Advanced Robotics to Address the Translational Gap in Tendon Engineering.

Tendon disease is a significant and growing burden to healthcare systems. One strategy to address this challenge is tissue engineering. A widely held view in this field is that mechanical stimulation provided to constructs should replicate the mechanical environment of native tissue as closely as possible. We review recent tendon tissue engineering studies in this article and highlight limitations of conventional uniaxial tensile bioreactors used in current literature. Advanced robotic platforms such as musculoskeletal humanoid robots and soft robotic actuators are promising technologies which may help address translational gaps in tendon tissue engineering. We suggest the proposed benefits of these technologies and identify recent studies which have worked to implement these technologies in tissue engineering. Lastly, key challenges to address in adapting these robotic technologies and proposed future research directions for tendon tissue engineering are discussed.

The effect of mono- versus multi-segment musculoskeletal models of the foot on simulated triceps surae lengths in pathological and healthy gait.

BACKGROUND: Estimating muscle-tendon complex (MTC) lengths is important for planning of soft tissue surgery and evaluating outcomes, e.g. in children with cerebral palsy (CP). Conventional musculoskeletal models often represent the foot as one rigid segment, called a mono-segment foot model (mono-SFM). However, a multi-segment foot model (multi-SFM) might provide better estimates of triceps surae MTC lengths, especially in patients with foot deformities. RESEARCH QUESTION: What is the effect of a mono- versus a multi-SFM on simulated ankle angles and triceps surae MTC lengths during gait in typically developing subjects and in children with CP with equinus, cavovarus or planovalgus foot deformities? METHODS: 50 subjects were included, 10 non-affected adults, 10 typically developing children, and 30 children with spastic CP and foot deformities. During walking trials, marker trajectories were collected for two marker models, including a mono- and multi-segment foot; respectively Newington gait model and Oxford foot model. Two musculoskeletal lower body models were constructed in OpenSim with either a mono- or multi-SFM based on the corresponding marker models. Normalized triceps surae MTC lengths (soleus, gastrocnemius medialis and lateralis) and ankle angles were calculated and compared between models using statistical parametric mapping RM-ANOVAs. Root mean square error values between simulated MTC lengths were compared using Wilcoxon signed-rank and rank-sum tests. RESULTS: Mono-SFM simulated significantly more ankle dorsiflexion (7.5 ± 1.2°) and longer triceps surae lengths (difference; soleus:2.6 ± 0.29 %, gastrocnemius medialis:1.7 ± 0.2 %, gastrocnemius lateralis:1.8 ± 0.2%) than a multi-SFM. Differences between models were larger in children with CP compared to typically developing children and larger in the stance compared to the swing phase of gait. Largest differences were found in children with CP presenting with planovalgus (4.8 %) or cavovarus (3.8 %) foot deformities. SIGNIFICANCE: It is advisable to use a multi-SFM in musculoskeletal models when simulating triceps surae MTC lengths, especially in individuals with planovalgus or cavovarus foot deformities.

Anatomical masking of pressure footprints based on the Oxford Foot Model: validation and clinical relevance.

Plantar pressure analysis is widely used in the assessment of foot function. In order to assess regional loading, a mask is applied to the footprint to sub-divide it into regions of interest (ROIs). The most common masking method is based on geometric features of the footprint (GM). Footprint masking based on anatomical landmarks of the foot has been implemented more recently, and involves the integration of a 3D motion capture system, plantar pressure measurement device, and a multi-segment foot model. However, thorough validation of anatomical masking (AM) using pathological footprints has not yet been presented. In the present study, an AM method based on the Oxford Foot Model (OFM) was compared to an equivalent GM. Pressure footprints from 20 young healthy subjects (HG) and 20 patients with clubfoot (CF) were anatomically divided into 5 ROIs using a subset of the OFM markers. The same foot regions were also identified by using a standard GM method. Comparisons of intra-subject coefficient of variation (CV) showed that the OFM-based AM was at least as reliable as the GM for all investigated pressure parameters in all foot regions. Clinical relevance of AM was investigated by comparing footprints from HG and CF groups. Contact time, maximum force, force-time integral and contact area proved to be sensitive parameters that were able to distinguish HG and CF groups, using both AM and GM methods However, the AM method revealed statistically significant differences between groups in 75% of measured variables, compared to 62% using a standard GM method, indicating that the AM method is more sensitive for revealing differences between groups.