Implementation of Fall Detection Positioning and Rescue System Using Smart Phone
1
S.Suresh Kumar,
2V.Devi Maheswaran,
3K.Jayasree
1,2,3Dept. of EEE, Rajalakshmi Engineering College, Chennai, India
Abstract
In the recent years, fall accident is the major injury for the elderly persons. To prevent this accident the fall detection, patient positioning and rescue system is implemented by using android technology. In turn this system is beneficiary for elderly person, physically challenged and patients. The proposed system tracks the patient body position and health condition through smart biomedical sensors. The sensor senses the heart beat rate, blood pressure, body temperature and patient body angle detection. When the sensor signal is above the threshold level the alert message is sent to the relatives and rescue center via GSM (Global system for mobile communication) further assistance is given to the patient by the relative or rescue system with the support of GPS (Global positioning system).
Keywords
Bio Medical Sensor, Android-Rescue System, Patient Position, Fall Detection.
I. Introduction
The android technology brings a advancement for monitoring, tracking and updating the fall injury of the affected patient. It is an application based system where the emergency rescue is brought out using prioritized rescuer. The existing module uploads the fall injury information in the home based system, where in the implication of android technology in fall detection helps to upload the data’s for the relevant contact.
A. Bio Medical Sensors
1. Digital Sphygmomanometer
This is the biomedical sensor for measuring the systolic and diastolic pressure. Electronic sphygmomanometer and mercury sphygmomanometer are used to measure the human blood pressure at present. Electronic sphygmomanometer is small, easy to operate and carry data, record the result efficiently. Hence it is better than mercury sphygmomanometer.
2. Accelerometer and Temperature Sensor
This wearable sensor used to detect the human fall. Tri axis accelerometer sensor works on the principle of MEMS technology [1-6]. Temperature sensor measures the body temperature of the patient and generates the corresponding analog sensor [7].
B. GSM and GPS 1. Topology
GSM optimizes the wireless network topology. In this proposed system the 2G GSM wireless mode of communication is preferred.
2. GSM Partitioning
In this proposed system the GSM based SMS service occurs at the data transfer speed of 9.6kpbs.Here GSM-900 uses 890 - 915 MHz to send information in full duplex mode. It has 124 RF
channels each spaced at 200 kHz. The full duplex spacing of each channel is 45 MHz.
2. Global Positioning System
The location of the injured patient is sensed using Global Positioning System (GPS).The SKG13BL GPS module is implemented using embedded logger function.
C. Android Technology
The message based android operating software is implemented in the fall detection system. The programming code for the under running application are designed using JAVA language. The eclipse software tool is used for programming and testing.
D. Controller 1. Features
The oscillator generates the clock cycle for executing each instruction at 2Mhz.Serial communication is exhibited between the modules at the data rate of 9600bps.The analog inputs of the controller are enabled for each instruction to store to 10 binary bits.
2. Port Definition
Five external modules are connected to the PIC18F4520 analog input port. Each module has the specific port address and timing cycle to execute the instructions. The port to port communication occurs simultaneously in sequential manner. The five ports are allowed to execute the instructions with certain delay timing cycle.
Such that the overlapping of controller process during fetch cycle is limited [8].
II. Block Diagram
A DC supply of 5V is applied at the Vcc PIN of microcontroller.
Accelerometer sensor is the first input interfacing module with PIC18F microcontroller. It has three outputs Xout, Yout, and Zout. This sensor senses the value of angle of patient at each moment. This sensed value determines whether the patient is under fall condition. Heart beat sensor is the second input interfacing module. It measures the fluctuation present in the sensed heart beat signal. The difference in fluctuating signal is calculated by repetitive ON and OFF timing cycle. BP sensor act is the input interfacing third module. It measures the systolic and diastolic pressure of the patient. The sensed value gives current health condition of the patient. Temperature sensor is the fourth input interfacing module. It measures the temperature sensitivity of the subjective patient continuously for each timing cycle.
