There are many ways through which physiological functions of the body – breathing rate, heartbeat or blood pressure - can be measured. These measurements can tell you something about the performance of the body at a given moment in time. However, for most methods to work they require direct contact. For athletes this direct contact for measurement is not always desired but information on performance is. The researcher is working on developing a computer vision method that can measure physiological functions over time whilst the athlete is in motion.
In a fix lab setting the researcher has collected data with a fixed camera setting and athlete in a fixed position on a home trainer. Through deep learning and a ‘regular’ heart rate monitor as a control measure the researcher has managed to train the algorithm. The current challenge is to find ways to be able to gather enough data, capture the athlete as best as possible, to be able to collect enough overlaying pixels to be able to do the same measurement whilst the athlete is performing in the wild. 

For this innovative idea there are a few next steps to be considered. One is to train the algorithm to measure other parameters such as blood pressure or breathing rate. Subsequently, a next step is to being able to apply this idea through the development of an app or device which will be used by trainers or doctors. Another very big, next step is to be able to apply this method to athletes that are running a marathon. Moreover, the innovative idea or measuring parameters without touching the body could also be applied to intensive care patients or to premature born babies.