Quantification of finger joint loadings using musculoskeletal modelling clarifies mechanical risk factors of hand osteoarthritis

https://doi.org/10.1016/j.medengphy.2013.10.007Get rights and content

Abstract

Owing to limited quantitative data related to the loadings (forces and pressures) acting upon finger joints, several clinical observations regarding mechanical risk factors of hand osteoarthritis remain misunderstood. To improve the knowledge of this pathology, the present study used musculoskeletal modelling to quantify the forces and pressures acting upon hand joints during two grasping tasks.

Kinematic and grip force data were recorded during both a pinch and a power grip tasks. Three-dimensional magnetic resonance imaging measurements were conducted to quantify joint contact areas. Using these datasets as input, a musculoskeletal model of the hand and wrist, including twenty-three degrees of freedom and forty-two muscles, has been developed to estimate joint forces and joint pressures.

When compared with the power grip task, the pinch grip task resulted in two to eight times higher joint loadings whereas the grip forces exerted on each finger were twice lower. For both tasks, joint forces and pressures increased along a disto-proximal direction for each finger.

The quantitative dataset provided by the present hand model clarified two clinical observations about osteoarthritis development which were not fully understood, i.e., the strong risk associated to pinch grip tasks and the high frequency of thumb-base osteoarthritis.

Introduction

Hand osteoarthritis (OA) is a major public health concern which symptomatic cases were reported for 5–25% of the population [14], [26], [28], [49]. This pathology induces a degeneration of articular cartilage and surrounding tissues [4], [26] resulting in loss of grip strength [16], [24], [29], [49], reduced range of motions [25] and other impairments regarding daily tasks [24], [29], [49]. The treatment of hand OA can vary from conservative methods, e.g., physiotherapy, medication or orthotics, to highly invasive surgery [47]. Understanding risk factors is important to prevent the disease and to improve potential therapies. Genetics, ageing or hormonal issues have been proposed as accounting factors of primary OA (idiopathic cases) [2], [22] but no clear evidence has been provided. Conversely, anatomic, metabolic, traumatic and inflammatory disorders have been clearly identified as secondary factors resulting in OA [4]. Especially, the mechanical loadings, i.e., the forces and pressures, acting upon the joints had often been considered as an important risk factor of hand OA because they reflect how the cartilage is used [1], [4], [21], [22], [48].

Despite the numerous investigations of the potential risk factors of OA, two aspects of hand OA development remain misunderstood. The first one relates to the risks associated to the grip techniques. Generally, two grip techniques have been compared in the biomechanics literature i.e., the power and the pinch grip. While the power grip almost involves the whole hand palmar surface and is used for forceful tasks (e.g., tool handling or racket sports), the pinch grip is related to fingertips and precision tasks (e.g., writing or sewing) [33]. Intriguingly, several studies have associated OA in the distal interphalangeal (DIP) joints and the pinch grip [20], [23], [27], [32], [39], thereby suggesting that this task induces high joint loadings, whereas the grip force measured during this task is around five times lower than the ones reported for the power grip [40]. The second puzzling issue concerns the specific alterations of each finger. OA is indeed more frequent and severe in the most distal joint (DIP) for the long fingers and in the most proximal (trapeziometacarpal, TMC) for the thumb [7], [13], [49]. Therefore, while the five fingers represent a similar open-chain linkage with 3 mobile segments, they show different adaptations to OA disorders.

Since the two issues presented above relates to mechanical risk factors of hand OA, a quantification of the loadings about finger joints would be helpful. Unfortunately, the assessment of such intern variables is very challenging given that their direct in vivo measurements are ethically and technically impossible. Alternatively, musculoskeletal models can provide an estimation of the joint forces using kinematic and external force data as input. Such models have been previously used for either the thumb [10], the index finger [3], [9], [17], [44] or the thumb-index pinch [42] but, for several reasons, the provided estimations are not sufficient to fully comprehend mechanical risk factors of hand OA. First, none of these previous models included all the five fingers and the wrist together and thus neglected the mechanical couplings induced by poly-articular muscles which are important to consider when studying multi-finger tasks [34]. Second, the input data of these previous models were only assumptions rather than experimental in vivo subject-specific measurements. Finally, the joint contact dimensions were not taken into account whereas they represent crucial information to fully describe the risk of damage [32]. One could indeed expect that the risk of damage would be lower if a given force is supported by a large rather than a small contact area.