The ADC is first four built in module of PIC18F microcontroller.
It converts all the sensor analog output to digital value. These digital values are used for processing in microcontroller. The microcontroller executes each module sequentially based upon the coding flow. 48MHz is the clock frequency of the controller; this frequency is used to execute each instruction. This controller make use of a special purpose control registers for mapping hardware
data and software data. The Microcontroller read and processes the sensor value and updates this information to Android mobile to monitor the status of the patient. After processing the input signal the controller will detect whether the processed (stored) signal is above the threshold value or not. If not GSM module is activated.GSM (Global System for Mobile communication) is the implemented in the form of Subscriber Identity Module (SIM).This GPS module tracks the status of the patient by using the Android technology. Android based GSM network enables the user to create application oriented software for tracking an valuable information about the status of the patient from the microcontroller. This application software is been designed for the specific purpose.
Fig. 1: Block Diagram of Patient Module
There are two output units in this system, first serves for ambulance unit and other serves for relation unit. The relation unit comprises of GSM Module, Microcontroller, LCD display, Buzzer and Reset.
The GSM receives status of the patient from the microcontroller of the patient unit.
Fig. 2: Block Diagram of Ambulance unit 1
An application is matured in android mobile. The patient unit read the sensor value and GPS value and sent through GSM and this information updated in android mobile easily to identify the status of the person. The patient module sent information to android mobile whenever sensors value increase the threshold value. The patient Microcontroller read the sensor value and display in LCD.
If the sensor value is above the threshold value through serial Communication this information communicates to the Ambulance unit for medical help. In ambulance unit the Microcontroller read the data transmitted from the patient unit and display in LCD. The received data will be the patient critical data along with the user location. If the ambulance is free the Ambulance unit response the ready message with its own ID to the patient unit. The patient unit receives the message from Ambulance unit. The patient unit response the message to ambulance unit along with the ID of first message receives from the ambulance unit. The message and data communicate between patient and ambulance unit in serial communication are seen through virtual terminal.
Fig. 3: Block Diagram of Ambulance unit 1
The virtual terminals are synchronized for timing cycle of clock signal. The buzzer gives the sound alarm if in case of emergency for the patient. The LCD displays the status of the patient as message in this prototype declaration. The RESET is used to erase the older information regarding the status of the patient is cleared. Thus these android applications bring effective rescue system for elderly patient.
III. Flow Chart and Algorithm A. Algorithm
Initialization
• Biomedical sensors are placed on the patient body.
• Microcontroller read the sensor value of heart beat, blood
• pressure and temperature sensor.
The sensor value read by Microcontroller are updated to the
• Android Mobile to monitor the status of the patient.
If the sensor value read by Microcontroller are above the
• threshold value. This information convey to their relatives along with the patient location.
If the sensor value read by Microcontroller are above the
• threshold value. This information convey to nearby Ambulance
unit for medical help.
The ambulance communicate response message to patient unit
• ready to come with its own ID when the ambulance is free.
The patient unit sent come soon message to ambulance unit
• with priority based first message receives from ambulance unit.
Stops the execution.
•
B. Flow Chart
Fig. 4: Flow Chart
C. Flow Chart Description
AMB - Ambulance, REL - Relation, HR -Heart rate, BP- Blood Pressure, ACC -Accelerometer, TH –Temperature, NET- Network
IV. Sensor specification and threshold values Table 1: Specification Blood Pressure
STAGES SYSTOLIC
(mm hg) DIASTOLIC
(mm hg)
Hypotension < 90 < 60
Desired 90–119 60–79
Pre hypertension 120–139 80–89 Stage 1
Hypertension 140–159 90–99
Stage 2
Hypertension 160–179 100–109
Hypertensive
Crisis ≥ 180 ≥ 110
The Table 1 refers to the specification values of blood pressure.
