This paper shows a computer application developed in visual C # that acquires and sends by Bluetooth signals of electromyography through a wireless bracelet Myo for the control of an engine that simulates the steering wheel of a vehicle. The experiments carried out allow the control of a steering system by EMG signals of the right forearm that in the future can be adapted to a user with reduced mobility in the upper limb or serve as neuromotor rehabilitation therapy through serious games in virtual reality.
International Journal of Mechanical Engineering and Technology (IJMET) Volume 10, Issue 12, December 2019, pp 323-329, Article ID: IJMET_10_12_035 Available online at http://www.iaeme.com/ijmet/issues.asp?JType=IJMET&VType=10&IType=12 ISSN Print: 0976-6340 and ISSN Online: 0976-6359 © IAEME Publication DRIVER ASSISTANCE SYSTEM FOR PEOPLE WITH REDUCED MOBILITY IN UPPER LIMB THROUGH ELECTROMYOGRAPHY SIGNALS Juan D Abril, Oswaldo Rivera, Oscar F Avilés, Mauricio Mauledoux, Rubén Hernández Universidad Militar Nueva Granada, Programa de Ingeniería Mecatrónica, Grupo de Investigación en Mecatrónica DAVINCI, Cr 11 No 101-80 Bogotá D.C, Colombia ABSTRACT This paper shows a computer application developed in visual C # that acquires and sends by Bluetooth signals of electromyography through a wireless bracelet Myo for the control of an engine that simulates the steering wheel of a vehicle The experiments carried out allow the control of a steering system by EMG signals of the right forearm that in the future can be adapted to a user with reduced mobility in the upper limb or serve as neuromotor rehabilitation therapy through serious games in virtual reality Keywords: Assistive Technologies, EMG, Upper limb disability, Gesture Control Armband Cite this Article: Juan D Abril, Oswaldo Rivera, Oscar F Avilés, Mauricio Mauledoux, Rubén Hernández, Driver Assistance System for People with Reduced Mobility in Upper Limb Through Electromyography Signals International Journal of Mechanical Engineering and Technology 10(12), 2019, pp 323-329 http://www.iaeme.com/IJMET/issues.asp?JType=IJMET&VType=10&IType=12 INTRODUCTION Different assistance systems have been developed to help people with reduced mobility to adapt in a vehicle and manage them to achieve independence and less dependence on other people to perform daily tasks, including modifications of: pedal extensions, pears installed in the steering wheels for one-hand operation, adjustment of left or right hand controls and secondary controls by pressing buttons [1] The alternative proposed with this prototype is the analysis of the bioelectrical activity of skeletal muscle oriented due to the electrical potential generated in the forearm (in the range of 0.1-10 mV and from DC levels up to 10kHz) [2], the device selected for detection is the Myo bracelet located on the right forearm of the user, which allows the acquisition of EMG signals and wireless transmission to the computer, which then processes the electrical signal of the gesture made and sends an instruction of the movement of the steering wheel http://www.iaeme.com/IJMET/index.asp 323 editor@iaeme.com Juan D Abril, Oswaldo Rivera, Oscar F Avilés, Mauricio Mauledoux, Rubén Hernández Figure EMG signal of muscle obtained in computer This document shows the methodology developed for the acquisition and processing of electromyographic data resulting from arm movements, performed by the user, to control a steering wheel ELECTROMIOGRAPHIC BIOPOTENTIAL From the diagnosis of the electrical activity characteristic of different types of excitable cells of the nervous, muscular and glandular type, the bioelectric potentials resulting from the electrochemical activity of their membranes can be measured The following are the ranges of the most representative biopotentials of the human body [3], see Table The EMGs signals are collected through bipolar surface electrodes normally located on the skin of the area to be examined These signals provide information about the neuromuscular activity that originates them, essential in clinical diagnosis, rehabilitation and as a source of control for active devices and functional electrical stimulation schemes [4] A comparison between superficial and intramuscular EMGS signals, concluded that the information extracted in the two classes of signals is equally valuable, without finding significant differences in their classification capacity [2], [5] The EMGS signals generated by muscle contraction require a correct identification of the muscular regions involved in the execution of the movements to be classified, due to the high natural electrical resistance of the skin, even with the application of a gel that improves the conductivity which achieves a good contact surface and adhesion with the electrodes Despite these considerations, the signals collected will be too weak, so it is necessary to pre-process filtering and amplification before analysis Table 1: Range of Electromyographic Potential Bio signal Definition Electrocardiogram (ECG) Electroencephalogram (EEG) Electrogastrogram (EGG) Electromyography (EMG) Electroneurogram (ENG) Electrooculogram (EOG) Electroretinogram (ERG) Cardiac electrical activity Cerebral electrical activity Gastric electrical activity Muscle electrical activity Nervous electrical activity Retina-cornea Potential electrical activity of the retina Phonocardiogram (PCG) Heart sounds http://www.iaeme.com/IJMET/index.asp 324 Amplitude range 0.5-4 mV 5-300 µV 10 µV – 1mV 0.1-0.5 mV 0.01-3mV 50-3500 µV 0-900 µV 80 dB (dynamic range) 100 µPa (threshold) Frequency range 0.01-250 Hz DC-150 Hz DC-1 Hz DC-10 kHz DC – 1kHz DC-50 Hz DC-50 Hz 5-2 kHz editor@iaeme.com Driver Assistance System for People with Reduced Mobility in Upper Limb Through Electromyography Signals 3.1 Improvements in the Vehicle for People in Disability Condition The number of people with disabilities in Colombia registered in 2018 is 1,379,001, which corresponds to 2.6% of the total population of the country Among the alterations that most refer 34.1% (470,215) have alterations in the movement of the body, hands, arms and legs; while 26% (350.216) alterations in the nervous system These alterations affect men and women in equal measure 34% In turn, 50% of people with disabilities in Colombia manifest having difficulty performing daily activities such as walking, running and jumping, which suggests involvement in the lower extremities [6] These activities imply that driving can be seriously affected, adding to the disease pictures of depression or frustration, the reason for the dependence generated towards others, because they cannot take care of themselves [7] DRIVING ASSISTANCE SYSTEM With the aim of improving the quality of life of people with pathologies related to decreased mobility in the upper limb, the prototype of a car driving assistance system was developed, which acquires the electromyography signals of the forearm muscle group and through an interface made in Visual C # it allows controlling the movement of a steering wheel that simulates the steering system of a car, to reduce the levels of muscle fatigue generated by the symptoms associated with the aforementioned disorders Figure Figure Prototype of driving assistance system Elements of the Driving Assistance System The system consists of the following elements: System for the acquisition and sending of electromyography signals (Myo bracelet) Graphic interface in computer software Automobile steering emulator Objective of the System Design a management system controlled by electromyography signals to help people with reduced mobility in the upper limb as an alternative to a conventional steering wheel System Characteristics Detection of hand gestures to guide the steering system of a vehicle User interface that allows the validation of the system Execution of movement through a rudder driven by an electric motor http://www.iaeme.com/IJMET/index.asp 325 editor@iaeme.com Juan D Abril, Oswaldo Rivera, Oscar F Avilés, Mauricio Mauledoux, Rubén Hernández The assistance system for driving EMG signals of the muscular group of the forearm works under the following algorithm: Figure Operating algorithm driving assistance system In this case, the rudder position feedback system is performed directly by the user METHODOLOGY 4.1 Acquisition of Electromyography Signals The Myo Bracelet has sensors that record the muscular activity of the forearm It is usually used to control devices wirelessly through a series of gestures that record the electromyography levels of agonist and antagonist muscles corresponding to each gesture For these, the predetermined gestures implemented by the bracelet are shown below [8], [9] Figure Gestures recognized through Myo Additionally, it has application development kits on platforms such as Visual C #, Matlab, Arduino, among others, and from this an application was developed in Visual C # in this project 4.2 Program in Visual C # A reading of the data of each one of the electromyography sensors is developed to detect muscle activation of gestures, in particular we selected gestures, Figure and Figure show: Hand bend greater than 45 ° to turn the steering wheel to the left Hand in neutral position at ° to keep the steering wheel in the current position And extension of the upper hand to 45 ° to turn the steering wheel to the right http://www.iaeme.com/IJMET/index.asp 326 editor@iaeme.com Driver Assistance System for People with Reduced Mobility in Upper Limb Through Electromyography Signals Figure Application in C # and steering wheel driven by Dynamixel engine Figure Positions of the hand From the definition of the problem, a user interface was developed, capable of gathering all the information coming from the sensors, processing it and applying it in the change of direction as the user wishes It was developed on the Microsoft Visual Studio platform, in the visual-oriented programming language Sharp C #, due to the ease of integration of the various SDKs available for both the MyoArmband and the Dynamixel final actuator engine or steering wheel emulator, on which was going to act the algorithm developed 4.3 Sending Driving Instruction Through a serial port at 1Mb / s the instruction