the functional structure of the remote patient monitoring system based on an IoT-cloud architecture. The system has been designed to measure physiological parameters of a human being such as pulse rate and body temperature. The inputs from the sensors are fed to the programming board for further processing and calculation

A wireless transreciver module is integrated with the pro- gramming board to send the data to a user interface, a cus- tom developed app that displays the health parameters. The received health parameters are processed in the app, and a corresponding brief health analysis report is generated and displayed on the app. If the analysis infers that the person is medically distressed, a text message is sent to all those people that are registered in the app as friends, family, doctors or car- egivers. The data is also sent to a live online database which can be accessed by anyone with whom the database URL has been shared. This database also plots the data on a time graph which can be customized to show data from any of the sensors over a period of time.

The design is practical and can be scaled up further to inte- grate many more sensors in order to measure various other health parameters

The various hardware blocks are explained in full details in a later section.

1 Details of the sensing system

The current version of the system consists of three sensing units, a temperature sensor, a heart rate detector unit and a fall detector.

This sensor was mainly used to track the physical move- ments of the patient and monitor whether there were any cases of falling or sudden impacts on the patient’s body. The acceleration value was read in three different axes in an interval of every 2 ms. In the next step, the magnitude of the difference between two consecutive set of readings were measured which was then compared with the threshold value, to detect an impact of significantly large magnitude. Experiments were conducted to set the threshold value of fall. The everyday human movement like walking, sitting, standing, writing and jumping was simulated and data were obtained. It was concluded from the obtained data that at rest accelerometer reading ranges from 9.00 to 10.50 m/s2 and during freefall the acceleration value becomes less than

9.00 m/s2 and when collision occurs, it rises above 11.00 m/

The response of accelerometer after being attached to wrist-band were also tested for different activities as shown in Fig. 9a, b. The sudden sharp peak was observed when hit during normal activity like walking or writing. Using these data, threshold value for shock or hit to accelerometer was decided to be 15.0 m/s2 for the proposed prototype. The

output from the accelerometer was read at the ADC pins A2, A3 and A4 of the Arduino microcontroller. The difference in the sensed values also improved the accuracy of the whole sensing system.

Interfacing and communication

The microcontroller used in the wrist strap unit is the Arduino Uno. It is programmed to perform the operations like signal conditioning, computing, analyzing and is also responsible for communication. It takes inputs from the sen- sors in the form of analog and digital voltages. Each sensor has a dedicated port, A1 for the temperature sensor and A0 for the heart rate sensor. Each sensor’s signal is sampled at a pre-defined rate using Arduino’s interrupt driven algorithms.