Musculoskeletal Morphing from Human to Mouse

Procedia IUTAM Procedia IUTAM 00 (2011) 1–9

2011 Symposium on Human Body Dynamics Musculoskeletal Morphing from Human to Mouse

Yoshihiko Nakamuraa,∗, Yosuke Ikegamia, Akihiro Yoshimatsua, Ko Ayusawaa, Hirotaka Imagawaa, and Satoshi Ootab

aDepartment of Mechano-Informatics, Graduate School of Information and Science and Technology, University of Tokyo, 7-3-1, Hongo, Bunkyo-ku, Tokyo, Japan bBioresource Center, Riken, 3-1-1 Takanodai, Tsukuba-shi, Ibaragi, Japan

Abstract The analysis of movement provides various insights of human body such as biomechanical property of muscles, function of neural systems, physiology of sensory-motor system, skills of athletic movements, and more. Biomechan- ical modeling and robotics computation have been integrated to extend the applications of musculoskeletal analysis of human movements. The analysis would also provide valuable means for the other mammalian animals. One of current approaches of post-genomic research focuses to find connections between the phenotype and the genotype. The former means the visible morphological or behavioral expression of an animal, while the latter implies its genetic expression. Knockout mice allows to study the developmental pathway from the genetic disorders to the behavioral disorders. Would musculoskeletal analysis of mice also offer scientific means for such study? This paper reports our recent technological development to build the musculoskeletal model of a laboratory mouse. We propose mapping the musculoskeletal model of human to a laboratory mouse based on the morphological similarity between the two mammals. Although the model will need fine adjustment based on the CT data or else, we can still use the mapped musculoskeletal model as an approximate model of the mouse’s musculoskeletal system. The preliminary results of muscle length analysis is shown for the motion captured data of a hairless mouse. Keywords: Musculoskeletal Model; Phenotype Analysis; Homology Mapping; Laboratory Mouse; Morphing Mammalian Bones

1. Introduction

Mice are useful laboratory animals for biomedical studies. Mice are classiﬁed to early mammalia in taxology and have close biological relationship with human. Bifurcation on the evolutional tree from mice toward human started 75 million years ago[1]. Homology of the two species is the reason of importance of mice as laboratory animals. The completion of decoding the whole genome was declared for mouse in 2002 and for human in 2003. The two species are reported 90% of genome in common and show 70% homology in their phenotypes[1]. The whole database including the mouse genome is made available in the WEB as the Mouse Genome Informatics[2]. Recent development of the genetically modiﬁed mouse and low cost of breeding and managements in laboratories have increased the importance

