**6. Results and conclusions**

A useful way of acquiring EMG signals and motor drive has been explained in this chapter. Modern microelectronics and controllers have enabled us to develop efficient control of prosthetic robotic mechanisms. To summarize the discussions made earlier, Figure 22 shows a block diagram depicting all the necessary steps required to achieve successful prosthesis.

**Figure 22.** Block diagram indicating all steps for driving a robotic mechanism

Computational Intelligence in Electromyography Analysis – 444 A Perspective on Current Applications and Future Challenges

then the resolution of the ADC can be given as:-

samples an ADC can convert in one second.

**5.2. Thresholding and motor drive** 

adequately meet requirements for a robotic arm.

**6. Results and conclusions** 

possible so that the data loss of EMG is kept at a minimum [21].

rates greater than 1000 kSPS and quantization schemes of more than 24 bits.

before, a suitable threshold is applied to that particular quantized digital signal.

driver in order to drive the respective electric motors of a robotic mechanism.

"quantization scheme". If an ADC has a defined range and a quantization scheme of *'n-bits'*,

Vresolution= Vrange/(2)n (6)

While converting an EMG signal into digital format, three specifications should be taken

The number of bits, which an analog signal can be converted into digital format by an ADC, is known as quantization. The maximum amount of voltage an ADC can convert into digital quantized bits defines the range of an ADC. The sampling rate means the number of

After the EMG signal has been amplified up to a suitable level, the range of an ADC should be selected so that it can comprehend a particular voltage level. The number of quantization bits is important, as they determine the resolution of the ADC. The more the number of quantization bits, the less will be resolution of the ADC; the more it will help in control purposes. The ADC sampling rate is also a key consideration. It should be kept as large as

ADCs are now available as a peripheral with microcontroller chips and can give sampling

The control of robotic prosthesis is provided through the thresholding technique [21]. Once the signal is received in digital format, taking all necessary considerations as described

Before applying the threshold, the digital quantized signal is to be observed properly. A threshold value should then set be accordingly. It is recommended to set the threshold value to a point which is less than half the digital quantized output of the EMG signal. When the digital signal exceeds this threshold, the microcontroller should set an output pin to '1' and '0' otherwise [21]. E.g. if the maximum value of the digital quantized signal is 750 (decimal value) then we can set a threshold of 275. This signal is forwarded to an H-bridge or a motor

The motor driver should be designed or selected according to our requirements of electric motor. Usually a motor driver which can drive a 12V motor and handle up to 4A current can

A useful way of acquiring EMG signals and motor drive has been explained in this chapter. Modern microelectronics and controllers have enabled us to develop efficient control of prosthetic robotic mechanisms. To summarize the discussions made earlier, Figure 22 shows a block diagram depicting all the necessary steps required to achieve successful prosthesis.

into account. 1) Quantization, 2) Range of conversion and 3) Sampling rate [21].

As an example, we discuss the control of a robotic hand. There are two primary motions of the human hand, flexing and extending. For flexion, electrode should be placed on Flexor Digitorum Profundus and for extension; the electrode should be placed on Extensor Digitorum Communis [21]. As both muscles exhibit different signal patterns, therefore, a multi-channel input scheme should be employed, so that both signals are gathered independently. Both signals should be observed carefully and a suitable threshold should be set after filtering and amplification. The same procedure is to be followed in order to develop control of all the fingers of the robotic hand i.e. by placing EMG electrodes on specific muscles which control them, allowing us to classify different motions of the hand [22].

The signal observed from a subject with a moderate built is shown in Table 1. The amplification set for the detected EMG signals from the subject was 10,000. Table 1 provides the EMG signal response from each of the subject's fingers after amplification and threshold set for their control [21].

