Breathe Happy will be working with the SimDH programme to develop a custom deep learning model which can accurately identify yoga poses and their execution. The development of the technology will be by Adarsh Krishnan, MSc Data Science Student at LSBU, working closely with Breathe Happy’s CTO.
Breathe Happy provide live and remote wellbeing sessions with world-class instructors. These sessions are engaging with a motivating community and personalised posture correction from teachers in the comfort of user’s home at the convenience of their schedule based on three key pillars of MOVE, BREATHE, CONNECT.
SimDH Programme Manager, George Boorman, says:
“We’re excited for this project with Breathe Happy, and the collaborative opportunity it has presented to them and to a LSBU student. The development of novel technology enabling their yoga instructors to guide participants more effectively in real-time is a great enhancement of their already fantastic service.”
Simon Perrott, CTO at Breathe Happy, says:
“SimDH allowed us to share our vision with a Masters student and collaborate together in how to more effectively use computer vision to correct posture; the student has deepened his understanding of Neural Nets in an immediately applicable area and we have together progressed towards our goals”
The work undertaken in this project will form Adarsh’s MSc thesis, whilst also producing a new product which Breathe Happy can deploy within their platform and launch to market.
"This SimDH project allowed me to use computer vision to estimate poses of a human body and implement it in a product. The experience of working with a company before even finishing my studies is a valuable asset for any young graduate to have."
SimDH provides free business and innovation support to London's Health Tech SMEs. Find out more at www.simdh.com.
Learn more about Breathe Happy’s live and interactive yoga classes at www.letsbreathehappy.com
This collaboration is match-funded by European Regional Development Fund.
SimDH allowed us to share our vision with a Masters student and collaborate together in how to more effectively use computer vision to correct posture; the student has deepened his understanding of Neural Nets in an immediately applicable area and we have together progressed towards our goals