∗Corresponding author. Tel: +81-3-5841-6379; fax: +81-3-5841-7916 Email address: [email protected] (Yoshihiko Nakamura) Yoshihiko Nakamura, Yosuke Ikegami, Akihiro Yoshimatsu, Ko Ayusawa, Hirotaka Imagawa, and Satoshi Oota / Procedia IUTAM 00 (2011) 1–9 2 of laboratory mouse as a model animal for studies in medical and pharmaceutical fields [3]. In genetic disorders, it is considered a useful approach to transfer the knowledge from mouse experiments to human. Observation of phenotype is commonly done for cell development and for social behaviors of individual mice. More quantitative observation is to be of critical importance for biomechanical evaluation of the musculoskeletal system. Technological developments are most demanded for such qualitative biomechanical observation of the laboratory mouse. A model of musculoskeletal system is necessary for analysis of musculoskeletal phenomena. The model should include the skeletal model for kinematic analysis and the musculotendinous model for analysis of motor function. While there are some literatures on the skeletal system of mouse [4], there are not many works done and published on modeling of musculotendinous system of mouse or even of the other mammalian animals. As it is done for human, MRI and CT imaging is the main source of anatomical information. Since resolution of MRI imaging depends on the relative scale of animals and excitation coils, MRI imaging has technical difficulties for small animals. X-ray CT scanning is more useful for small laboratory animals due to the additional fact that the problem of radiation exposure is not too critical for such animals. The ANR project conducts musculoskeletal analysis for laboratory rat based on the X-ray CT scanning [5]. More recently, Oota et al.[6],[7] developed the model of skeletal system of laboratory mouse based on the X-ray CT scanning, while modeling of the whole musculotendinous system is still a future problem. On the other hand, there are many publications on the modeling and analysis of human musculoskeletal system based on the rich accumulation of anatomical and physiological knowledges [8],[9]. Nakamura et al. developed the wholebody model of the human musculoskeletal system that is appropriate and consistent with the algorithms of robotic kinematic and dynamic computation[10],[11][12][13] and proposed an optimization algorithm to estimate muscle activities based on the information from a motion capture system and the other sensory systems. The developed software and measurement system have been applied for analysis of human motions. The paper describes on a systematic method to build a musculotendinous model of a mammalian animal, specif- ically of a laboratory mouse in this paper. The use of MRI/CT image is assumed for fine anatomical agreements. However, our main proposal is to use the human musculotendinous model, that is developed in precision, and transfer it to build the preliminary model of another mammalian animal before fine anatomical adjustments from the MRI/CT image data. This approach relies on the homology between mammalian species. The proposed method consists of two consecutive steps. The first step is to find a geometrical morphing map from one bone of the human skeletal system to the corresponding one of another mammalian species, namely laboratory mouse in this paper. The second step uses the geometrical morphing maps of bones to transfer the terminal points and via-points of the elements of human musculotendinous system to those of mouse musculotendinous system. This paper also shows the results of muscle length analysis from the motion captured data of a mutant nude mouse. More detailed analysis of muscle activities will need anatomical refinements of the musculotendinous system. Contact measurements and analysis will also need be solved in future studies. The related technologies would be useful such as identification of mass properties of the body segments[14][15][16][17][18], and estimation of neuromuscular activities[19][20].

2. Of Mice and Men 2.1. Model of the human musculoskeletal system The human musculoskeletal system developed by Nakamura et al. [13] consists of the main elements to actuate 150 DOF of the whole body skeletal system, which excludes the DOF in the hands, feet, and head. The components as the objects of biomechanical analysis are currently 1206 in total, consisting of 997 muscles, 50 tendons, 125 ligaments, and 34 cartilages. We adopted the human musculoskeletal system in Fig.1 as a model of human to be used for mapping between skeletal systems and transformation of musculotendinous system. The skeletal system is based on an adult Caucasian model [21]. The model includes about 200 bones in total, which are grouped to make 50 segments connected by kinematic spherical joints. A bone is geometrically modeled as a polygonal object. Each of muscles, tendons, ligaments, and cartilages is modeled by a wire with the point of origin, the via points, the point of insertion on links. A link is either a link of bone segment or a virtual link. A link of bone segment has mass, while a virtual link doesn’t. The virtual links are ﬁctitious links introduced for representation of connection or bifurcation of wires. The virtual links are ﬂoating links. The mass of whole body is distributed among the bone segments. Yoshihiko Nakamura, Yosuke Ikegami, Akihiro Yoshimatsu, Ko Ayusawa, Hirotaka Imagawa, and Satoshi Oota / Procedia IUTAM 00 (2011) 1–9 3

Soleus

Virtual link

Achilles tendon

Fig. 1: Overview of Human Full Body Muscu- Fig. 2: Conceputual Example of Virtual Fig. 3: Mouse Skeleton Model: this poly- loskeletal Model: this model is provided by Y. Link gon data is provided by S. Oota, et al.[7] Nakamura, et al.[11]

An example of the complex of soleus and Achilles tendon is shown in Fig.2. Achilles tendon has the origin on calcaneal tuberosity and the insertion on a virtual link. Soleus is represented by a wire with the origin on the complex of tibia and ﬁbula and the insertion on the same virtual link.

2.2. Model of the mouse skeletal system The polygon model of the mouse skeletal system developed by Oota et al. [7] was used, by courtesy of the researchers. The model was made through segmentation and polygon reduction from the volume data obtained by a high precision X-ray CT scanner in University of Texas at Austin. The skeletal mouse system is shown in Fig.3.

