Validation and development of a posture quantification and classification technique using MediaPipe Pose

JUAN CARLOS ITURRIETA; ELISA PÉREZ; FERNANDO TETTAMANTI; NATALIA LOPEZ

San Juan

Congreso; XXIII CONGRESO ARGENTINO DE BIOINGENIERÍA Y XII JORNADAS DE INGENIERÍA CLÍNICA ? SABI 2022; 2022

Universidad Nacional de San Juan - Facultad de Ingeniería

Currently, according to the WHO, neurological disorders leave a high rate of motor sequelae in many individuals worldwide. For public health this represents a great cost that many developing countries cannot absorb in their health system or are overwhelmed to provide a prompt response to these demands. The importance of proposing therapies to support adequate rehabilitation makes us think of methods that can be more effective and low-cost in neurorehabilitation. Therefore, being able to classify positions objectively in a therapy environment is of utmost importance, helping the subjectivity of the therapist, or of the therapy itself, reducing time and costs. In this work we presented a development of quantification and classification of upper limb postures, using a webcam type sensor and MediaPipe®. The algorithm developed to estimate angular excursion using the Bland-Altman method was validated and it can be concluded that it is interchangeable with the goniometer.