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

Impact of the Covid-19 pandemic and lockdowns on the education and mental health of physiotherapy students in France: a descriptive cross-sectional study with national online survey

International audienceObjective: To determine the impact of the SARS-CoV-2 (COVID-19) pandemic and lockdowns on the mental health status, training, perceptions of the physiotherapy profession, and career plans of French physiotherapy students. Design: A descriptive cross-sectional study was conducted, representing the first and only survey of its kind, using a national online survey. Subjects: A total of 2678 French physiotherapy students participated in the study. Methods: Mental health status was assessed using the validated French versions of established depression, anxiety, and insomnia scales. Results: The survey revealed that female sex, age below 21 years, living alone, and having a psychiatric history or COVID-19 risk factors were associated with more severe symptoms of depression, anxiety, and insomnia in the surveyed students. In addition, stress, anxiety, and depression induced by the COVID-19 crisis were linked to apprehension about continuing practical training in physiotherapy. These factors also affected students’ perceptions of the profession and the initially envisioned mode of practice, particularly among fifth-year students (odds ratio (OR) = 2.25, 95% confidence interval (95% CI) = (1.69, 2.99), p < 0.001). Notably, the pandemic significantly reduced the desire of these students to pursue a career as physiotherapists (adjusted OR (aOR) 1.41 (1.06, 1.86)). Conclusion: French physiotherapy students, especially those in their fifth year, have experienced significant impacts from the COVID-19 pandemic, affecting their mental health, education, perceptions of the physiotherapy profession, and career plans

Optimal marker set assessment for motion capture of 3D mimic facial movements

International audienc

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 visualisation 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 analysed 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

Réponses rapides dans le cadre du COVID-19 – Mesures et précautions essentielles pour le masseur-kinésithérapeute auprès des patients à domicile

La méthode retenue pour cette réponse rapide est basée sur une synthèse des données probantes disponibles les plus pertinentes, les recommandations nationales et internationales, ainsi que sur une consultation des parties prenantes. Ce document a été élaboré collégialement entre la HAS, le Conseil national de l’ordre des masseurs-kinésithérapeutes et les référents des CNP et sociétés savantes : CMK, GKR-SPLF, SFP, SKR. Validation par le collège de la HAS en date du 16 avril 2020

Abstracts of the 9th International Organisation of Physical Therapy in Mental Health Conference

This book contains the abstracts of the papers presented at the 9th International Organisation of Physical Therapy in Mental Health Conference, Organized by the International Organisation of Physical Therapy in Mental Health and Greek Scientific Section “Physiotherapy in Mental Health” of PanHellenic Physiotherapists’ Association, held on 4–6 May 2022. It is the biannual conference of the International Organization of Physical Therapy in Mental Health (IOPTMH), and we answered with success the question: Physiotherapy in mental health; what’s next? The highly qualified scientific program, the reputable presenters, and the venue altogether form a powerful motivation for both physiotherapists and other mental health professionals to attend this conference. Conference Title: 9th International Organisation of Physical Therapy in Mental Health ConferenceConference Theme: Physiotherapy in mental health; what’s next?Conference Date: 4–6 May 2022Conference Location: Crowne Plaza Athens - City Centre Hotel, 50, Michalakopoulou Str. GR 11528 AthensConference Organizer: International Organisation of Physical Therapy in Mental Health and Greek Scientific Section “Physiotherapy in Mental Health” of PanHellenic Physiotherapists’ AssociationConference Secretariat - Public Relations: Alpha Public Relations and Integrated Marketing S.A., 55, Pytheou Str. GR 11743 Athen