This document summarizes a presentation on wearable sensors for human activity monitoring. It discusses how wearable sensors can be used to monitor patients' vital signs like temperature, blood pressure, and brain activity. The document reviews several existing studies on using wearable sensors to monitor patients with conditions like Parkinson's disease. It proposes a system using MEMS sensors, ECG sensors, and an Arduino board connected to an Ethernet module to remotely monitor human activity and vital signs. The system would allow for 24/7 monitoring by doctors and caregivers. Future work could involve monitoring hospitalized patients during recovery and rehabilitation.

1. WEARABLE SENSORS FOR HUMAN ACTIVITY
MO MONITORING
Presented by
R.Prabhu (711712106052)
R.S.V.Sudharsun (711712106086)
R.Surya (711712106087)
Department of ECE.
Guided By
R.Vaishnavi.M.E.,[Assistant Professor]

2. Abstract
Introduction
Literature Review
Problem Statement
Solution
Objective
Proposed Direction
Conclusion
Journal References
Outline

3. Abstract
Wearable sensors in the form of panic buttons for emergency
Help have been in use for a long time and are a huge
Commercial success. Of course for proper utilization.

4. Introduction
In the medical field, it is possible to monitor Patients’ body
temperature, blood pressure, brain activity, muscle Motion and
critical data.

5. Introduction(Contd.,)
It is important to have Very light sensors that could be worn
on the body to perform standard medical monitoring.

6. Introduction(Contd.,)
In the area of sport and training there is an increasing trend of
using various wearable sensors. Something, for example,
Measurement of ECG signal which was possible only in the
Laboratory based system a few years back is now possible Using
wearable sensors

7. Literature Review
 “Wireless sensors relay medical insight to patients and
caregivers” [special reports], J. Edwards May 2012.
Uses:This innovation is need more maintaninens this
monitoring is not secured.
Drawback:It is not applicable for home patents.
, “A Zigbee-based wearable physiological parameters
monitoring system,” K. Malhi Mar. 2012.
Uses:Galvonic skin response measuring is possible only.it
measures only mentioned part of our body
Drawback:It is measuring particular part of our body.

8. Literature Review(contd.,)
 “On-shoe wearable sensors for gait and turning assessment of
patients with Parkinson’s disease,” B. Mariani, M. C. Jiménez
Jan. 2013.
Uses: It is measures by the movements of legs.
Drawback: The sensors is varying because of walking. it is
inaccurate.
“A web-based system for home monitoring of patients with
Parkinson’s disease using wearable sensors,” B.-R. Chen et al.,
Mar. 2011.
Uses: The system is applicable for mobile phones particular
operating system(ex-IOS)
Drawback: The application is not applicable for all operating
systems.

9. Literature Review(contd.,)
[Online]. Available: http://www.stjohn.org.nz/Medical-Alarms/
Medical-Alarm-Devices, accessed Sep. 14, 2014.
Uses: The device only measure only blood pressure
Drawback: The alarm device will inform only after excess
pressure.
 [Online]. Available:
http://www.secom.com.my/products_alarm_sensors.
asp, accessed Sep. 14, 2014.
Uses: Utilizing multipurpose of measuring in the body system
only critical positions.
Drawback: The sensor size is large is not applicable of wearing
continuously.

10. PROBLEM STATEMENT
The person needing help should be alert and fit enough to
press the button. Most importantly, the panic button should
not be light in weight so that it is not comfortable to wear
24/7.

11. PROPOSED DIRECTIONS
The use of wearable sensors has made it possible to
have the necessary treatment at home for patients after an
attack of diseases such as heart-attacks, sleep apnea and
Parkinson disease and so on.

12. All the physiological signals as well as physical activities of
the patient are possible to be monitored with the help of
wearable sensors.
During the rehabilitation stage the wearable sensors may
provide audio feedback, virtual reality images and other
rehabilitative services.