2.3. Distinction of skeletal systems of human and mouse The principle of mapping skeletal systems is based on the homology between mammalian species. Although mouse and human has a large diﬀerence in scale, taxonomical diﬀerence is not too far within mammals. According to Simpson[22] human and mouse are in the same branch of Euarchontoglires within the tree of life of Mammals[23]. Namely,

• (Euarchontoglires (Superorder: Glires (Order: Rodentia (Family: Muridae (Mouse))))) • (Euarchontoglires (Superorder: Euarchonta (Order: Primates (Family: Hominidae (Homo sapiens)))))

It is important to understand the difference in skeletal geometry between human and mouse. The main difference is in the number of bones in coccyx. The coccyx of human consists of 3-5 bones of accretion, while that of mouse consists of 25-27 separate bones. The structure of spine is also noteworthy. The thoracic vertebrae are 12 for human and 13 for mouse. There is the 6th in the mouse lumber vertebrae while the human lumber vertebrae has only 5. The sacrum of adult human is a single accrete bones, while sacrum of mouse consists of 4 separate bones. The pair of radius and ulna are separate for human, and accrete as a single body for mouse. The similar relationship is found for the pair of tibia and fibula. They are separate for human, and accrete for mouse. The other components in the two skeletal systems have one-to-one correspondence. In this paper, we consider mapping between bones with one-to-one correspondence and with many-to-one correspondence. We do not consider Yoshihiko Nakamura, Yosuke Ikegami, Akihiro Yoshimatsu, Ko Ayusawa, Hirotaka Imagawa, and Satoshi Oota / Procedia IUTAM 00 (2011) 1–9 4

Landmark of Left Femur Bone

head of femur fovea C1-C7 neck of femur

great trochanter trochanteric fossa T1-T13 inter trochanter Human:12) lesser trochanter third trochanter (4)

body of femur (2) L1-L6 Human:5)

medial condyle (2) S1-S4 lateral condyle (2)

CA1-CA25 Human:3-5)

Human Mouse

Fig. 4: Conﬁguration of Mouse Vertebrae: C, T, L, S and CA indicates Fig. 5: Landmarks of human and mouse femur bone cervical, thoracic, lumbar, sacral, and caudal bones, respectivrly tailbones and two bones missing in the human thoracic and lumbar vertebrae. The systematic modeling of missing components must be discussed in more details taking account of evolutional morphology.

3. From Human to Mouse

3.1. The Mechanostat Theory The Mechanostat Theory is suggested by the Wolff’s law [24] and by Frost [25]. The theory describes that the geometry of an animal bone is determined by stress applied to the bone, typically by stress due to muscle tension and the gravitation. According to the Mechanostat Theory, the homology of geometry implies the homology of biomechanical function. The biomechanical functional points are determined by in the relation to the anatomical landmarks. On a pair of corresponding bones of human and mouse, we search for corresponding anatomical landmarks and define them as the landmarks of the pair. The other landmarks include such geometric points as the centers of the heads of humerus and femur, which are not necessarily on the surface of bones. Since the two skeletal systems show high homology, we propose to find the mapping function f : L → L0 as a set of mappings of the landmarks, where L and L0 are the sets of the landmarks of human and mouse respectvely. The coordinates of the origins, insertions, and via points of muscles, tendons, ligaments, and cartilages of the human musculoskeletal system are transferred by the mapping function onto the surfaces of the muscle skeletal system. We define the element points as the origins, insertions, and via points of muscles, tendons, ligaments, and cartilages. There are many possible constructions of the mapping function, one of which is to be discussed in the following subsection. Note that the precision of correspondence is limited between the mapped musculotendinous system and the real musculotendious system of mouse and that we will need careful refinements after the mapping.

