A fully automatic, non-contact method for the assessment of the respiratory function is proposed using an RGB-D camera-based technology. The proposed algorithm relies on the depth channel of the camera to estimate the movements of the body’s trunk during breathing. It solves in fixed-time complexity, $\mathcal{O}\left(1\right)$, as the acquisition relies on the mean depth value of the target regions only using the color channels to automatically locate them. This simplicity allows the extraction of real-time values of the respiration, as well as the synchronous assessment on multiple body parts. Two different experiments have been performed: a first one conducted on 10 users in a single region and with a fixed breathing frequency, and a second one conducted on 20 users considering a simultaneous acquisition in two regions. The breath rate has then been computed and compared with a reference measurement. The results show a non-statistically significant bias of $0.11$ breaths/min and $96\%$ limits of agreement of $-2.21$/$2.34$ breaths/min regarding the breath-by-breath assessment. The overall real-time assessment shows a RMSE of $0.21$ breaths/min. We have shown that this method is suitable for applications where respiration needs to be monitored in non-ambulatory and static environments.

Disabled people have more difficulties for expression and interaction on a non-verbal level because of the physical, sensory or communication difficulties that they usually present. Regarding music therapy, the existing adapted interfaces target disabled people with controlled motor abilities, which still suggests a barrier for the most affected users presenting truly little or uncontrolled movements. In this work, we have developed a device to build an adapted musical instrument through physiological signals. The instrument uses the electrocardiogram (ECG), the electrical activity of the skin (EDA), the respiration signal and the movement of the user to generate music via sonification of the characteristic features of each physiological signal. Furthermore, the ECG and EDA signals have been used to assess the emotional state of the person to provide to the music therapist objective information in real-time about the adaptation of the user to the techniques and interfaces used in their sessions. The adapted instrument has been tested by people with cerebral palsy showing its high degree of adaptability to the user. In four months, an increase in participation of the most affected users in their music therapy sessions has been achieved. In concrete, the results show that the considered users have achieved six of the so-called aids to analysis which are commonly used to evaluate such practices. The results of the assessment of emotional states indicate that the state of a person can be extracted from the ECG in periods of ten seconds while the evolution of the EDA reveals if the person is relaxed or excited. The device has generated a lot of interest among educators since it outperforms the state-of-the-art techniques allowing the integration of the most affected users by eliminating the aforementioned barrier because of non-controlled movements while assessing the emotional state of the person when facing the activity.