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Hand and Wrist Biomechanics

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A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Applied Biosciences and Bioengineering".

Deadline for manuscript submissions: closed (20 July 2023) | Viewed by 8260

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Special Issue Editors

Dr. Verónica Gracia-Ibáñez

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Guest Editor

Department of Mechanical Engineering and Construction, Universitat Jaume I, E12071 Castellón, Spain
Interests: hand and wrist biomechanics; 3D motion analysis; hand synergies; functional assessment of hand and wrist; hand disfunctions; electromyography; exoesqueletons; ergonomics; biomedical engineering; rehabilitation; design engineering; industrial engineering
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Dr. Néstor José Jarque-Bou

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Guest Editor

Department of Mechanical Engineering and Construction, Universitat Jaume I, Av. Vicent Sos Baynat, 12071 Castelló de la Plana, Spain
Interests: design engineering; industrial engineering; biomedical engineering; hand synergies; kinematics; biomechanics; electromyography; motion capture; rehabilitation; 3D motion analysis

Prof. Dr. Margarita Vergara

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Guest Editor

Department of Mechanical Engineering and Construction, Universitat Jaume I, 12071 Castelló, Spain
Interests: designing product; design and development; ergonomics; design thinking; prototyping; biomechanical engineering; biomechanics; design engineering; product development; engineering drawing

Special Issue Information

Dear Colleagues,

The high complexity of the hand enables humans to carry out a huge variety of activities providing them with functional independence. Deep knowledge of healthy hand behavior, from grasping biomechanics to complex manipulation in daily life activities, both from its kinematics and from muscle activation comprehension, is a challenging field. This knowledge is of vital importance in fields such as robotics and prosthesics, especially in trying to imitate the behavior of the human hand, one of the most difficult parts of the human body to imitate. It is also key in ergonomics for product design, as well as for improving work environments. Designs must consider hand and wrist healthy operating parameters to avoid forcing the human mechanism and thus avert injuries. In addition, many injuries and pathologies affecting the hand and wrist cause each year a large number of people to suffer from disabilities preventing them from a fully functional life. Knowing the biomechanical limitations produced by the diseases is of vital importance in clinical making decisions and in rehabilitation treatments.

This Special Issue invites biomechanical researchers to provide contributions on: (i) studies that improve the biomechanical understanding of the healthy human hand and wrist; and (ii) studies applied in different fields (robotics, health, ergonomics) that use biomechanical parameters of the healthy human hand and wrist as a gold standard: to improve humanoid robotic hands and hand prostheses; to be checked against same parameters in certain pathologies for the better understanding of the functional limitations that they produce; or in ergonomic designs of assistive products or assistive hand exoskeletons for people with disabilities, as well as hand exoskeletons for rehabilitation or to assist improving the workplace.

Dr. Verónica Gracia-Ibáñez
Dr. Néstor José Jarque-Bou
Prof. Dr. Margarita Vergara
Guest Editors

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Keywords

hand biomechanics
wrist biomechanics
hand kinematics
wrist kinematics
hand synergies
human grasping
forearm and hand muscle activation

Published Papers (6 papers)

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Editorial

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2 pages, 202 KiB

Open AccessEditorial

Hand and Wrist Biomechanics

by Verónica Gracia-Ibáñez, Néstor J. Jarque-Bou and Margarita Vergara

Appl. Sci. 2023, 13(24), 13158; https://doi.org/10.3390/app132413158 - 11 Dec 2023

Viewed by 716

Abstract

The complexity of the human hand enables us to carry out a huge variety of activities, providing us with functional independence [...] Full article

(This article belongs to the Special Issue Hand and Wrist Biomechanics)

