Comparison of three local frame definitions for the kinematic analysis of the fingers and the wrist

The Evaluation of a Flexor Digitorum Profundus-to-Volar Plate Zone I Repair Versus Button Repair: An In Vitro Biomechanics Study

PURPOSE

The purpose of the study was to evaluate joint kinematics and tendon work of flexion (WOF) following a flexor digitorum profundus (FDP)-to-volar plate (VP) repair technique relative to a pullout button for zone I flexor tendon injuries.

METHODS

Fourteen digits were tested using an in vitro active finger motion simulator under 3 repaired conditions following a simulated zone I avulsion: button, FDP-VP, and "no slack" FDP-VP (corrected for additional VP length). Outcome metrics included active joint range of motion (ROM), fingertip strength, FDP and flexor digitorum superficialis tensile loads, and WOF.

RESULTS

The button and FDP-VP techniques restored WOF to the intact condition for FDP and flexor digitorum superficialis. All repairs restored distal interphalangeal joint ROM and kinematics to the intact condition. Similarly, all repairs restored WOF; however, the "no slack" FDP-VP significantly increased WOF by 10% to 12% over the simple FDP-VP repair. The button technique had similar fingertip strength to the intact condition, whereas the FDP-VP repairs significantly reduced peak fingertip strength from intact, albeit only 1-2 N compared with the button repair.

CONCLUSION

In this in vitro cadaveric model, the button and FDP-VP techniques restored WOF and ROM to within intact levels, with no difference between these repairs in all measured outcome metrics.

CLINICAL RELEVANCE

Based on its initial strength and its equal biomechanical performance compared with the button repair, the FDP-VP technique may be a viable option for treating FDP avulsions.

Reliability, accuracy, and minimal detectable difference of a mixed concept marker set for finger kinematic evaluation

The study of finger biomechanics requires special tools for accurately recording finger joint data. A marker set to evaluate finger postures during activities of daily living is needed to understand finger biomechanics in order to improve prosthesis design and clinical interventions. The purpose of this study was to evaluate the reliability of a proposed hand marker set (the Warwick marker set) to capture finger kinematics using motion capture. The marker set consisted of the application of two and three marker clusters to the fingers of twelve participants who participated in the tests across two sessions. Calibration markers were applied using a custom palpation technique. Each participant performed a series of range of motion movements and held a set of objects. Intra and inter-session reliability was calculated as well as Standard Error of Measurement (SEM) and Minimal Detectable Difference (MDD). The findings showed varying levels of intra- and inter-session reliability, ranging from poor to excellent. The SEM and MDD values were lower for the intra-session range of motion and grasp evaluation. The reduced reliability can potentially be attributed to skin artifacts, differences in marker placement, and the inherent kinematic variability of finger motion. The proposed marker set shows potential to assess finger postures and analyse activities of daily living, primarily within the context of single session tests.

SenGlove—A Modular Wearable Device to Measure Kinematic Parameters of The Human Hand

For technical or medical applications, the knowledge of the exact kinematics of the human hand is key to utilizing its capability of handling and manipulating objects and communicating with other humans or machines. The optimal relationship between the number of measurement parameters, measurement accuracy, as well as complexity, usability and cost of the measuring systems is hard to find. Biomechanic assumptions, the concepts of a biomechatronic system and the mechatronic design process, as well as commercially available components, are used to develop a sensorized glove. The proposed wearable introduced in this paper can measure 14 of 15 angular values of a simplified hand model. Additionally, five contact pressure values at the fingertips and inertial data of the whole hand with six degrees of freedom are gathered. Due to the modular design and a hand size examination based on anthropometric parameters, the concept of the wearable is applicable to a large variety of hand sizes and adaptable to different use cases. Validations show a combined root-mean-square error of 0.99° to 2.38° for the measurement of all joint angles on one finger, surpassing the human perception threshold and the current state-of-the-art in science and technology for comparable systems.

A method for measuring in vivo finger kinematics using electromagnetic tracking

Accurate in vivo measurement of finger joint kinematics is important for evaluation of treatment methods, implant designs, and for the development and validation of computer models of the hand. The main objective of this project was to develop a standardized finger kinematic measurement system employing electromagnetic (EM) tracking to measure in vivo finger motion pathways. A landmark digitization protocol was developed and used in vivo, in a biomechanical study using EM trackers secured to the finger segments. In vivo results for finger flexion/extension showed no significant differences between EM and goniometer results, 5°±3°; p = 0.735.

