The blenderFace method: video-based measurement of raw movement data during facial expressions of emotion using open-source software

Pedagogical impact of integration of musculoskeletal anatomy blended learning on physiotherapy education

Background

In physiotherapy education, blended learning is recognized to be more effective compared to traditional teaching. The aim of this study was to assess the consequences of a musculoskeletal anatomy blended learning program on skills developed by students.

Methods

We conducted an observational retrospective monocentric study in a French physiotherapy school named "X." Ninety-two first-year students in the 2017-18 baseline group (students with traditional face-to-face learning), and ninety-eight first-year students and ninety-five second-year students in the 2018-19 and 2019-20 blended learning experimental groups was included. A success rate of the anatomy final written exam, defined by the percentage of students scoring 50% or above, was analyzed between 2017 and 2020. We also evaluated the pedagogical value of musculoskeletal e-learning and its usefulness for preparing the student for their anatomy final written exam at «X».

Results

We observed an improvement in the success rate of the anatomy final written exam between the 2017-18 baseline group, 2018-19 and 2019-2020 experimental groups during first (Kruskal-Wallis = 74.06, df = 2, p < 0.001) and second semester (Kruskal-Wallis = 173.6, df = 2, p < 0.001). We obtained a data survey and questionnaire response rate of 74% (n = 89/120) for the 2018-19 and 62% (n = 72/116) for the 2019-20 experimental groups. Concerning questionnaire response, they were no significant statistical difference between 2018-19 and 2019-20 experimental groups.

Conclusion

Blended learning could improve student success rate of the anatomy final written exam and learning of professional physiotherapy skills.

Quantified analysis of facial movement: A reference for clinical applications

Most techniques for evaluating unilateral impairments in facial movement yield subjective measurements. The objective of the present study was to define a reference dataset and develop a visualization tool for clinical assessments. In this prospective study, a motion capture system was used to quantify facial movements in 30 healthy adults and 2 patients. We analyzed the displacements of 105 reflective markers placed on the participant's face during five movements (M1-M5). For each marker, the primary endpoint was the maximum amplitude of displacement from the static position (M0) in an analysis of variance. The measurement precision was 0.1 mm. Significant displacements of markers were identified for M1-M5, and displacement patterns were defined. The patients and age-matched healthy participants were compared with regard to the amplitude of displacement. We created a new type of radar plot to visually represent the diagnosis and facilitate effective communication between medical professionals. In proof-of-concept experiments, we collected quantitative data on patients with facial palsy and created a patient-specific radar plot. Our new protocol for clinical facial motion capture ("quantified analysis of facial movement," QAFM) was accurate and should thus facilitate the long-term clinical follow-up of patients with facial palsy. To take account of the limitations affecting the comparison with the healthy side, we created a dataset of healthy facial movements; our method might therefore be applicable to other conditions in which movements on one or both sides of the face are impaired. The patient-specific radar plot enables clinicians to read and understand the results rapidly.