3.2. The Skeletal Subspace Deformation The Skeletal Subspace Deformation (SSD) was proposed by Lewis et al.[26][27] and commonly used for production of animation including polygon reshaping. The manipulation points that influence the vertices of the polyhedron are first defined and the weights of influence are set taking account of the initial distances. The new positions of vertices are computed from the relative movement of the manipulation points. In production of CG animation, the Yoshihiko Nakamura, Yosuke Ikegami, Akihiro Yoshimatsu, Ko Ayusawa, Hirotaka Imagawa, and Satoshi Oota / Procedia IUTAM 00 (2011) 1–9 5

Link Ni Element Point E Σlj k Landmark j P eik iP Landmark j’ Link N’ eik i Σ’lj P lij P’ P lij vim Σi Element Point Ek’

P’ eik iP’ eik P’ vim Σw Σ’i

Fig. 6: Morphing by the skeletal subspace deformation (SSD): anatomical landmarks and element points manipulation points are selected at the joints of the CG character to provide natural deformation and posture of the character. We choose the landmarks of a bone or a body of accrete bones as the manipulation points of the SSD. The polyhedra of the human skeletal system are deformed by moving the manipulation points from the positions of the landmarks of the human skeletal system to those of the mouse skeletal system. The positions of the element points of the human musculotendinous system are consequently mapped to their new positions in the relation to the landmarks. The new positions are the candidates of the element points of the mouse musculotendinous system.

3.3. Bone Morphing

A link is represented by a polyhedron. The world coordinate system Σw is deﬁned and used to describe the coordinates of all the points. The set of landmarks of the ith link is given by Li = { j}, j ∈ {1, ..., nil}. We picked up the landmarks according to Itai et al. [4]. A pair of landmarks are deﬁned in one-to-one relationship and on the corresponding pair of links. The mth vertex of the ith link is described by the extended expression such as = T T ∈ 4 0 vim [pvim 1] R . The mth vertex of the ith link, vim, is tranferred by mapping function f to 0 = vim fim(vim) (1) where the mapping function is represented by ∑ −1 f (v ) = w T 0 (T ) v (2) m im im j li j li j im j∈Li

Ti implies the homogenous transformation matrix representing the position and orientation of the link coordinates of the ith link and the scale factor, where the orientation and the scale factor are manually adjusted for closer matching of polygonal surfaces. The weight function wim j is deﬁned according to the distance between a landmark and the mth vertex of the ith link, and satisﬁes the following constraints: ∑ wim j = 1 (3)

j∈Li

3.4. Mapping the element points The element points are transferred by the above mapping function to

0 = eik fik(eik) (4) = T T ∈ 4 where the element points are represented by the extended expression, namely eik [peik 1] R . Yoshihiko Nakamura, Yosuke Ikegami, Akihiro Yoshimatsu, Ko Ayusawa, Hirotaka Imagawa, and Satoshi Oota / Procedia IUTAM 00 (2011) 1–9 6

Fig. 7: Morphed human skeletal system Fig. 8: Mapped musculotendinous system

3.5. Mapping on virtual links The concept of the virtual links was introduced to represent the connection of muscle and tendon and the bifurcation of muscles in consistent with the computational algorithm of multibody dynamics. Virtual links are commonly floating links. The points of virtual links are represented in the influence of the landmarks of multiple bones. Let the set of bones that influence a virtual link be represented by Ω = {p, q, ...r}. Then, the set of the landmarks Lv that influence the virtual link is represented by the following equation.． ∪ Lv = Ls = {u} (5) s∈Ω

By representing an element of the newly deﬁned set Lv by u, point evd of a virtual link is transferred by the mapping function to

0 = evd fvd(evd) (6) = T T ∈ 4 where evd [pevd 1] R .

3.6. The set of landmarks of femur One ﬁnds many common names of anatomical landmarks in pairs of corresponding bones of human and mouse. We selected some of them according to human anatomy [8] and a recent literature [4] on the mouse skeletal system obtained by X-ray CT scanning. An example of the set of landmarks are shown for femur in Fig.2. We selected 17 femoral landmarks, which are classiﬁed into four types. Namely, (1) Point Type, (2) Line Type, (3) Fossa/Crest Type, and (4) Center-of-Sphere Type. The landmarks are used as the manipulation points of the SSD. The human femur was then transformed to the mouse femur by the morphing. The transformed shape of the human femur is illustrated in Fig.5. Note that the surface of a polyhedra may collapse or be distorted by the SSD depending on the choice of the manipulation points. When they occurred, we manually adjusted orientation and scales to obtain smooth transformation.

