Using Wearable IoT Devices to Analyze Healthcare Data for Human Activity Recognition

Now a day's wearable sensors have gained lots of importance in the field of healthcare researches. Utilizing wearable IoT (sensors) for analyzing health parameters has become more reliable. But in the present scenario the W-IoT which are used, needs to be improvised as there are few complexities in the design and the monitoring abilities. To overcome this, a system is designed which uses linear regression algorithms to analyze the wearable sensors data. All the information gathered from the wearable device applied to the liner regression algorithm where the analysis is made, and the outcome is displayed on the things board server and the update are sent to the mobile application. With this, the reduction of complexity can be achieved and also reduce the human effort by constant monitoring of the patient.