Exploiting Weak Head Movements for Camera-based Respiration Detection.

In recent years, considerable progress has been made in the non-contact based detection of the respiration rate from video sequences. Common techniques either directly assess the movement of the chest due to breathing or are based on analyzing subtle color changes that occur as a result of hemodynamic properties of the skin tissue by means of remote photoplethysmography (rPPG). However, extracting hemodynamic parameters from rPPG is often difficult especially if the skin is not visible to the camera. In contrast, extracting respiratory signals from chest movements turned out to be a robust method. However, the detectability of chest regions cannot be guaranteed in any application scenario, for instance if the camera setting is optimized to provide close-up images of the head. In such a case an alternative method for respiration detection is required.It is reasonable to assume that the mechanical coupling between chest and head induces minor movements of the head which, like in rPPG, can be detected from subtle color changes as well. Although the strength of these movements is expected to be much smaller in scale, sensing these intensity variations could provide a reasonably suited respiration signal for subsequent respiratory rate analysis.In order to investigate this coupling we conducted an experimental study with 12 subjects and applied motion-and rPPG-based methods to estimate the respiratory frequency from both head regions and chest. Our results show that it is possible to derive signals correlated to chest movement from facial regions. The method is a feasible alternative to rPPG-based respiratory rate estimations when rPPG-signals cannot be derived reliably and chest movement detection cannot be applied as well.

Similarity based hierarchical clustering of physiological parameters for the identification of health states - a feasibility study.

This paper introduces a new unsupervised method for the clustering of physiological data into health states based on their similarity. We propose an iterative hierarchical clustering approach that combines health states according to a similarity constraint to new arbitrary health states. We applied our method to experimental data in which the physical strain of subjects was systematically varied. We derived health states based on parameters extracted from ECG data. The occurrence of health states shows a high temporal correlation to the experimental phases of the physical exercise. We compared our method to other clustering algorithms and found a significantly higher accuracy with respect to the identification of health states.

Evaluation of a training model to teach veterinary students a technique for injecting the jugular vein in horses.

In this study, a newly-developed model for training veterinary students to inject the jugular vein in horses was evaluated as an additional tool to supplement the current method of teaching. The model was first validated by 19 experienced equine veterinarians, who judged the model to be a realistic and valuable tool for learning the technique. Subsequently, it was assessed using 24 students who were divided randomly into two groups. The injection technique was taught conventionally in a classroom lecture and a live demonstration to both groups, but only group 1 received additional training on the new model. All participants filled out self-assessment questionnaires before and after group 1 received training on the model. Finally, the proficiency of both groups was assessed using an objective structured clinical evaluation (OSCE) on live horses. Students from group 1 showed significantly improved confidence after their additional training on the model and also showed greater confidence when compared to group 2 students. In the OSCE, group 1 had a significantly better score compared to group 2: the median (with inter-quartile range) was 15 (0.7) vs. 11.5 (2.8) points out of 15, respectively. The training model proved to be a useful tool to teach veterinary students how to perform jugular vein injections in horses in a controlled environment, without time limitations or animal welfare concerns. The newly developed training model offers an inexpensive, efficient, animal-sparing way to teach this clinical skill to veterinary students.