13. HUMAN ACTIVITY RECOGNITION UNIT
Arduino
UNO
Ethernet
Module
Ethernet
Module
MEMS
Sensor
MEMS
Sensor
ECG
sensor
ECG
sensor
GSR sensorGSR sensor
Power Supply Unit
Step down
Transformer
Bridge
Rectifier
Filter
Circuit
Voltage
Regulator

14. 02/24/17 Second Doctoral Committee Review 14
MEMS sensor
GSR sensor
ECG sensor
 Arduino
Ethernet Module
SPI protocol
PC
Smart phone

15. 02/24/17 Second Doctoral Committee Review 15
 Arduino IDE
Standard C and C++ constructs
Blynk Application

16. RESULTS AND DISCUSSION:
This system can be work 24*7 and also multiple doctors can
monitor the single patients details.

17. Data and processing will be standardized. Systems will be
secure and provide clear and detailed decisions and
recommendations.

18. HARDWARE IMPLEMENTATION
02/24/17 Second Doctoral Committee Review 18

19. SOFTWARE IMPLEMENTATION
02/24/17 Second Doctoral Committee Review 19

20. SIMULATION OUTPUT
02/24/17 Second Doctoral Committee Review 20

21. 02/24/17 Second Doctoral Committee Review 21

22. CONCLUSION:
The system can be tuned to the requirement of individual patient.
The whole activity can be monitored remotely by doctors, nurses
or caregivers.

23. FUTURE WORK:
Patients after an operation usually go through the
recovery/rehabilitation process where they follow a strict routine.
It can be monitoring hole activity the hospitalized peoples.

24. REFERENCES:
“A Wearable Sensor for Unobtrusive, Long-Term Assessment
of Electrodermal Activity” Ming-Zher Poh, Student Member,
IEEE, Nicholas C. Swenson, and Rosalind W. Picard*, Fellow,
IEEE. IEEE TRANSACTIONS ON BIOMEDICAL
ENGINEERING, VOL. 57, NO. 5, MAY 2010.
 ‘‘An evaluation of the cuffless blood pressure estimation based
on pulse transit time technique: A half year study on
normotensive subjects,’’ M. Y. Wong, C. C. Poon, and Y. T.
Zhang Cardiovasc. Eng., vol. 9, pp. 32–38, Mar. 2009.
“Monitoring Motor Fluctuations in Patients With Parkinson’s
Disease Using Wearable Sensors”Shyamal Patel, Konrad
Lorincz, Richard Hughes, Nancy Huggins, Fellow, IEEE,
Jennifer Dy, Matt Welsh, Member, IEEE, and Paolo Bonato,
Senior Member, IEEE TRANSACTIONS ON
INFORMATION TECHNOLOGY IN BIOMEDICINE, VOL.
13, NO. 6, NOVEMBER 2009.

25. “Noninvasive Galvanic Skin Sensor for Early Diagnosis Of
Sudomotor
Dysfunction: Application to Diabetes”. Khalfallah, K.; Ayoub,
H.; Calvet, Neveu, X.; IEEE Sensor J. 2010, 12, 456-463.
“Imaging facial signs of neurophysiological responses,” D.
Shastri, A. Merla, P. Tsiamyrtzis, and I. Pavlidis, IEEE Trans.
Biomed. Eng., vol. 56,no. 2, pp. 477–484, Feb. 2009.
“Automatic ingestion monitor: A novel wearable device for
monitoring of ingestive behavior,” J. M. Fontana, M. Farooq,
and E. Sazonov, IEEE Trans. Biomed. Eng., vol. 61, no. 6, pp.
1772–1779,Jun. 2014.
“Elderly care based on cognitive sensor network,” A. Gaddam,
S.C.Mukhopadhyay, and G. S. Gupta, IEEE Sensors J., vol. 11,
no. 3,
pp. 574–581, Mar. 2011.
02/24/17 Second Doctoral Committee Review 25

26. Queries?

27. Thank You