**2.3. Biomechanical data acquisition and measurement processing**

The standard trial session aims to completely define the subject's posture both in the ortho‐ static position and in simple or complex dynamic conditions. Each static postural attitude is considered correctly recorded when at least five, 2‐s lasting, acquisitions are performed. Given the GOALS system data acquisition rate depending on the hardware configuration, we can have rates starting from 100 up to 360 Hz); this means that a minimum of 1000 measure‐ ments are averaged per each static postural stance [6–8, 27–31]. Before averaging, an amount of pre‐processing is needed on the acquired 3D raw data in order to comply with clinical analysis requirements.

Once the 3D skeleton reconstruction is obtained, it is possible to compute, on the derived model, all the clinical parameters that are generally calculated on the radiographic image and used for the correct description and biomechanical characterization of spinal pathology (i.e. Cobb and kypho‐lordotic angles).

Moreover, a set of significant biomechanical variables describing the three‐dimensional nature of body posture are obtained. To describe trunk and global unbalancing, spinal offset and global offset (i.e. displacements of each spine markers with respect to the vertical line passing through the S3 vertebra and with respect to the vertical line passing through the middle point between the heels, respectively) are used [6–8, 27–31]. Both global and spinal offset values are finally averaged to obtain descriptive data that summarize these parameters (**Figure 6**).

Other parameters include pelvis frontal and sagittal inclinations, pelvis torsion, shoulder‐ to‐pelvis, pelvis‐to‐heels and shoulder‐to‐heels horizontal rotations (**Figure 7**), joint forces, joint torques and several more. The 49 markers set can be used not only for gait or movement measurements but it can be very useful when deeper information about lower limbs seg‐ mental posture is sought (intra‐extra rotations, ab‐adductions flexion‐extension). In fact, in this way the posture measurements are complemented by the pose of each lower limb chain segment enlightening joint adaptations, anomalies and/or weakness.

Our studies as well as our clinical experience led us to identify a set of static attitudes (such as indifferent orthostasis—that is, neutral erect standing—with and/or without an underfoot

**Figure 6.** (a) From left to right: automatic identification of frontal plane spinal curves, related Cobb angular values and spinal offsets with respect to the vertical line passing through S3; (b) full 3D skeleton posture reconstruction (frontal and sagittal views), including global offsets computation and visualization.

A 3D Spine and Full Skeleton Model for Opto-Electronic Stereo-Photogrammetric Multi-Sensor... http://dx.doi.org/10.5772/intechopen.68633 29

**2.3. Biomechanical data acquisition and measurement processing**

analysis requirements.

Cobb and kypho‐lordotic angles).

28 Innovations in Spinal Deformities and Postural Disorders

The standard trial session aims to completely define the subject's posture both in the ortho‐ static position and in simple or complex dynamic conditions. Each static postural attitude is considered correctly recorded when at least five, 2‐s lasting, acquisitions are performed. Given the GOALS system data acquisition rate depending on the hardware configuration, we can have rates starting from 100 up to 360 Hz); this means that a minimum of 1000 measure‐ ments are averaged per each static postural stance [6–8, 27–31]. Before averaging, an amount of pre‐processing is needed on the acquired 3D raw data in order to comply with clinical

Once the 3D skeleton reconstruction is obtained, it is possible to compute, on the derived model, all the clinical parameters that are generally calculated on the radiographic image and used for the correct description and biomechanical characterization of spinal pathology (i.e.

Moreover, a set of significant biomechanical variables describing the three‐dimensional nature of body posture are obtained. To describe trunk and global unbalancing, spinal offset and global offset (i.e. displacements of each spine markers with respect to the vertical line passing through the S3 vertebra and with respect to the vertical line passing through the middle point between the heels, respectively) are used [6–8, 27–31]. Both global and spinal offset values are finally averaged to obtain descriptive data that summarize these parameters (**Figure 6**).

Other parameters include pelvis frontal and sagittal inclinations, pelvis torsion, shoulder‐ to‐pelvis, pelvis‐to‐heels and shoulder‐to‐heels horizontal rotations (**Figure 7**), joint forces, joint torques and several more. The 49 markers set can be used not only for gait or movement measurements but it can be very useful when deeper information about lower limbs seg‐ mental posture is sought (intra‐extra rotations, ab‐adductions flexion‐extension). In fact, in this way the posture measurements are complemented by the pose of each lower limb chain

Our studies as well as our clinical experience led us to identify a set of static attitudes (such as indifferent orthostasis—that is, neutral erect standing—with and/or without an underfoot

**Figure 6.** (a) From left to right: automatic identification of frontal plane spinal curves, related Cobb angular values and spinal offsets with respect to the vertical line passing through S3; (b) full 3D skeleton posture reconstruction (frontal and

segment enlightening joint adaptations, anomalies and/or weakness.

sagittal views), including global offsets computation and visualization.

**Figure 7.** (a) Frontal spinal angles, pelvis orientation and torsion as derived by the relative position of PSIS and ASIS landmarks; (b) leftward and rightward lateral‐bending tasks performed by a scoliotic subject.

wedge, self‐corrected manoeuvres, ante‐retroversion static postural exercises and sitting pos‐ ture), which can provide a complete documentation of subject postural, balancing and mor‐ phological characteristics. As for static posture, also for gait the possibility to extract the mean gait cycle characteristics has been considered and developed.

The mathematical details for the optimization of the procedure as well as the average gait cycle computation are beyond the limits of this chapter [8, 27, 28].

The final outcome is the mean gait cycle in which the average time course and associated standard deviation is defined per each variable of interest [8, 27, 28, 31]. Two main advantages can be enu‐ merated with the possibility to extract the mean characteristics of both static posture and cyclic motor task (gait): first, it allows to overcome the single measurements analysis limits by taking into account the ensemble behaviour improving the statistical reliability of the evaluation; second, it permits to obtain information about the repeatability and variability of the performed motor task, thus enlightening the subject's motor control capability. For the graphical representation as well as clinical parameter visualization and enlightening, a software package (named ASAP 3D Skeleton Model©) based on 3D graphic modelling has been developed. This latter is now available as a commercial software package (Bioengineering & Biomedicine Company S.r.l. Italy).
