This seminar presentation discusses the design and control of an IPMC-based artificial muscle finger driven by EMG signals. An IPMC strip is fixed to a holder as the artificial finger. EMG signals are acquired from the index finger muscles and used to control the bending of the IPMC strip, mimicking natural finger movement. Experimental results show the IPMC finger is capable of responding to EMG inputs and can perform tasks like holding micro-objects, potentially serving as a lightweight and flexible replacement for electric motors in rehabilitation applications.

1. Seminar on
EMG Driven IPMC Based
Artificial Muscle Finger
Presented by:
BIBI ABIDA
M.Tech 1st year 2nd
sem
Bio-Medical
Engineering

2. Contents:
 Introduction
 Design & Control
 Actuation mechanism of IPMC
 Basic tendon of index finger
 Model for controlling EMG signal
 Experimental testing set up
 Advantages
 Conclusion
 References

3. Introduction
 The medical, rehabilitation and bio-mimetic
technology demands human actuated devices.
 They support in the daily life activities such as
functional assistance or
 functional substitution of human organs.
 Major challenges are:
the acquisition of the user’s intention from his or her
bionic signals
to provide with an appropriate control signal for the
device.
need to consider the mechanical design issues such as
lightweight and small size with flexible behavior.
 For bionic signals, EMG signal can be used to control
these devices.

4. Introduction (contd..)
 EMG reflects the muscles motion, and can be
acquired from the body surface.
 Ionic polymer metal composite (IPMC) has
tremendous potential as an artificial muscle.
 This can be stimulated by supplying a small voltage of
±3V and shows evidence of a large bending behavior.
 In place of the supply voltage from external source for
actuating an IPMC, EMG signal can be used where
EMG electrodes show a reliable approach to extract
voltage signal from body.
 Using this voltage signal via EMG sensor, IPMC can
illustrate the bio-mimetic behavior through the
movement of human muscles.
 Hence, , an IPMC is used as an artificial muscle finger

5. Design and control
 An IPMC strip (Size 40 mm × 10 mm× 0.2 mm) fixed
with holder and another plastic based finger of similar
size is made for supporting the micro object .

6. Actuation mech. of IPMC

7. Basic tendon of index finger for
identification of EMG signal

8. Block diagram of EMG signal behaviour from
human index finger

9. Acquired data from finger muscles via
EMG signal

10. Block diagram of EMG signal via human
finger after applying PID control system

11. Experimental testing setup

15. Advantages:
 Low voltage in man-machine interface.
 Large bending amplitude.
 Simple control that are applied in development of
micro/bio robot.
 Actuating through a small voltage(±3 v),
 Light in weight, Flexible in nature.
 Does not involve sophisticated controllers for
operation
 Voltage is taken from human index finger through
EMG sensor instead of battery source.
 A suitable finger for holding the object in the fields of
micro manipulation.
 Replacement of an electro-mechanical system like
electric motors in the application field of rehabilitation

16. Conclusion :
 Experimentally, it is demonstrated that IPMC based
artificial muscle finger is capable of adopting this
voltage from EMG signal and mimics as a human
finger.
 IPMC can be activated through EMG signal and is
applicable as flexible and compliant finger for holding
the object in the fields of micro manipulation.
 In future, IPMC based micro robotic arm along with
multiple IPMC artificial fingers will be used.
 It can be a replacement of an electro-mechanical
system like electric motors in the application field of
rehabilitation technology.

17. References
 Jain R. K., Datta S., Majumder S., Chowdhury S. & Banerjee P.
(2011). IPMC artificial muscle finger activated through EMG.
Worldwide EAP newsletter on http://www.EAPnewsletter. Vol. 13,
No 01, June (The 25th issue), pp.10-12.
 Ahmad I., Ansari F. & Dey U. K. (2012). A review of EMG recording
technique, International Journal of Engineering Science and
Technology, Vol. 4, No. 2, pp. 530-539.
 Andreasen D. S., Allen S. K. & Backus D. A. (2005). Exoskeleton
with EMG based active assistance for rehabilitation, Proceedings of
the 2005 IEEE 9th International Conference on Rehabilitation
Robotics, Chicago, IL, USA, June 28 - July 1, pp. 333-336.
 Andrews J. (2008). Finger movement classification using forearm
EMG signals, MS Thesis, Queen's University, Kingston Ontario,
Canada

18. Thank you