Acoustic and prosodic information for home monitoring of bipolar disorder

Epidemiological studies suggest that bipolar disorder has a prevalence of about 1% in European countries, becoming one the most disabling illnesses working age adults, and often long-term persistent with complex management treatment. Therefore, capacity home monitoring for patients this is crucial their quality life. The current paper introduces use speech-based information as an easy-to-record, ubiquitous non-intrusive health sensor suitable monitoring, its application framework on NYMPHA-MD project. Some preliminary results also show potential acoustic prosodic features to detect classify disorder, by predicting values Hamilton Depression Rating Scale (HDRS) Young Mania (YMRS) from speech.