In Vivo Measurement of Wrist Movements during the Dart-Throwing Motion Using Inertial Measurement Units

BACKGROUND

This study investigates the dart-throwing motion (DTM) by comparing an inertial measurement unit-based system previously validated for basic motion tasks with an optoelectronic motion capture system. The DTM is interesting as wrist movement during many activities of daily living occur in this movement plane, but the complex movement is difficult to assess clinically.

METHODS

Ten healthy subjects were recorded while performing the DTM with their right wrist using inertial sensors and skin markers. Maximum range of motion obtained by the different systems and the mean absolute difference were calculated.

RESULTS

In the flexion-extension plane, both systems calculated a range of motion of 100° with mean absolute differences of 8°, while in the radial-ulnar deviation plane, a mean absolute difference of 17° and range of motion values of 48° for the optoelectronic system and 59° for the inertial measurement units were found.

CONCLUSIONS

This study shows the challenge of comparing results of different kinematic motion capture systems for complex movements while also highlighting inertial measurement units as promising for future clinical application in dynamic and coupled wrist movements. Possible sources of error and solutions are discussed.

Quantifying Soft Tissue Artefacts and Imaging Variability in Motion Capture of the Fingers

This study assessed the accuracy of marker-based kinematic analysis of the fingers, considering soft tissue artefacts (STA) and marker imaging uncertainty. We collected CT images of the hand from healthy volunteers with fingers in full extension, mid- and full-flexion, including motion capture markers. Bones and markers were segmented and meshed. The bone meshes for each volunteer's scans were aligned using the proximal phalanx to study the proximal interphalangeal joint (PIP), and using the middle phalanx to study the distal interphalangeal joint (DIP). The angle changes between positions were extracted. The HAWK protocol was used to calculate PIP and DIP joint flexion angles in each position based on the marker centroids. Finally the marker locations were 'corrected' relative to the underlying bones, and the flexion angles recalculated. Static and dynamic marker imaging uncertainty was evaluated using a wand. A strong positive correlation was observed between marker- and CT-based joint angle changes with 0.980 and 0.892 regression slopes for PIP and DIP, respectively, and Root Mean Squared Errors below 4°. Notably for the PIP joint, correlation was worsened by STA correction. The 95% imaging uncertainty interval was < ± 1° for joints, and < ± 0.25 mm for segment lengths. In summary, the HAWK marker set's accuracy was characterised for finger joint flexion angle changes in a small group of healthy individuals and static poses, and was found to benefit from skin movements during flexion.

Comparison of a New Inertial Sensor Based System with an Optoelectronic Motion Capture System for Motion Analysis of Healthy Human Wrist Joints

This study aims to compare a new inertial measurement unit based system with the highly accurate but complex laboratory gold standard, an optoelectronic motion capture system. Inertial measurement units are sensors based on accelerometers, gyroscopes, and/or magnetometers. Ten healthy subjects were recorded while performing flexion-extension and radial-ulnar deviation movements of their right wrist using inertial sensors and skin markers. Maximum range of motion during these trials and mean absolute difference between the systems were calculated. A difference of 10° ± 5° for flexion-extension and 2° ± 1° for radial-ulnar deviation was found between the two systems with absolute range of motion values of 126° and 50° in the respective axes. A Wilcoxon rank sum test resulted in a no statistical differences between the systems with p-values of 0.24 and 0.62. The observed results are even more precise than reports from previous studies, where differences between 14° and 27° for flexion-extension and differences between 6° and 17° for radial-ulnar deviation were found. Effortless and fast applicability, good precision, and low inter-observer variability make inertial measurement unit based systems applicable to clinical settings.

Assessment of hand function during activities of daily living using motion tracking cameras: A systematic review

The human hand is the most frequently used body part in activities of daily living. With its complex anatomical structure and the small size compared to the body, assessing the functional capability is highly challenging. The aim of this review was to provide a systematic overview on currently available 3D motion analysis based on skin markers for the assessment of hand function during activities of daily living. It is focused on methodology rather than results. A systematic review according to the PRISMA guidelines was performed. The systematic search yielded 1349 discrete articles. Of 147 articles included on basis of title, 123 were excluded after abstract review, and 24 were included in the full-text analysis with 13 key articles. There is still limited knowledge about hand and finger kinematics during activities of daily living. A standardization of the task is required in order to overcome the nonrepetitive nature and high variability of upper limb motion and ensure repeatability of task performance. To yield a progress in the analysis of human hand movements, an assessment of human kinematics including fingers, wrist, and thumb and an identification of relevant parameters that characterize a healthy motion pattern during functional tasks are needed.

