HMSystem Anand Joshi - Anand Dipakkumar Joshi 's

HMSystem
Anand Joshi
Idea
HMSystem is abbreviation of Health Monitoring System. HMSystem is a web and mobile based
system that consists of body sensors such as SPO2, mounted on the patient's body to record
their health activities in regular intervals and display it to the medical personnel via the
website. So the health professionals can keep a regular eye on the patient's health. Also, when
the health of the patient goes critical it then alarm system so that necessary precautions
measures can be taken timely by the doctors. For example, at the very critical stage of patient's
health, it can automatically generate the call to the ambulance. Also this system implements
the concept of health prediction. This concept predicts the health of person in near future by
taking into consideration the past health data as well as the present data. These data are
projected on the graph showing Time Vs Health. The linear curve is marked which helps the
doctors to estimate the level.
This complete project is divided into several modules:
1. Hardware Interfacing Module
2. Communication Module
3. Data Storage and Management Module
4. Emergency Handling Module
5. Health Prediction Module
Hardware Interfacing Module
The sensors – SPO2, Blood Pressure, etc sensors are attached to the patients or the aged
persons. These sensors take readings and send the output to low power wireless modules say
eg SunSpots. These sensors give the reading to the base station which is either a laptop or a
mobile device. The data are recorded on the SDCard situated on the base station. This approach
helps to maintain the client version of the data. This data is encrypted with the RSA so that only
the patient’s doctor can decrypt and receive the information. Also the data is compressed to
reduce the size, helps to store more data in less space and also it helps to reduce network
traffic when transmitting the data to doctor’s machine.
Fig: SPO2 Sensor

Fig: Blood Pressure Sensor
Fig: SunSpot Sensors
Body Sensors Take Reading
Send Data to Transmitting
Sensors
Data is saved on SDCard
after processing on base
Station
Low Power Transmitting
Sensors transmit data to
Receiving Sensors on Base
Station
•Either PC, PDA or a mobile device
Data ready for transmittion
to Communication Module
Fig: Process flow in Hardware Interfacing Module

Communication Module
Tracking Server Database
Tracking Server
Doctor’s Server
Doctor’s Server Database
Patient’s Base Point
Doctor’s Machine
The Communication module has a bit complicated structure. The figure above shows the basic
connections between the different components of this module. We describe the connections as
under:
1. The Patient’s Base point can be any instrument connected to wireless internet
connection. The Patient’s Base point is a machine or a smart phone or a simple base

station. Here the sensors are interfaced directly or indirectly to the Patient’s Base Point.
The Patient’s Base Point has the dynamic ip address and hence in order to establish the
communication with doctor’s machine, it needs to establish the connection with it.
2. Doctor is usually having the static ip address to which patient can connect. (Dynamic ip
are also possible but for first approach we took the simpler case)
3. To get the ip address of the doctor’s machine, it contacts the Tracking server by making
proper authentications. Once it logs inside the system, it gets the doctor’s connection
information.
4. This forms the client – server architecture between the tracking machine and patient’s
base point. Now once the patient’s base point receives the details, it forms peer-peer
connection with the doctor’s machine for the transfer of the medical data.
5. These transfers are of two kinds. For the first case patient’s module regularly transmit
information (daily if condition is normal and hourly if condition is critical). Second case is
when doctor wants to pull the data from the patient’s machine. For this case, he can’t
contact the Patient’s module directly because patient carries a dynamic ip address. So to
solve that Doctor’s server sets the call bit in tracking server which is captured by the
Patient’s module and when it receives that bit, it transmits the data to the Doctor’s
server.
Data Storage and Management Module
The Data Storage and Management module works on
1. Patient’s Base Point: The patient’s module is constantly receiving the data and is stored
on the SDcard. This is for the patient backup information. This data is encrypted by the
Private Key of the patient and then encrypted by the Public Key of the doctor. This
facility ensures proper protection of data and then the data is compressed to store on
the SDCard. This data is sent by the patient’s module on the periodic basis.
2. Doctor’s Server: The periodic and on demand data coming from the patient’s end are
temporary stored and policies are employed on that to retrieve the most effective
reading and only that particular reading is stored. From daily large number of readings
only one reading is sampled out which effectively represents all data. Like that there are
daily, monthly and yearly data store. The older data of two years back is converted to
reports and mailed or sent back to the patient.
3. Tracking Server: Tracking servers main purpose is to keep track of the Doctor’s server
and thus help to form the communication link between the patient and doctor. The
tracking server maintains the databases that have information of doctor’s ip address
and it has patients associated to a given doctor. It also stores the access bit information
that helps the patient module to know whether the doctor needs the data on demand
or not.

Emergency Handling Module
The Patient’s base module received data continuously. If this data is crossing certain thresholds
limits than it alerts the emergency services both at doctor end and automated calls to
ambulance and emergency services are done.
Health Prediction Module
The Health Prediction Module uses the concepts of machine learning and data mining to make
predictions that what can be the health of the patient in near future considering the past
records. Here the doctor’s server has the software that computes the supposed future value of
the medical reading while considering the past trends of the health. If the future predicted
value turns to be greater than the threshold value, than the doctors are alerted well in advance
and the doctors can take necessary precautions to prevent the health going in such critical
conditions in near future.