hand movement measurement is important in clinical, ergonomics and biomechanical fields. Videogrammetric techniques allow the measurement of hand movement without interfering the natural hand behaviour. However, an accurate measurement of the hand movement requires the use of a high number of markers, which limits its applicability for the clinical practice (60 markers would be needed for hand and wrist). In this work, a simple method that uses a reduced number of markers (29), based on a simplified kinematic model of the hand, is proposed and evaluated. A set of experiments has been performed to evaluate the errors associated to the kinematic simplification, together with the evaluation of its accuracy, repeatability and reproducibility. The global error attributed to the kinematic simplification was 6.68º. The method has small errors in repeatability and reproducibility (3.43º and 4.23º, respectively) and shows no statistically significant difference with the use of electronic goniometers. The relevance of the work lies in the ability of measuring all degrees of freedom of the hand with a reduced number of markers without interfering the natural hand behaviour, which makes it suitable for its use in clinical applications, as well as for ergonomic and biomechanical purposes

The BE-UJI hand function activity set: a reduced set of activities for the evaluation of the healthy and pathological hand

Background Hand kinematics during hand function tests based on the performance of activities of daily living (ADLs) can provide objective data to determine patients’ functional loss. However, they are rarely used during clinical assessments because of their long duration. Starting with the 20 Sollerman Hand Function Test (SHFT) tasks, we propose identifying a reduced set of ADLs that provides similar kinematic information to the original full set in terms of synergies, ranges of motion and velocities. Methods We followed an iterative method with the kinematics of 16 hand joints while performing the 20 ADLs of the SHFT. For each subject, ADLs were ordered according to their influence on the synergies obtained by means of a principal component analysis, the minimum number of ADLs that represented the original kinematic synergies (maximum angle of 30° between synergies), and the maintained ranges of joint movements (85% of the original ones) were selected for each subject. The set of the most frequently selected ADLs was verified to be representative of the SHFT ADLs in terms of motion strategies, ranges of motion and joint velocities when considering healthy subjects and Hand Osteoarthritis patients. Results A set of 10 tasks, the BE‑UJI activity set, was identified by ensuring a certain (minimum) similarity in synergy (maximum mean angle between synergies of 25.5°), functional joint ranges (maximum differences of 10°) and joint velocities (maximum differences of 15°/s). The obtained tasks were: pick up coins from purses, lift wooden cubes, pick up nuts and turn them, write with a pen, cut with a knife, lift a telephone, unscrew jar lids and pour water from a cup, a jar and a Pure‑Pak. These activities guarantee using the seven commonest handgrips in ADLs. Conclusion The BE‑UJI activity set for the hand function assessment can be used to obtain quantitative data in clinics as an alternative to the SHFT. It reduces the test time and allows clinicians to obtain objective kinematic data of the motor strategies, ranges of motion and joint velocities used by patients

Scalability of the Muscular Action in a Parametric 3D Model of the Index Finger

A method for scaling the muscle action is proposed and used to achieve a 3D inverse dynamic model of the human finger with all its components scalable. This method is based on scaling the PCSA (physiological cross-sectional area) in a Hill muscle model. Different anthropometric parameters and maximal grip force data have been measured and their correlations have been analysed and used for scaling the PCSA of each muscle. A linear relationship between the normalised PCSA and the product of the length and breadth of the hand has been finally used for scaling, with a slope of 0.01315 cm-2, with the length and breadth of the hand expressed in centimetres. The parametric muscle model has been included in a parametric finger model previously developed by the authors, and it has been validated reproducing the results of an experiment in which subjects from different population groups exerted maximal voluntary forces with their index finger in a controlled postur

Medición del movimiento de todos los segmentos de la mano mediante videogrametría

Comunicación presentada en el XIX Congreso Nacional de Ingeniería Mecánica, celebrado en Castellón, del 14 al 16 de noviembre de 2012La medición del movimiento de la mano es importante en muy diversos campos, a la vez que compleja por el elevado número de grados de libertad que posee. Generalmente es deseable que la técnica de medición no interfiera en el normal desarrollo de las actividades a realizar por la mano, siendo una buena alternativa la captura de movimiento a partir de imágenes de video y uso de marcadores pasivos (o videogrametría). Estas técnicas se han usado ampliamente en el análisis de la marcha, pero su aplicación al análisis del movimiento de la mano es todavía escasa. La mayor parte de los trabajos de la literatura presentan su uso sólo para un dedo, o realizan grandes simplificaciones cinemáticas. En este trabajo se describe un método para la medición de los movimientos de todos los segmentos de la mano a partir del registro de imágenes de video y el uso de 29 marcadores reflectantes, seleccionados para definir unos sistemas de referencia asociados a cada segmento, que se utilizan para calcular los ángulos de rotación entre cada par de segmentos consecutivos. Se ha tenido especial cuidado en el significado fisiológico de estos ángulos de rotación (25 en total). Así, el movimiento de la mano se describe con ángulos de flexión-extensión en todas las articulaciones interfalángicas y en las metacarpocarpianas de los dedos anular y meñique, y con ángulos de flexión-extensión y de abducción-aducción en todas las articulaciones metacarpofalángicas, en la metacarpocarpiana del pulgar y también en la muñeca. Para analizar la repetibilidad y factibilidad del método propuesto, se ha desarrollado un experimento que ha consistido en el agarre de un mismo cono por cinco sujetos distintos. Cada sujeto ha realizado tres repeticiones diferentes del agarre en cada una de las dos sesiones en que se le han colocado los marcadores y se ha realizado su seguimiento. La técnica ha demostrado ser factible para el estudio del movimiento de la mano durante la realización de agarres, con un error de repetibilidad global de 2.3º

Hand Kinematics Characterization While Performing Activities of Daily Living Through Kinematics Reduction

Improving the understanding of hand kinematics during the performance of activities of daily living may help improve the control of hand prostheses and hand function assessment. This work identifies sparse synergies (each degree of freedom is present mainly in only one synergy), representative of the global population, with emphasis in unveiling the coordination of joints with small range of motion (palmar arching and fingers abduction). The study is the most complete study described in the literature till now, involving 22 healthy subjects and 26 representative day-to-day life activities. Principal component analysis was used to reduce the original 16 angles recorded with an instrumented glove. Five synergies explained 75% of total variance: closeness (coordinated flexion and abduction of metacarpophalangeal finger joints), digit arching (flexion of proximal interphalangeal joints), palmar-thumb coordination (coordination of palmar arching and thumb carpometacarpal flexion), thumb opposition , and thumb arch . The temporal evolution of these synergies is provided during reaching per intended grasp and during manipulation per specific task, which could be used as normative patterns for the global population. Reaching has been observed to require the modulation of closeness , digit arch and thumb opposition synergies, with different control patterns per grasp. All the synergies are very important during manipulation and need to be modulated for all the tasks. Finally, groups of tasks with similar kinematic requirements in terms of synergies have been identified, which could benefit the selection of tasks for rehabilitation and hand function assessments