Size is a very important factor while designing an electronics circuit. A circuit occupying minimum space will be most appropriate in application. A size effective circuit will be easy to place and handle in a robotic mechanism. Advances in biomedical instrumentation have brought fruitful gains to robotic prosthetic technology. The ADS1298 is a 64 pin IC with 8 differential inputs with programmable gain amplifiers (PGAs) and a 24 bit ADC. The PGAs can provide a maximum gain of 12 but the 24 bit ADC quantization scheme is enough to process the EMG signal [23]. With all necessary peripherals attached to a single IC, the size of the whole circuitry can be reduced up to 95%.

Latest robotic researches have enabled us to design and create multi-degree of freedom robotic mechanisms [24]. A good mechanical design and apparatus is essential for efficient robotic prosthesis. Newer electronic components and materials have made robotic prosthesis more functional and adaptable. When we talk about materials, the perfect one should be lighter, durable, adjustable and comfortable for the user. Nowadays, carbon fiber frames are being employed as a solution to this matter. An example of a carbon fiber limb is the state of the art Ottoblock C-Leg. The C-Leg has a built in computer which analyzes data from various sensors and actuates the knee using a hydraulic cylinder.

When a human uses a robot, he desires to use his natural limb movements to control the mechanism. In order to achieve this, EMG provides the perfect assistance to allow a subject to make normal movements using a robotic apparatus, hence, efficient controllers and improved algorithms are essential for enhanced control of the device. Given the fact that EMG was introduced more than 30 years ago, the research community has a come a long way in coming up with innovative techniques, hardware solutions and advanced procedures to design, control and utilize these signals to produce resourceful prosthetic means to tackle disabilities and amputations effectively.

Signal Acquisition Using Surface EMG and Circuit Design Considerations for Robotic Prosthesis 447

Due to its practicality and noninvasiveness, SEMG proves to play a significant role in medical applications and rehabilitation prosthesis. However, the human machine interface will decide if the robotic mechanism will be used in everyday life application or not. It is very important to improve the Quality of Life (QOL) of elder and disabled population. It is believed that in the near future, "we will be able to replace entire limbs with prosthetics that can replicate one's own biological functions precisely, casting natural outward appearance

Robotic researchers and biomedical engineers have been trying to combine their techniques to make the perfect biomechatronic mechanism. However, in order to ensure that challenges are met and to create a more smart and intelligent machine, communication between

The study was carried out at College of Electrical and Mechanical Engineering (CEME), NUST in collaboration with Armed Forces Institute of Rehabilitation Medicine (AFIRM). The author is highly indebted to Brig. Dr. Javaid Iqbal and Dr. Umer Shahbaz Khan for their help in the study and CEME for providing necessary funds to make this research possible. Special

[1] Alan G. Outten, Stephen J. Roberts and Maria J. Stokes (1996) "Analysis of human muscle activity", Artificial Intelligence Methods for Biomedical Data Processing, IEE

[2] Musslih LA. Harba and Goh Eng Chee (2002) "Muscle Mechanomyographic and Electromyographic Signals Compared with Reference to Action Potential Average Propagation Velocity", Engineering in Medicine and Biology Society, 19th Annual

[3] Nissan Kunju, Neelesh Kumar, Dinesh Pankaj, Aseem Dhawan, Amod Kumar (2009) "EMG Signal Analysis for Identifying Walking Patterns of Normal Healthy

[4] Carlo J. De Luca (1997) "Use of Surface Electromyography in Biomechanics" Journal of

[5] Carlo J. De Luca (2006) "Electromyography: Encyclopedia of Medical Devices and

thanks to all colleagues and people who have willingly helped out with their abilities.

clinicians, users and engineers should be established on a greater scale.

*National University of Sciences and Technology, Pakistan* 

International Conference of the IEEE, Vol.3

[6] Jarret Smith (2010) image title: "motor-unit-lg"

Individuals" Indian Journal of Biomechanics: Special Issue

Instrumentation" (John G. Webster Ed.), John Wiley Publisher

and requiring minimum upkeep" [26].

**Author details** 

Muhammad Zahak Jamal

**Acknowledgement** 

**8. References** 

Colloquium, London

Applied Biomechanics, Vol.3


**Table 1.** EMG signals observed and the threshold in terms of voltage [17]
