Using body-measurement indices and wrist-type photoplethysmography signals to categorize consumer electronic users' health state through a smartwatch application

The development of wearable technologies has been boosted considerably. On one hand, due to Internet of Things market expansion, and on the other, owing to health awareness on users demanding the convergence of wearable technology with applications that track their activity during the day, providing feedback on how to improve their consuming experience employing human vital signs. The availability of sensors on most of the wrist smartwatches and fitness bands, make this convergence a precondition for consumer devices industry and stakeholders. This article presents an analytical exploitation of this valuable data, and uses the embedded heart rate sensor from an attainable smartwatch to meet the prior requirements, parting the users according to the level of physical activity in pursuance of make a suitable recommendation from a specific consumer device edible catalog, according to the number of calories recommended for a healthy state.