A Tangible Solution for Hand Motion Tracking in Clinical Applications

Objective real-time assessment of hand motion is crucial in many clinical applications including technically-assisted physical rehabilitation of the upper extremity. We propose an inertial-sensor-based hand motion tracking system and a set of dual-quaternion-based methods for estimation of finger segment orientations and fingertip positions. The proposed system addresses the specific requirements of clinical applications in two ways: (1) In contrast to glove-based approaches, the proposed solution maintains the sense of touch. (2) In contrast to previous work, the proposed methods avoid the use of complex calibration procedures, which means that they are suitable for patients with severe motor impairment of the hand. To overcome the limited significance of validation in lab environments with homogeneous magnetic fields, we validate the proposed system using functional hand motions in the presence of severe magnetic disturbances as they appear in realistic clinical settings. We show that standard sensor fusion methods that rely on magnetometer readings may perform well in perfect laboratory environments but can lead to more than 15 cm root-mean-square error for the fingertip distances in realistic environments, while our advanced method yields root-mean-square errors below 2 cm for all performed motions.

Distal upper limb kinematics during functional everyday tasks

Quantitative characterisation of upper limb motion allows the evaluation of the effect of pathology on functional task performance, potentially directing rehabilitation strategies. Movement patterns of the distal upper limb in healthy adults during functional tasks have not been extensively characterised. During five loaded functional tasks (drinking from a glass, pouring from a kettle, turning a handle, lifting a bag to a shelf, turning a key) the movement patterns were characterised using three-dimensional motion analysis with a minimal marker set in 16 healthy adults (10 M,6F, 27 (IQR:25-43)years). Joint angles reported include flexion/extension at the elbow and wrist, forearm supination/pronation and digits 2-5 metacarpophalangeal (MCP) joint flexion/extension. Additionally for the thumb the angle between the metacarpal of the thumb and the 2nd digit (Thumb base), the thumb MCP (Thumb MCP) and interphalangeal (Thumb IP) joint angles are presented. Durations of activities performed at self-selected comfortable speeds (3.36 (IQR:3.07,3.66)s turning a key to 6.20 (IQR:5.44,6.38)s drinking from a glass) are reported. The maximum joint angles used (median of participants' maxima) were 141° of elbow flexion, 116° forearm supination, 36° wrist extension, 56° Thumb base, 14° Thumb MCP flexion, 18° Thumb IP flexion, 85° MCP2-5 flexion. The tasks of drinking from a glass, lifting a bag to a shelf and turning a key appeared to have the least variation in performance, suggesting that these activities are better suited to be selected as standardized tasks for assessing the impact of pathology on movement than pouring from a kettle and turning a handle.

Measuring 3D Hand and Finger Kinematics-A Comparison between Inertial Sensing and an Opto-Electronic Marker System

Objective analysis of hand and finger kinematics is important to increase understanding of hand function and to quantify motor symptoms for clinical diagnosis. The aim of this paper is to compare a new 3D measurement system containing multiple miniature inertial sensors (PowerGlove) with an opto-electronic marker system during specific finger tasks in three healthy subjects. Various finger movements tasks were performed: flexion, fast flexion, tapping, hand open/closing, ab/adduction and circular pointing. 3D joint angles of the index finger joints and position of the thumb and index were compared between systems. Median root mean square differences of the main joint angles of interest ranged between 3.3 and 8.4deg. Largest differences were found in fast and circular pointing tasks, mainly in range of motion. Smallest differences for all 3D joint angles were observed in the flexion tasks. For fast finger tapping, the thumb/index amplitude showed a median difference of 15.8mm. Differences could be explained by skin movement artifacts caused by relative marker movements of the marker system, particularly during fast tasks; large movement accelerations and angular velocities which exceeded the range of the inertial sensors; and by differences in segment calibrations between systems. The PowerGlove is a system that can be of value to measure 3D hand and finger kinematics and positions in an ambulatory setting. The reported differences need to be taken into account when applying the system in studies understanding the hand function and quantifying hand motor symptoms in clinical practice.

Optimal Grip Points with Human Hand

The aim of this work was to determine how an object of given shape should be grasped to maximize the grasping capacity of the human hand. To do that the model searches the optimal grip points on the object with the aim of maximizing the weight of the object lifted without slipping. The model solves both the equilibrium of the grasped object and the biomechanical constraints of the human hand, such as the stress limit of each muscle. To give some examples, grasps of three-dimensional (3D) objects of different shape and size were optimized. The results of the simulations done also allowed the identification of the parameters that further influence human grasping. Moreover, trials were done to prove the results given by the computational model.