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MO MONITORING Presented by R.Prabhu (711712106052) R.S.V.Sudharsun (711712106086) R.Surya (711712106087) Department of ECE. Guided By

WEARABLE SENSOR FOR HUMAN ACTIVITY MONITORING

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Page 1: WEARABLE SENSOR FOR HUMAN ACTIVITY MONITORING

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]

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Abstract IntroductionLiterature ReviewProblem Statement SolutionObjectiveProposed DirectionConclusion Journal References

Outline

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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.

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Introduction

In the medical field, it is possible to monitor Patients’ body

temperature, blood pressure, brain activity, muscle Motion and

critical data.

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Introduction(Contd.,)

It is important to have Very light sensors that could be worn

on the body to perform standard medical monitoring.

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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

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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.

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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.

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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 pressureDrawback: 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.

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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.

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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.

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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.

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HUMAN ACTIVITY RECOGNITION UNIT

Arduino

UNO

Ethernet Module

MEMS Sensor

ECG sensor

GSR sensor

Power Supply Unit

Step down Transformer

Bridge Rectifier

Filter Circuit

Voltage Regulator

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05/03/23 Second Doctoral Committee Review 14

MEMS sensor

GSR sensor

ECG sensor

Arduino

Ethernet Module

SPI protocol

PC

Smart phone

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05/03/23 Second Doctoral Committee Review 15

Arduino IDE

Standard C and C++ constructs

Blynk Application

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RESULTS AND DISCUSSION:

This system can be work 24*7 and also multiple doctors can

monitor the single patients details.

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Data and processing will be standardized. Systems will be

secure and provide clear and detailed decisions and

recommendations.

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HARDWARE IMPLEMENTATION

05/03/23 Second Doctoral Committee Review 18

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SOFTWARE IMPLEMENTATION

05/03/23 Second Doctoral Committee Review 19

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SIMULATION OUTPUT

05/03/23 Second Doctoral Committee Review 20

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05/03/23 Second Doctoral Committee Review 21

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CONCLUSION:

The system can be tuned to the requirement of individual

patient. The whole activity can be monitored remotely by

doctors, nurses or caregivers.

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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.

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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.

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“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.

05/03/23 Second Doctoral Committee Review 25

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Queries?

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Thank You