Development of cost-effective myoelectric prosthesis
ABSTARCT :
Background: With the loss of an upper limb, activities of daily living (ADL) become more challenging for the affected person.
Functional body powered upper limb prosthesis can replace the functions of upper limb for ADL activities up to some extent. But in higher level of upper limb amputation, it becomes difficult for the patient to manage ADL activities.
The requirement of externally powered prosthesis such as myoelectric prosthesis plays a vital role in this aspect. Description of Problem statement: A myoelectric prosthesis is an externally powered prosthesis which is controlled by muscle contraction (muscle action potential). In market, many variants of myoelectric prostheses are available with various features.
The most important feature of these prostheses is the grasping pattern types and also it indicates about movement of different fingers in prosthesis.
Because it is expensive, access to these high-end prosthesesbecomes challenging for patients with upper limb amputation living in developing nations like India
Even though few myoelectric prostheses are available in market with less cost, but the features are limited and are not working precisely.
Expected Solutions: Experts from different disciplines, such as engineers for creating programs and fabrication of controlling circuits and Prosthetist for fabrication of sockets and fitment of the prostheses are required to design and develop a cost-effective myoelectric prosthesis.
Most important feature of the prosthesis is the grasping pattern which is completely dependent on the prosthetic hand.
Thus, design and fabrication of prosthetic hand also plays a vital role in the complete working mechanism of the prosthesis. Thus, to get a successful result, it is possible to work collaboratively with experts from different discipline.
EXISTING SYSTEM :
To begin with, our inspiration for this design stems from the recent studies of Myoelectric hand prosthesis where prosthetics are controlled by Electromyographic (EMG) signals from the hand or other neighboring parts of the human body1 .
The above-mentioned EMG signal is produced by a muscle when an electrical command signal originated from the brain transmits through nerve cells in order to contract the muscle2 . It has been possible to detect such signal from the appropriate muscles using skin-surface electrodes.
Since the brain signals are originated from the thought process of a person, therefore, essentially a myoelectric hand is controlled by the thoughts of that person.
Recently, many researchers and also commercial companies, mainly in developed countries, designed and marketed such prosthesis3-4 . As for an example, a research team developed an EMG controlled hand with a vibrotactile feedback system and successfully tested on subjects7 .
DISADVANTAGE :
Limited Functionality: Cheaper models may not provide the same range of motion or precision as more expensive counterparts, leading to reduced user satisfaction and capability.
Durability Issues: Cost-cutting measures can lead to the use of lower-quality materials, making the prosthesis less durable and more prone to wear and tear.
Less Customization: Affordable options might not be as customizable to fit individual needs, which can affect comfort and usability for different users.
Reduced Sensor Accuracy: Inexpensive devices may employ lower-quality sensors, resulting in less accurate signal detection and a less responsive experience.
Shorter Lifespan: Cost-effective prostheses might require more frequent repairs or replacements, leading to higher long-term costs for users
PROPOSED SYSTEM :
The new feature is mainly based on the correlation between different channels of EMG signals. The function first creates the correlation data of the adjacent channels or electrodes and then it is integrated to get the SMA (signal magnitude area), which is a statistical measure of the magnitude of a varying quantity.
Then all of the resulting SMA is added to generate SMAT (signal magnitude area of total channels). Finally square root of it is taken which is inspired by RMS (root mean square) .Different tension in different muscle groups gives rise to the individual finger movement.
So the relative similarity or dissimilarity of adjacent electrodes or channels of the EMG signal should be a significant feature to distinguish different gestures. But all the available features focused on the each channel individually. We wanted to create a feature that would focus on the relative strength or pattern of the EMG signal between channels.
All the common classifiers were tested where Quadratic SVM gave the best result. So, the control model is built using this combined feature set and classifier.
ADVANTAGE :
Increased Accessibility: Lower costs make myoelectric prostheses more accessible to a larger population, including those in low-income communities or developing countries.
Broader Adoption: More affordable options can encourage wider adoption among users who might otherwise be deterred by high prices, promoting independence and improved quality of life.
Encouragement of Innovation: The demand for affordable solutions can stimulate innovation in materials and manufacturing processes, potentially leading to new technologies.
Customization Potential: With increased demand, manufacturers may explore new ways to offer customizable features within a budget-friendly framework
Simplicity of Design: Cost-effective prostheses may emphasize simpler designs, which can be easier to maintain and repair, enhancing user experience.
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