According to these values the blood pressure of the patient is normal when the systolic and diastolic pressure is of 90mm Hg and 60mm Hg. The patient is considered to be in low pressure when the systolic pressure is 70mm Hg and diastolic of 50mm Hg. The patient is considered to be in very high pressure when the systolic pressure is of range from 120 to 190mm Hg. Similarly the diastolic pressure of the hyper tensed patient is of range from 80mm Hg to 120mm Hg. Based upon these values the sensor module detects the status and health condition of the patient. The various blood pressure stages are discussed in the below given bar chart.
Fig. 5: Bar Chart for Blood Pressure Specification Table 2: Sensor Threshold Values
Sensor Threshold value Function
Heart beat sensor Greater than 72
bps. Call ambulance
and call relatives.
Blood pressure
sensor Systolic pressure
80 mm/hg. Call ambulance and call relatives.
Blood pressure
sensor Diastolic pressure
120 mm/hg. Call ambulance and call relatives.
Temperature sensor 37.5 degree Celsius. Call relatives Accelerometer
sensor
200mv/g (assumed) in output.
Call ambulance and call relatives.
The Table 2 refers to the sensor threshold values. According to this table when the sensed values are above the threshold values then the fall alert is given to the relation and ambulance units.
Figure 6: Flow Chart for threshold decision.
V. Simulation Result A. Patient Module
Fig. 7: Simulation Diagram for Relation Unit
The result of the patient unit, ambulance units, and relation unit is synthesized using PROTEUS Simulation Software. Initially the patient module is synthesized and simulated. The result of the patient module implicates the processed and sensed values of the corresponding sensors. The patient module updates the controller output to the relation and ambulance unit by means of UART communication. For ease of simulation the UART communication between the modules are preferred instead of GSM. Up next the relation module is initialized and the response message is delivered to the patient unit. For the need of immediate recovery of patient either the relation unit or ambulance unit sends the ready message to the patient unit.
B. Ambulance Unit 1
Fig. 8: Simulation Diagram for Ambulance Unit C. Ambulance unit 2
Fig. 9: Simulation Diagram for Ambulance Unit 2
Table 3: Simulation Output Process
Patient unit Read sensor value
Continuously updated the data to android mobile.
Sent response message to ambulance unit
Relation unit Receive data from patient unit
Receive data from patient unit when read sensor value above the threshold level.
Ambulance unit 1
Receive data from patient unit
Sent ready message when ambulance unit is free and wait for response from patient unit
Ambulance unit 2
Receive data from patient unit
Sent ready message when ambulance unit is free and wait for response from patient unit
The simulation of all four modules at one single is coded, designed and synthesized for effective results.
Fig. 10: Schematic Diagram for Patient Relation and Ambulance Unit
Table 4: Simulation Result
UNITS DISPLAY OUTPUT
Patient unit
Acc value = 200 mV HR value =73 bps BP systolic =81 mm hg BP diastolic =102 mm hg Temperature = 38 deg Celsius
Relation unit
Acc value = 200 mV HR value =73 bps BP systolic =81 mm hg BP diastolic =102 mm hg Temperature = 38 deg Celsius
Ambulance unit 1 Ambulance unit 2
Acc value = 200 mV HR value =73 bps BP systolic =81 mm hg BP diastolic =102 mm hg Temperature = 38 deg Celsius The above tabular column defines the simulation results of each module for their respective sensor values. The results are furnished by the below line chart.
Fig. 11: Line Chart for the Simulated Results VI. Hardware Result
The hardware implementation of fall detection, positioning and recue system using smart phone is described by the below images.
The accurate results for the conducted hardware experiments are formulated below.