The objective of the present study was to quantify the forces and pressures acting upon hand joints during two grasping tasks and to interpret this data with regard to the observations concerning mechanical risk factors of hand OA. Considering the two issues described above, we hypothesised that (1) the joint pressure would be higher during the pinch grip than during the power grip for every joint and that (2) the joint pressure would increase along a proximo-distal direction for the long fingers and along a disto-proximal direction for the thumb.

Section snippets

Subjects and protocol

Ten healthy right handed males were recruited for this experiment (age: 25.5 ± 3.2 years; height: 178.6 ± 6.1 cm; weight: 71.2 ± 7.2 kg; hand length: 19.0 ± 0.8 cm; hand width: 8.6 ± 0.5 cm). Each participant was free of upper-right extremity disorder and signed an informed consent. Although hand OA is female predominant [14], [24], [26], [49], the present work focused, as a first step, on analysing how the joint loadings were influenced by different joints or grasping tasks regardless of gender.

Grip forces and joint angles during the gripping tasks

The grip force recorded during the power grip and the pinch grip tasks were 811.3 ± 121.6 and 132.5 ± 26.5 N, respectively. During the pinch grip task, the thumb and index finger produced each a 66.2-N force concentrated on the fingertip (Fig. 3) whereas they each exerted during the power grip task around 130 N. During the power grip, the highest external forces were exerted by the thumb most proximal areas (metacarpal: 35.6 ± 24.5 N; metacarpo-phalangeal joint: 55.7 ± 23.9 N) and by the index finger most

Discussion

Based on the combination of both an experimental and a modelling approach, the present study provided estimations of finger joint loadings. This dataset is of great interest given that the limited quantitative data available so far prevented a complete understanding of the mechanical risk factors of hand OA.

The recorded grip forces are comparable to those reported in the literature for pinch [8], [18] and power grip tasks [45]. As expected, the force exerted by the thumb and index fingers

Acknowledgements

We would like to thank Dr. Jean-Pierre Mattei (CRMBM) for his helpful comments related to finger osteoarthritis.
Financial disclosure

Part of this study was financed by the “Santé, sport et développement durable” foundation of the Aix-Marseille University.

Institute of Movement Sciences (ISM UMR 7287) is using equipment of Oxylane Research for data acquisition.
Conflict of interest

None.
Ethical approval

The project was approved by the Aix-Marseille University ethics committee (ref number:

References (49)

  • F. Paclet et al.

    Motor control theories improve biomechanical model of the hand for finger pressing tasks

    J Biomech

    (2012)
  • J.W. Ramsay et al.

    Muscle moment arm and normalized moment contributions as reference data for musculoskeletal elbow and wrist joint models

    J Biomech

    (2009)
  • J.L. Sancho-Bru et al.

    A 3-D dynamic model of human finger for studying free movements

    J Biomech

    (2001)
  • N. Tsaousidis et al.

    Effects of gloves on maximum force and the rate of force development in pinch, wrist flexion and grip

    Int J Ind Ergon

    (1998)
  • F.J. Valero-Cuevas et al.

    Large index-fingertip forces are produced by subject-independent patterns of muscle excitation

    J Biomech

    (1998)
  • L. Vigouroux et al.

    Middle and ring fingers are more exposed to pulley rupture than index and little during sport-climbing: a biomechanical explanation

    Clin Biomech

    (2008)
  • B. Weightman et al.

    Finger joint force predictions related to design of joint replacements

    J Biomed Eng

    (1982)
  • B. Wimer et al.

    Development of a new dynamometer for measuring grip strength applied on a cylindrical handle

    Med Eng Phys

    (2009)
  • Y. Zhang et al.

    Epidemiology of osteoarthritis

    Clin Geriatr Med

    (2010)
  • C.J. Alexander et al.

    Relation between the finger positions used in the precision and partial power grips and the regional prevalence of osteoarthritis

    Skeletal Radiol

    (1994)
  • C.J. Alexander

    Idiopathic osteoarthritis: time to change paradigms?

    Skeletal Radiol

    (2004)
  • K.N. An et al.

    Forces in the normal and abnormal hand

    J Orthop Res

    (1985)
  • B. Buchholz et al.

    Anthropometric data for describing the kinematics of the human hand

    Ergonomics

    (1992)
  • E.Y. Chao et al.

    Biomechanics of the hand: a basic research study

    World Sci

    (1989)
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