###### Abstract
[PERSON] also recommended a geodesic, close packing and hierarchical spine model using tensegrity mast. More information about spinal tensegrity mast models can be found in [11]. Configurations of biotensegrity have been proposed through form-finding process by solving complex geometrical inputs and forces [12]. The first physical biotensegrity model that mimics living cells, namely cellular tensegrity model, was built with the spherical central nucleus [13]. Thereafter, mathematical modeling with various cellular models using regular tensegrities were studied [12]. Many have claimed excellent prediction of cellular mechanistic properties through cellular tensegrity models [5; 6; 14]. However, the major limitation of these models lies in the use of simple configurations to represent the complex structure in nature [11]. Despite the fact that the basic mathematical formulation to express the mechanical models for biotensegrity has achieved a  
Figure 1: Motivation of the study. certain maturity, many of the investigations focused extensively on cellular tensegrity models [6; 12]. In this study, a form-finding of biotensegrity models to specifically represent the complex living organism at a higher hierarchy is addressed. There are many established form-finding strategies on tensegrity structures, which have been classified as kinematical and statical methods [15]. A force density-based analytical form-finding method was applied for regular tensegrity structures by group elements [16]. Form-finding method combining symmetry-based qualitative analysis with particle swarm optimization for symmetric tensegities and prestressed cable-strut structures was proposed [17]. A method using strut finite element and unconstrained nonlinear programming for form-finding of hyper-elastic tensegrity structures was studied [18]. A nonlinear programming approach for form-finding of tensegrity structures by using fictitious materials properties was presented [19]. An optimization method to generate nodal coordinates of super-stable tensegrity structures with known connectivity data and force densities was proposed [20]. Form-finding analysis of an asymmetric large deployable antenna using a force density-based optimization algorithm was carried out [21]. A form-finding method whereby a fully automatic labeling of elements through a double-loop genetic algorithm was used [22]. A modified dynamic relaxation algorithm for the form-finding of tensegrity robots in task space was proposed [23]. Many of the investigations mentioned above were aimed at finding new configurations of tensegrity subjected to different constraints or optimization criteria. This paper presents form-finding strategies for spine biotensegrity models. The remainder of the paper is organized as follows: Section 2 defines the geometry of the spine biotensegrity models that are based on key parameters from human spine vertebrae and natural sagittal curvature. Section 3 presents the search strategies for form-finding of self-equilibrated configuration of the spine biotensegrity models adopted in this study. Section 4 discusses form-finding results of spine biotensegrity models using the algorithm proposed. Lastly, the conclusions are presented in Section 5.