4. Muscle Length Analysis of Mouse Locomotion

The measurements of mouse locomotion was done using an optical motion capture system. Four EAGLE cameras and one EAGLE-EYE camera of Motion Analysis Inc. were used to observe nine markers of 2.4 mm in diameter at Yoshihiko Nakamura, Yosuke Ikegami, Akihiro Yoshimatsu, Ko Ayusawa, Hirotaka Imagawa, and Satoshi Oota / Procedia IUTAM 00 (2011) 1–9 7

Fig. 9: Nine markers on a mouse Fig. 10: Mouse on the bridge Fig. 11: Fifteen markers on a nude mouse the rate of 120 fps. In the first measurements, a normal hairy mouse was shaved under anesthesia to attach the nine markers as shown in Fig.9. The mouse wakened from anesthesia and unforcedly moved downward on the inclined bridge as shown in Fig.10. The bridge was 87 mm wide and 910 mm long with 18 degree inclined. The inverse kinematics was solved from the position data of the nine markers by the least square optimization to minimize errors with the markers on the skeletal model. The skeletal model has total 121 DOF including 37 spherical joints (3DOF each), 4 rotational joints (1DOF each), and 1 free joint (6DOF). The change of muscle lengths were computed and shown in the gradation of colors in Fig.12. The labeling after motion capturing was not done very reliable manner because of remaining hair, which resulted in rather stiff motion. In the second measurements, we used a mutant nude mouse in the same conditions otherwise. We used 15 markers attached to the skin without stressing the mouse by shaving as shown in Fig.11. We adopted the same 121 DOF skeletal model. The labeling was successfully done and we obtained much smoother data. The graph of muscle length analysis is shown in Fig.13. The graph shows the curves of muscle lengths for six major muscles of lower limbs, namely, gluteus maximus, rectus femoris, semimembranosus, tibialis anterior, gastrocnemius, and soleus. The markers as small as 2.4 mm in diameter are still heavy for a mouse. More markers are necessary for measuring more natural motions, which must be done by developing smaller and lighter makers. The dynamics force analysis is possible using the musculoskeletal model. For this analysis, we need to (1) set up a force sensing environments for contact force measurement, and (2) identify the mass properties of body segments of mouse. The results of musculotendinous morphing must be evaluated by comparing with the segmented volume data obtained from X-ray CT scanning of mouse. For in vivo identification of mass property of the body segments, Venture et al.[14][16][17], and Ayusawa et al.[15] [18] off-line and on-line algorithms assuming motion capturing and contact force sensing with force plates. They even showed that motion capturing in the air without contact force measurements can make mass property identification. The computational algorithm we developed for estimating muscle activities of the human musculoskeletal system can be applied[10][12][11][13], though the scale difference would need careful investigation for reliable and mean- ingful measurements. The authors also investigate estimation of activities of the neuromuscular system based on the muscle activites[19][20], which would be useful to study the pathway from neural disorder to behavioral disorder. The post-genome phenotype study would also require mathematical and biomechanical means to evaluate neuromuscular activities in a quantitative manner.

