Quantification of facial movements by motion capture

DeepSmile: Anomaly Detection Software for Facial Movement Assessment

Facial movements are crucial for human interaction because they provide relevant information on verbal and non-verbal communication and social interactions. From a clinical point of view, the analysis of facial movements is important for diagnosis, follow-up, drug therapy, and surgical treatment. Current methods of assessing facial palsy are either (i) objective but inaccurate, (ii) subjective and, thus, depending on the clinician's level of experience, or (iii) based on static data. To address the aforementioned problems, we implemented a deep learning algorithm to assess facial movements during smiling. Such a model was trained on a dataset that contains healthy smiles only following an anomaly detection strategy. Generally speaking, the degree of anomaly is computed by comparing the model's suggested healthy smile with the person's actual smile. The experimentation showed that the model successfully computed a high degree of anomaly when assessing the patients' smiles. Furthermore, a graphical user interface was developed to test its practical usage in a clinical routine. In conclusion, we present a deep learning model, implemented on open-source software, designed to help clinicians to assess facial movements.

Occlusion trajectory and a concept of a device for testing operating life of dentures

PURPOSE

This paper presents an original method for the assessment of occlusion trajectory. On this basis, a special device for the assessment of operating life of dentures was designed.

MATERIAL/METHODS

For this purpose, the SMART system by BTS for a comprehensive movement analysis was used. In order to analyze occlusion trajectory, characteristic points on patients' heads were appointed in which markers were placed, in accordance with the rules of measurement in dentistry. Markers' movement was recorded by means of 6 cameras, and then composition of coordinates was performed in a 3D system.

RESULTS

In this way, curves representing movements of the characteristic points were plotted which, after the composition, with a considerable approximation, can be regarded as occlusion trajectory.

CONCLUSIONS

On the basis of the obtained results, a thesis was put forward to the effect that traditional tribological testing machines based on systems of the pin-on-disc, ball-on-disc, etc. types, due to the simplicity of their working movements, are not adequately precise for the purpose of operational assessment of elements of prosthodontics. On this basis, a tribological node for a specialist testing machine for the assessment of operating life of dentures was designed.

Computational and experimental characterization of skin mechanics: identifying current challenges and future directions

The characterization of skin mechanics has many clinical implications and has been an active area of research for the past few decades. Biomechanical models have evolved from earlier empirical models to state-of-the-art structural models that provide linkage between tissue microstructure and macroscopic stress-strain response. To maximize the accuracy and predictive capabilities of such computational models, there is a need to reliably identify often a large number of unknown model parameters. This is critically dependent on the availability of experimental data that cover an extensive range of different deformation modes, and quantification of internal structural features, such as collagen orientation. To this end, future challenges should include the ongoing development of noninvasive instrumentation and imaging modalities for in vivo skin measurements. We highlight the important concept of tightly integrating computational models, instrumentation, and imaging modalities into a single platform to investigate skin biomechanics.