Music your body listens to
Rubato is an innovative technology that matches music to the listener’s physiological and psychological state. We are utilizing algorithms and machine-learned data, based on biometrics and musical attributes. Our mission is to recommend music that scientifically helps people to manage their stress and improve sleep quality, by turning enjoyable music listening experience into scientific Biofeedback treatment.
Music has prominent effects on humans, but it affects each one of us in different ways: the same music might be relaxing for one person but increases stress in another. Similarly, one piece of music might improve one’s sleep quality, but might also prevent others from falling asleep. Today, there is no solution to measure and quantify music’s effect on people and personalize musical recommendations by this measurement.
What we do
Our technology analyzes individual cardiac rhythms, trends, and variability, and selects music based on key attributes like tempo, key, scale, and structure. Our SaaS platform connects wearables and music providers, to deliver a playlist that affects and optimizes pertinent biomarkers in a measurable manner, boosting music’s proven benefits.
We use DNN (Deep Neural Networks) to identify and cluster different musical attributes, as well as HRV vectors in large scale to quantify music’s effect. Based on proprietary analysis method, we determine a scientific match between music and bio-markers, and generate insights for personal music recommendation, as well as prediction of music’s effect on different crowds.
For many years, people have been listening to music for their enjoyment. Now, and certainly in the future, people will use music as a form of Biofeedback, and curate playlists that would scientifically help them to optimize their health and overall wellbeing. Rubato aims to help them reach this goal.
Our curation, recommendation, and selection of music is based on scientifically verified
measures and algorithms. We facilitate the BPM Entrainment effect through heart and
respiratory rates; we use heart rate variability (HRV) indexes to determine such
preferences as types of scales (major/minor), the emotional influence of text and lyrics,
and response to various musical structural patterns.