In this presentation, i have tried to show the difference in the EMG signal output of different age group, gender and have also compared the signal pattern of a normal human being to that of a paralytic person. Surface EMG sensors have employed for the testing on volunteers. References: [1] H. S. Milner-Brown and R. B. Stein, "The relation between the surface electromyogram and muscular force," Journal of Physiology, vol. 246, pp. 549- 569, 1975. [2] C. Orizio, "Muscle sound: bases for the introduction of a mechanomyographic signal in muscle studies," Critical reviews in biomedical engineering, vol. 21, pp. 201-43, 1993 1993. [3] D. B. Sanders, E. V. Stalberg, and S. D. Nandedkar, "Analysis of the electromyographic interference pattern," J Clin Neurophysiol., vol. 13, pp. 385-400, Sep 1996. [4] W. Yao, A. J. Fuglevand, and R. M. Enoka, "Motor-unit synchronization increases EMG amplitude and decreases force steadiness of simulated contractions," Journal of Neurophysiology, vol. 83, pp. 441-452, 2000. [5] Clancy, E. A., Bouchard, S., and Rancour, D. (2001): "Estimation and application of EMG amplitude during dynamic contractions", IEEE Eng. Med. BioI. Mag., 20, pp. 47-54. [6] James C. Huhta, John G. Webster (1973): "60-Hz Interference in Electromyography", IEEE Transactions on Biomedical Engineering, Vol. BME-20, No. 2. [7] Pinwei Zhu, "Design of Surface Electromyography Detection Circuit", 2010 International Conference on Future Information Technology and Management Engineering. [8] Analog Devices, Inc. (2004): "Low Cost Low Power Instrumentation Amplifier", datasheet Rev. G, pp. 1-3.

1. A study on the effect of
age, gender and paralysis
on sEMG signals

2. What is sEMG?
• sEMG: Surface Electromyography
Electromyography (EMG) is a technique
for evaluating and recording the electrical
activity produced by skeletal muscles.

3. What is electrical activity of
muscles?
• Muscles are stimulated by signals
from nerve cells called motor
neurons. This stimulation causes
electrical activity in the muscle, which
in turn causes contraction. These
signals are called myoelectric signals.

4. Myoelectric signal
• Frequency Range:
10 Hz to 500 Hz
• Amplitude: 10uV to
5000uV
What is electrical activity of
muscles?

5. Myoelectric signal
• Frequency Range:
10 Hz to 500 Hz
• Amplitude: 10uV to
5000uV
What is electrical activity of
muscles?
NOISE

6. What is electrical activity of
muscles?
Power Transmission Lines(Hum)
India: 50Hz
USA: 60 Hz

7. Difficulties for retrieving the
signal.
• Low amplitude.
• Low SNR.
• Highly immune to noise.

8. • High gain amplifier.
• High CMRR
• Filter: 50hz band stop
and 10 hz-500Hz
bandpass.
Requirement:
• Low amplitude.
• Low SNR.
• Highly immune to noise.

9. Hardware:
Instrumentation amplifier(AD620)
Gain Range: 1:10,000
CMRR= 120dB
G = 49.4kΩ/ Ro+1

10. sEMG sensor(Electromyograph)

11. Electrodes:
• Dry electrodes:

12. Positioning of electrode:
•Electrode 1 and electrode 2 across the target
muscle i.e. Flexor carpi radialis.
•Electrode 3 to the body ground.
Electrodes:

13. Positioning of electrode:
•Electrode 1 and electrode 2 across the target
muscle i.e. Flexor carpi radialis.
•Electrode 3 to the body ground.
Electrodes:

14. Data acquisition:

15. Data acquisition:

16. Processing
• Now we have 16-bit data in MATLAB.
16 bit
data(Time
Domain)
DFT
Data in
frequency
Domain
Filter
implementation

17. Processing
• Now we have 16-bit data in MATLAB.
16 bit
data(Time
Domain)
DFT
Data in
frequency
Domain
Filter
implementation

18. Processing
• Now we have 16-bit data in MATLAB.
16 bit
data(Time
Domain)
DFT
Data in
frequency
Domain
Filter
implementation
Data Analysis

19. Volunteers
No. of
Volunteers Age Group Gender Normal/Paralytic
10 16-25 M Normal
10 16-25 F Normal
5 35-45 M Normal
5 55-65 M Normal
5 55-65 F Normal
1 35-45 F Half-Paralytic
• In total 36 volunteers were employed.

20. • Protocol followed:
• Sensors were attached to the volunteers’ right
arm and they were asked to keep their arm in
fully relaxed position.
• Then they were asked to keep there arm in fully
excited position by tightening their fist to get the
maximum firing by the muscle neurons.
• Similar task was done with the left arm.
Volunteers

21. Data Analysis and interpretation
Left hand sEMG data for age group 16-25.

22. Data Analysis and interpretation
Right hand sEMG data for age group 16-25.

23. Data Analysis and interpretation
Right and Left hand sEMG data for male of age group 55-65.
.

24. Data Analysis and interpretation
Right and Left hand sEMG data for female of age group 55-65.
.

25. Data Analysis and interpretation
Comparison between the left hand sEMG data of different age groups
at fully excited position.

26. Data Analysis and interpretation
Comparison between the sEMG data of the normal hand to the
paralytic hand of a half paralytic individual of age group 35-45.

27. Result
• Right hand’s sEMG signal in all the age group is more in comparison to
that of the left hand.
• sEMG data of female is found to be less than in comparison to the male, in
all age groups.
• sEMG signal’s strength increases from age group (16-25) to age group (35-
45) and then decreases for age group (55-65).
• The paralytic hand shows less amplitude sEMG signals in comparison to
the normal hand of the same individual

28. Future aspects
• This study and data acquired during the
experiment can be used as a reference to study
the electric activity of Flexor carpi radialis for
different movement of hand.
• Database of electrical activity of major muscles
of human body can be made, which can be used
to create the prosthetic limbs for people with
paralysis or amputees.

29. • Abhishek Jha
(abhishek.jha@ismu.ac.in)
Thank you!!
Authors:
• Mrinal Sen