Tracks: 2018 MSTC Full Conference, MedTech, Sensors & Sensor Networks
MSTC 2018 Session 2: HEALTH & WELLNESS
Tuesday February 13, 2018 ~ 2:30 - 3:00 PM
Shubhadip Paul is a Senior Embedded Software Engineer at NXP Semiconductors, a world leader in the secure connected vehicle, end-to-end security & privacy and smart connected solutions markets. Prior to that, Shubhadip has worked for Aricent, a leader in Embedded Software. He graduated from UP Technical University with a degree in Electronics and Communication Engineering. Shubhadip is actively involved in developing Software for creating Smart Sensing Nodes using NXP Sensors and MCUs. When he isn’t glued to a computer, he loves to drive and explore new destinations with Scenic Roads and National Parks being National Parks always on the circuit.
More individuals are conscious about their fitness and activity than they ever were. People want to get accurate step counts and activity numbers while following their daily routines and improve their Health. While higher accuracy is always desirable, so is a longer battery life and low cost of the device. A basic high precision Accelerometer combined with an accurate algorithm can provide precise activity monitoring. But this setup can lead to higher power consumption by the host processor which must monitor the acceleration data all the time and the Sensor which may be active all the time.
In this presentation, I will provide an example of how an advanced high precision Smart Accelerometer can be combined with a low power MCU to run high accuracy algorithms sporadically and achieve extended battery life using sensor technologies such as Accelerometer powered by an Intelligent Sensor Software Development Kit (ISSDK).
Driven by the power of a Sensor Framework such as NXP’s ISSDK to read digital sensor data based on Sensor Events and combined with programmable motion detection and power modes of NXP’s latest Accelerometers, High Performance Health Equipment can be developed in minimal time with minimal effort. This platform can easily expand beyond a smart pedometer by the consumer for medical and industrial markets allowing the next generation always on IoT connected devices and sensor end nodes to achieve lower powered processing capability and aggregate sensor data.