5. Conclusion

In this paper we discussed a systematic method to construct the musculotendinous model of mouse. through geometric morphing between the human skeletal system and the skeletal system of mouse. The musculotendinous model of mouse was constructed from that of human based on the homology of the two species. The muscle length analysis was conducted using the motion capture data. Further technical developments must be done. They include (1) evaluation of the obtained musculotendinous model in comparison with the segmented volume data of a real mouse, (2) development of small and light markers, (3) force sensing environments for measuring contact forces, (4) identiﬁcation of mass properties of body segments. Yoshihiko Nakamura, Yosuke Ikegami, Akihiro Yoshimatsu, Ko Ayusawa, Hirotaka Imagawa, and Satoshi Oota / Procedia IUTAM 00 (2011) 1–9 8

t =0.00 (s) t =0.04 (s) t =0.08 (s)

t =0.13 (s) t =0.17 (s) t =0.21 (s)

t =0.25 (s) t =0.29 (s) t =0.33 (s)

t =0.38 (s) t =0.42 (s) t =0.46 (s)

t =0.50 (s) t =0.54 (s) t =0.58 (s)

t =0.63 (s) t =0.67 (s) t =0.71 (s)

Fig. 12: Muscle length analysis of locomotion (a hairy mouse)

The biomechanical studies of behavioral phenotype of knockout laboratory mouse will provide the scientific research tool for post genome research. Foe example, studies with knockout model mouse of Parkinson disease may dis- cover the whole pathway from the genetic disorders to neuro musculoskeletal disorders. Since the proposed approach is general and systematic, it can be extended to construct the other mammalian species. The models if constructed for extinct species and our evolutional ancestors would provide biomechanical means for the fields of evolutional biology. This work was supported by Grant-in-Aid for Scientific Research (S) (20220001) of the Japan Society for the Promotion of Science.

References

[1] R. H. Waterson, et al., Initial sequencing and comparative analysis of the mouse genome, Nature 420 (6915) (2002) 520–562. [2] Mouse genom informatics. http://www.informatics.jax.org/ [online] (2010). [3] J. W. Gordon, G. A. Scangos, D. J. Plotkin, et al., Genetic transformation of mouse embryos by microinjection of puriﬁed dna, in: Proc. of National Academy of Sciences of the United Status of America, Vol. 77, 1980, pp. 7380–7384. [4] I. Bab, C. Hajbi-Yonissi, Y. Gabet, R. Muller, Micro-Tomographic Atlas of the Mouse Skeleton, Springer, 2007. [5] T. Lelarda, M. Jamonc, J. P. Gascb, P. P. Vidal, Postural development in rats, Experimental Neurology 202 (1) (2006) 112–124. [6] S. Oota, K. Mekada, Y. Fujita, J. Humphpheries, K. Fukami-Kobayashi, Y. Obata, T. Rowe, A. Yoshiki, Four-dimensional quantitative analysis of the gait of mutant mice using coarse-grained motion capture, Proc. of IEEE EMBS Annual International Conference (2009) 5227–5230. [7] S. Oota, A. Yoshiki, Y. Fujita, J. Humpheries, K. Fukami-Kobayashi, Y. Obata, T. Rowe, Y. Nakamura, Development of a coase-grained skeletal model of laboratory mouse and its application, Proc. of 1st Int’l Conf. on Applied Bionics and Biomechanics. [8] C. D. Clemente, Anatomy A Regional Atlas of the Human Body, Lippincott Williams & Wilkins, 2007. [9] S. Itoh, Y. Yokokohji, Function analysis of intrinsic muscles of human hand based on musculo-skeletal model, Annual Conference of the Robotics Society of Japan (Japanese) (2010) AC2O2. [10] Y. Nakamura, K. Yamane, I. Suzuki, Y. Fujita, Dynamic computation of musculo-skeletal human model based on eﬃcient algorithm for closed kinematic chains, Proc. of the 2nd International Symposium on Adaptive Motion of Animals and Machines (2003) SaP–I–2. [11] Y. Nakamura, K. Yamane, I. Suzuki, Y. Fujita, Somatosensory computation for man-machine interface from motion capture data and musculoskeletal human model, IEEE Transactions on Robotics 21 (2005) 58–66. Yoshihiko Nakamura, Yosuke Ikegami, Akihiro Yoshimatsu, Ko Ayusawa, Hirotaka Imagawa, and Satoshi Oota / Procedia IUTAM 00 (2011) 1–9 9

-3 x 10 GluteusMaximus TibialisAnterior

LeftGluteusMaximus LeftTibialisAnterior 9 RightGluteusMaximus RightTibialisAnterior