Research

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13 pages, 3114 KiB

Open AccessCommunication

Evaluating a Kinematic Data Glove with Pressure Sensors to Automatically Differentiate Free Motion from Product Manipulation

by Alba Roda-Sales, Joaquín L. Sancho-Bru and Margarita Vergara

Appl. Sci. 2023, 13(15), 8765; https://doi.org/10.3390/app13158765 - 29 Jul 2023

Viewed by 922

Abstract

When studying hand kinematics, it is key to differentiate between free motion and manipulation. This differentiation can be achieved using pressure sensors or through visual analysis in the absence of sensors. Certain data gloves, such as the CyberGlove II, allow recording hand kinematics with good accuracy when properly calibrated. Other gloves, such as the Virtual Motion Glove 30 (VMG30), are also equipped with pressure sensors to detect object contact. The aim of this study is to perform a technical validation to evaluate the feasibility of using virtual reality gloves with pressure sensors such as the VMG30 for hand kinematics characterization during product manipulation, testing its accuracy for motion recording when compared with CyberGlove as well as its ability to differentiate between free motion and manipulation using its pressure sensors in comparison to visual analysis. Firstly, both data gloves were calibrated using a specific protocol developed by the research group. Then, the active ranges of motion of 16 hand joints angles were recorded in three participants using both gloves and compared using repeated measures ANOVAs. The detection capability of pressure sensors was compared to visual analysis in two participants while performing six tasks involving product manipulation. The results revealed that kinematic data recordings from the VMG30 were less accurate than those from the CyberGlove. Furthermore, the pressure sensors did not provide additional precision with respect to the visual analysis technique. In fact, several pressure sensors were rarely activated, and the distribution of pressure sensors within the glove was questioned. Current available gloves such as the VMG30 would require design improvements to fit the requirements for kinematics characterization during product manipulation. The pressure sensors should have higher sensitivity, the pressure sensor’s location should comprise the palm, glove fit should be improved, and its overall stiffness should be reduced. Full article

(This article belongs to the Special Issue Hand and Wrist Biomechanics)

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18 pages, 32768 KiB

Open AccessCommunication

A Novel Passive Implantable Differential Mechanism to Restore Individuated Finger Flexion during Grasping following Tendon Transfer Surgery: A Pilot Study

by Suraj Chakravarthi Raja, Won Suk You, Kian Jalaleddini, Justin C. Casebier, Nina R. Lightdale-Miric, Vincent R. Hentz, Francisco J. Valero-Cuevas and Ravi Balasubramanian

Appl. Sci. 2023, 13(9), 5804; https://doi.org/10.3390/app13095804 - 8 May 2023

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Abstract

Tendon transfer surgery is often used to restore hand grasp function following high median-ulnar nerve palsy. This surgery typically reroutes and sutures the tendon of the extensor carpi radialis longus (ECRL) muscle to all four flexor digitorum profundus (FDP) tendons of the hand, coupling them together. This makes it difficult to grasp irregularly shaped objects. We propose inserting a novel implantable passive device between the FDP tendons to surgically construct a differential mechanism, enabling the fingers to individually adapt to the irregular contours during grasping. These passive implants with no moving parts are fabricated from biocompatible materials. We tested the implants’ ability to create differential flexion between the index and middle fingers when actuated by a single muscle in two human cadaver hands using a computerized closed-loop control paradigm. In these cadaveric models, the implants enabled significantly more differential flexion between the index and middle fingers for a wide range of donor tendon tensions. The implants also redistributed fingertip forces between fingers. When grasping uneven objects, the difference in contact forces between fingers reduced by nearly 23% compared to the current suture-based surgery. These results suggest that self-adaptive grasp is possible in tendon transfers that drive multiple distal flexor tendons. Full article

(This article belongs to the Special Issue Hand and Wrist Biomechanics)

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12 pages, 4802 KiB

Open AccessArticle

Smoothness and Efficiency Metrics Behavior after an Upper Extremity Training with Robic Humanoid Robot in Paediatric Spinal Cord Injured Patients

by Miriam Salas-Monedero, Víctor Cereijo-Herranz, Ana DelosReyes-Guzmán, Yolanda Pérez-Borrego, Angel Gil-Agudo, Fuensanta García-Martín, José-Carlos Pulido-Pascual and Elisa López-Dolado