0 50 100 150
Abnormal 106
39.4 80 143
105
Accelerometer 78 90 Temperature 32.5 37.5 Heart Rate 70 72 BP systolic 110 120 BP diasystolic 90 80
Fig. 12: Bar Chart for Hardware Result
Fig. 13: Patient Module
Fig. 14: Ambulance 1 Module
Fig. 15: Ambulance 2 Module
Fig. 16: Relation Mobile
Fig. 17: Android App
VII. Conclusion
Thus the implementation of smart phone accomplished ANDROID technology implicates the immediate rescue for the healthily challenged citizens. This system helps in monitoring the status of unconditional heart beat rate and blood pressure. The accelerometer detects the un-positioned pace of the patient and the processed signal is instantly updated to the ambulance unit and specified motile GSM number. The technical scenic advancement brought in this system is a newer version of fall detection for healthily challenged citizen via GSM and android technology.
References
[1] J.Wang, Z.Zhang, Bin.L,S. Lee, S.Sherratt,“An enhanced fall detection system for elderly Person monitoring using consumer home network”, IEEE Transactions on Consumer Electronics, 60 (1), 2014.
[2] S. Abbate, M. Avvenuti, G. Cola, P. Corsini, J.V. Light, A.Vecchio,“Recognition of false alarms in fall detection systems,” in Proc. 2011 IEEE Consumer Communications and Networking Conference, Las Vegas, USA, pp. 23-28, Jan. 2011.
[3] Tal Shany, Stephen J. Redmond, Michael R,“Sensors-Based Wearable Systems for Monitoring of Human Movement and Falls”, IEEE Sensors Journal, Vol. 12, No. 3, March 2012.
[4] Y.W Bai, S.C. Wu, C.L. Tsai,“Design and implementation of a fall monitor system by using a 3-axis accelerometer in a smart phone,” IEEE TransConsumer Electron., Vol. 58, No.
4, pp. 1269-1275, Nov. 2012.
[5] S. Abbate, M. Avvenuti, F. Bonatesta, G. Cola, P. Corsini, A.Vecchio,“A smartphone-based fall detection system,”
Pervasive and Mobile Computing, Vol. 8, No. 6, pp. 883- 899, Dec. 2012.
[6] M. Yu, A. Rhuma, S. Naqvi, L. Wang, J. Chambers,“A posture recognition based fall detection system for monitoring an elderly person in a smart home environment,” IEEE Trans. Infor. Tech. Biom., Vol. 16, No. 6, pp. 1274-1286, Aug.2012.
[7] Joyashree Bag, Subhashis Roy, Subir Kumar Sarkar,” FPGA Implementation of Advanced Health Care system using Zig- Bee enabled RFID Technology", IEEE International Advance Computing Conference (IACC), 2014.
[8] D.M. Karantonis, M.R. Narayanan, M. Mathie,
“Implementation of a real time human movement classifier using a triaxial accelerometer for ambulatory monitoring,”
IEEE Trans. Infor. Tech. Biom., Vol. 10, No. 1,pp. 156-167, Jan. 2006.
[9] Hairong Yan, HongweiHuo, Mikael Gidlund,“Wireless Sensor Network Based E-Health System –Implementation and Experimental Results”, IEEE Transactions on Consumer Electronics, Vol. 56, No. 4, November 2010.
Mrs. Devi Maheswaran completed her bachelor degree (1998) in University Visveswarayya College of Engineering, Bangalore University and completed her master degree (2007) in College of Engineering Guindy, Anna University.
She is currently working as Associate professor, in Electrical and Electronics Engineering (EEE) department at Rajalakshmi Engineering College, Thandalam. She is currently pursuing her Ph.D at VIT University, Chennai. Her current research areas includes design of SMPS, converter topologies, solar energy harvesting techniques, Embedded controllers, FACTS devices and design of driver circuit for LED lighting.
Suresh Kumar S completed his bachelor degree (2013) in University College of Engineering Villupuram (UCEV), Anna University and he is currently pursuing his master degree in Embedded System Technologies in Electrical and Electronics Engineering department in Rajalakshmi Engineering College, Thandalam.