8 0.016

6 0.014 Muscle Length[m] Muscle Length[m] 5 0 2 4 6 8 10 0 2 4 6 8 10 Time[s] Time[s]

RectusFemoris Gastrocnemius

LeftGastrocnemius 0.012 0.014 RightGastrocnemius

0.011 0.013

0.01 0.012

0.009 LeftRectusFemoris 0.011 RightRectusFemoris Muscle Length[m] Muscle Length[m] 0.008 0.01 0 2 4 6 8 10 0 2 4 6 8 10 Time[s] Time[s]

Semimembranosus Soleus

LeftSemimembranosus LeftSoleus 0.014 RightSemimembranosus 0.013 RightSoleus

0.013 0.012

0.012 0.011

0.011 0.01 Muscle Length[m] Muscle Length[m] 0.01 0.009 0 2 4 6 8 10 0 2 4 6 8 10 Time[s] Time[s]

Fig. 13: Muscle length analysis of locomotion (a mutant nude mouse)

[12] K. Yamane, Y. Fujita, Y. Nakamura, Estimation of physically and physiologically valid somatosensory information, Proc. of IEEE Interna- tional Conference on Robotics and Automation (2005) 2635–2641. [13] Y. Nakamura, K. Yamane, A. Murai, Macroscopic modeling and identification of the human neuromuscular network, Proc. of IEEE EMBS Annual International Conference (2006) 99–105. [14] G. Venture, K. Ayusawa, Y.Nakamura, Human and humanoid identification from base-link dynamics, Proc. of IEEE RAS/EMBS International Conference on Biomedical Robotics and Biomechatronics (2008) 445–450. [15] K. Ayusawa, G. Venture, Y. Nakamura, Identification of humanoid robots dynamics using floating-base motion dynamics, Proc. of IEEE/RSJ International Conference on Intelligent Robots and Systems (2008) 2854–2859. [16] G. Venture, K. Ayusawa, Y. Nakamura, Real-time identification and visualization of human segment parameters, Proc. of IEEE EMBS Annual International Conference (2009) 3983–3986. [17] G. Venture, K. Ayusawa, Y. Nakamura, Identification of human mass properties from motion, Proc. of 15th IFAC Symposium on Systems Identification (2009) 988–993. [18] K. Ayusawa, G. Venture, Y. Nakamura, Symbolic proof of inertia-parameter identifiability of legged mechanisms from unactuated base-link dynamics, Proc. of 15th IFAC Symposium on Systems Identification (2009) 693–698. [19] A. Murai, K. Yamane, Y. Nakamura, Modeling and identifying the somatic reflex network of the human neuromuscular system, Proc. of IEEE EMBS Annual International Conference (2007) 2717–2721. [20] A. Murai, Y. Katsu, Y. Nakamura, Characterization of motor skill based on musculoskeletal model, Proc. of IEEE EMBS Annual International Conference. [21] The viewpoint medical products: Veiwpoint corporation. http://www.viewpoint.com/ [online] (2002). [22] G. G. Simpson, The principles of classification and a classification of mammals, Bulletin of the American Museum of Natural History 85 (1945) 1–350. [23] The tree of life web project. http://tolweb.org/tree/phylogeny.html [online]. [24] H. Roesler, Some historical remarks on the theory of cancellous bone structure (wolff’s law), Mechanical Properties of Bone 15 (1981) 27–42. [25] H. M. Frost, Skeletal structural adaptations to mechanical usage (satmu): 1. redefining wolff’s law: the bone modeling problem, The Anatom- ical Record 4 (226) (1990) 403–413. [26] J. P. Lewis, M. Cordner, N. Fong, Pose space deformation: A unified approach to shape interpolation and skeleton-driven deformation, Proc. of SIGGRAPH 2000 (2000) 165–172. [27] F. Liu, R. Liang, D. Ye, Skeleton subspace deformation with displacement map, Proc. of EUROGRAPHICS 2003 (2003) 165–170.