Appl. Sci. 2023, 13(8), 4979; https://doi.org/10.3390/app13084979 - 15 Apr 2023

Viewed by 1250

Abstract

The upper extremity behavior in smoothness and efficiency metrics should be different between paraplegic and tetraplegic patients. The aim of this article was to analyze the behavior of these metrics after receiving upper extremity training with the humanoid robot Robic as a treatment. Ten pediatric patients participated in the study and completed ten experimental sessions with Robic. Patients were assessed at baseline and at ending the training using the Box and Block test and a non-immersive virtual application based on the Leap Motion Controller available in the RehabHand software. From this application, the smoothness metric was calculated as the number of peaks or units of movement detected in the velocity profile of the hand during the execution of the task, and the efficiency metric was assessed by calculating the length of the hand trajectory. Patients with tetraplegia had a significantly longer trajectory (286.01 ± 59.87 mm) than paraplegics (123.61 ± 17.14 mm) in the baseline situation. However, at the end of the training, there were no differences between them. In the Box and Block test, the paraplegic group passed more cubes than tetraplegics. In conclusion, the first experience with a Robic robot in SCI was very positive, with observed improvements in upper extremity dexterity in trained patients. Full article

(This article belongs to the Special Issue Hand and Wrist Biomechanics)

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14 pages, 3961 KiB

Open AccessArticle

Finite Element Modeling of the Fingers and Wrist Flexion/Extension Effect on Median Nerve Compression

by Saveliy Peshin, Yulia Karakulova and Alex G. Kuchumov

Appl. Sci. 2023, 13(2), 1219; https://doi.org/10.3390/app13021219 - 16 Jan 2023

Cited by 2 | Viewed by 2222

Abstract

Carpal tunnel syndrome (CTS) is the most common pathology among disorders of the peripheral nervous system related to median nerve compression. To our knowledge, there are limited data on the effect of tendon movement on median nerve compression. This study focuses on the understanding of the carpal syndrome by simulating the impact of tendons movement caused by fingers flexion by Finite Element Analysis. Therefore, such modeling is the step toward the development of a personalized technique for value determining median nerve compression. Open-source MRI of the human right hand was used to build patient-specific phalanges of the fingers. Carpal tunnel soft tissues were considered as hyper-elastic materials, while bone structures were considered as elastic ones. The final finite-element model had 40 solid bodies which contacted the joint. Results were obtained for four cases of wrist movements: finger flexion, hand flexion/extension, and wrist extension with subsequent by finger flexion. Compression of the median nerve ranged from 129 Pa to 227 Pa. The results show that compression of the median nerve occurs faster during wrist flexion than during wrist extension or finger flexion. A decrease in compression during finger flexion was noticed with wrist extension followed by finger flexion. Full article

(This article belongs to the Special Issue Hand and Wrist Biomechanics)

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14 pages, 5650 KiB

Open AccessArticle

Mapping of the Upper Limb Work-Space: Benchmarking Four Wrist Smoothness Metrics

by Alessandro Scano, Cristina Brambilla, Henning Müller and Manfredo Atzori

Appl. Sci. 2022, 12(24), 12643; https://doi.org/10.3390/app122412643 - 9 Dec 2022

Viewed by 862

Abstract

Smoothness is a commonly used measure of motion control. Physiological motion is characterized by high smoothness in the upper limb workspace. Moreover, there is evidence that smoothness-based models describe effectively skilled motion planning. Typical smoothness measures are based on wrist kinematics. Despite smoothness being often used as a measure of motor control and to evaluate clinical pathologies, so far, a smoothness map is not available for the whole workspace of the upper limb. In this work, we provide a map of the upper limb workspace comparing four smoothness metrics: the normalized jerk, the speed metric, the spectral arc length, and the number of speed peaks. Fifteen subjects were enrolled, performing several reaching movements in the upper limb workspace in multiple directions in five planes (frontal, left, right, horizontal and up). Smoothness of the wrist of each movement was computed and a 3D workspace map was reconstructed. The four smoothness metrics were in general accordance. Lower smoothness was found in the less dexterous sectors (up and left sectors), with respect to the frontal, horizontal, and right sectors. The number of speed peaks, frequently used for evaluating motion in neurological diseases, was instead not suitable for assessing movements of healthy subjects. Lastly, strong correlation was found especially between the normalized jerk and speed metric. These results can be used as a benchmark for motor control studies in various fields as well as clinical studies. Full article

(This article belongs to the Special Issue Hand and Wrist Biomechanics)

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