determined by the gesture made by the user is sent, the engine where the steering wheel simulates the steering system of a vehicle is rotated ° per second DISCUSSION OF RESULTS Figure shows the way in which the developed software filters the EMG signal to a DC level, with which the rudder can be addressed as desired by the user, the red box represents the EMG signal without any type of processing, the green box shows a rectification of half wave of the signal and finally the purple box shows the signal in DC levels through a retainer of samples http://www.iaeme.com/IJMET/index.asp 327 editor@iaeme.com Juan D Abril, Oswaldo Rivera, Oscar F Avilés, Mauricio Mauledoux, Rubén Hernández Figure Software interface description Figure shows the response of the sensors captured in the forearm muscles of the test subject and how they react to right or left flexion movements Where the activation and deactivation of each muscle group of the forearm (back and front) is clearly differentiated, depending on whether it is an agonist or antagonist according to the movement Sensors and are not considered in the analysis of the gesture, because they are on the border of the muscle groups agonists and antagonists of the two gestures selected Sensors to record the electromyographic signals of the anterior muscular group of the forearm and sensors to of the posterior muscular group Figure Bending Direction Left (orange), Bending Direction Right (blue) CONCLUSION The prototype developed in this project is proposed as a real alternative to be a form of assistance in driving activities for people with reduced mobility in a superior member At the same time, it was demonstrated that it is possible to use surface EMG signals to be applied to these assistance systems, being a non-invasive technique, easy and quick to implement and that does not generate trauma or discomfort when used by users , in this first phase, without any disability On the other hand, it should be noted that the inclusion of biosignals in the control of therapy robots or assistance for human beings is a reality and shows a marked tendency to be http://www.iaeme.com/IJMET/index.asp 328 editor@iaeme.com Driver Assistance System for People with Reduced Mobility in Upper Limb Through Electromyography Signals potentiated in the developments that have to with improving the quality of life of people with some degree of disability Finally, once the feasibility of the development of this type of systems has been verified, the possibility of carrying out a study of functioning in people with some of the underlying pathologies of this project is proposed, as an alternative in neuromuscular rehabilitation and rehabilitation systems, to be perfected through the feedback of the impressions and comments of the diverse patients, and later to include it as a car driving assistance system or complement in therapies with serious games through virtual reality ACKNOWLEDGEMENTS This work was financially supported by the Vicepresidency for Research of Universidad Militar Nueva Granada, through the project ING-2657 REFERENCES [1] Driving to Independence — ―Driver Rehabilitation Test Vehicles‖ [On line] http://drivingtoindependence.com/test-vehicles.html [2] Gila L, Malanda A, Rodríguez Carro.I, Rodríguez Falces J, y Navallas J, ―Métodos de procesamiento y análisis de señales electromiográficas‖, An Sist Sanit Navar., vol 32, pp 27–43, 2009 [3] Guerrero Martínez, Juan F ―Ingeniería Biomédica‖ Curso 2010-2011 Tema 2.1 Biopotenciales [4] Guerrero Martínez, Juan F,‖ Ingeniería Biomédica‖ Curso 2010-2011 Tema Bioseñales [5] Romo, Harold A., Realpe, Judy C., Jojoa, Pablo E Surface EMG Signals Analysis and Its Applications in Hand Prosthesis Control Universidad del Cauca [6] Cush JJ Approach to Articular and Musculoskeletal Disorders In: Kasper D, Fauci A, Hauser S, Longo D, Jameson J, Loscalzo J eds Harrison's Principles of Internal Medicine, 19e New York, NY: McGraw-Hill; 2014 http://accessmedicine.mhmedical.com/content.aspx?bookid=1130§ionid=79750978 Accessed June 01, 2018 [7] Portales Médicos, ―Depresión en Personas Discapacidad y su relación la Funcionalidad Familiar‖ [On line] https://www.revista-portalesmedicos.com/revistamedica/depresion-discapacidad-funcionalidad-familiar/ [8] Gangwar A, ―Myo Gesture Control Armband: In Depth Review‖, Beebom, 21-jul-2016 [9] Myo, ―Welcome to Myo Support‖ [On line]: https://support.getmyo.com/hc/en-us http://www.iaeme.com/IJMET/index.asp 329 editor@iaeme.com ... editor@iaeme.com Driver Assistance System for People with Reduced Mobility in Upper Limb Through Electromyography Signals 3.1 Improvements in the Vehicle for People in Disability Condition The number of people. .. http://www.iaeme.com/IJMET/index.asp 326 editor@iaeme.com Driver Assistance System for People with Reduced Mobility in Upper Limb Through Electromyography Signals Figure Application in C # and steering wheel... http://www.iaeme.com/IJMET/index.asp 328 editor@iaeme.com Driver Assistance System for People with Reduced Mobility in Upper Limb Through Electromyography Signals potentiated in the developments that have to with