Final Report 1, 2013

Transcript

3D Printed Prosthetic Hand with Intelligent EMG Control Timothy Inglis 1007168555 Supervisor: Dr. Leonard MacEachern April 10, 2013 Contents List of Tables 2 List of Figures 2 1 Introduction 7 1.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 1.2 Prosthetic Hand Overview . . . . . . . . . . . . . . . . . . . . . . . . . . 9 2 The Engineering Project 11 2.1 Health and Safety . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 2.2 Engineering Professionalism . . . . . . . . . . . . . . . . . . . . . . . . . 12 2.3 Project Management . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 3 EMG Signals and their Applications in Prosthetics 14 3.1 Fundamentals of Surface Electromyography . . . . . . . . . . . . . . . . . 14 3.2 Application of Electromyography in Prosthetics . . . . . . . . . . . . . . 15 4 EMG Acquisition System 18 4.1 Electrode Selection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 4.2 Pre-Amplification Stage . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 4.3 Signal Digitization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 4.4 Microcontroller Interface . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 5 Digital Signal Processing 22 5.1 Fast Fourier Transform . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 5.2 Advantages of DSP Filtering . . . . . . . . . . . . . . . . . . . . . . . . . 23 6 Grip Pressure Acquisition 24 6.1 Force Sensor Selection . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24 6.2 Force Sensor Integration . . . . . . . . . . . . . . . . . . . . . . . . . . . 24 1 7 User Interface and Hand Actuation System 27 7.1 Theory of Operation for Multi-Input System . . . . . . . . . . . . . . . . 27 7.2 Implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 8 Mechanical Hand Design and Manufacture 33 8.1 Mechanical Design Requirements . . . . . . . . . . . . . . . . . . . . . . 33 8.2 Preliminary design work . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 8.3 3D Modeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35 8.4 Simulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36 8.5 3D Printing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 8.6 Motor Selection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 8.7 Assembly . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 8.8 Testing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41 8.9 Benefits of a 3D printed hand . . . . . . . . . . . . . . . . . . . . . . . . 43 2 List of Tables 1 Number of Discrete Functions Availible in MIUI System . . . . . . . . . 28 2 Active Channels and Their Corresponding Opcode Numbers . . . . . . . 29 3 Implemented Hand Functions and Their Corresponding Opcodes . . . . . 30 4 Turnigy TGY 1501 MG: Hobby Servos . . . . . . . . . . . . . . . . . . . 39 5 Gantt Chart Displaying the Project Schedule for the Fall Term . . . . . . 45 6 Gantt Chart Displaying the Project Schedule for the Winter Term . . . . 46 List of Figures 1 Top Level Overview of the Electronic Control System for the Prosthetic Prototype . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 2 Single Motor Unit Activation Clearly Visible . . . . . . . . . . . . . . . . 14 3 Multiple Motor Unit Activation Appears Extremely Noisy . . . . . . . . 15 4 Myoelectric Arm Control Loop . . . . . . . . . . . . . . . . . . . . . . . . 16 5 Single Channel Amplitude Control . . . . . . . . . . . . . . . . . . . . . 17 6 Duel Channel Amplitude Control . . . . . . . . . . . . . . . . . . . . . . 17 7 Hhalf-cell potentials for various commonly used electrode materials [4, p.196] 19 8 FSR Signal Processing Circuit . . . . . . . . . . . . . . . . . . . . . . . . 25 9 FSR Pressure Distribution Modification . . . . . . . . . . . . . . . . . . . 26 10 Push-Button Implementation of Multiple Impulse User Interface . . . . . 32 11 Basic Mechanical Hand Operation . . . . . . . . . . . . . . . . . . . . . . 34 12 Prototype Hand Assembly . . . . . . . . . . . . . . . . . . . . . . . . . . 35 13 Prototype Hand Printing in Progressy . . . . . . . . . . . . . . . . . . . 37 14 Illistration of PWM signal [1] . . . . . . . . . . . . . . . . . . . . . . . . 39 15 Dorsal Side of Assembled Prototype . . . . . . . . . . . . . . . . . . . . . 40 3 Abstract Electromyography (EMG) is the most common control interface for modern, upperlimb prosthetics. Prosthetics that make use of EMG interfaces are commonly referred to as myoelectric arms. The hands used in these devices are known as myoelectric hands. The costs of commercially available myoelectric hands are very high, ranging in price from $15,000 to $50,000 [2]. Additionally, the repair of these hands usually requires expensive proprietary components and in almost all cases, a trained professional must conduct repairs. For many amputees, in Canada and else ware, this cost barrier makes the use of a myoelectric prosthetic impractical or impossible. At an approximate cost of $15,000, the most affordable and widely used myoelectric hands suffer from a severe lack of functionality compared to a human hand. These commonly used myoelectric hands afford the user only a single grip type: the pinch grip. The EMG control system employed by these hands allows the user to control the hands speed, but they must pay attention at all times when holding an object to avoid crushing it through accidental hand actuation. There are hands that offer dramatically superior functionality when compared to these most affordable hands. For example, the I-Limb and BeBionic hands have individual finger movement and the ability to switch between multiple grips. However, these hands are prohibitively expensive for all but those amputees with the best funding. Recognizing the need for an alternative to currently available technology for those with limited resources, we were able to develop a prototype hand with similar functionally to the more sophisticated myoelectric hands on the market while reducing the cost of the hand to well below that of the most affordable myoelectric hands that are currently available. Our team’s low-cost objective was achieved by developing an inexpensive EMG control platform and a mechanical hand that is designed to be produced inexpensively on a 3D printer. Our goal of achieving a high level of hand functionality was achieved by implementing a user interface that allows many more hand functions to be called by the user than current myoelectric hand control systems. This Multiple Impulse User Interface also reduces the chance of a stray muscle impulse causing unintended actuation of the 4 hand; reducing the mental task load for the user of the device. EMG signals are acquired from the residual limb of the user, amplified and then digitized with a high resolution analog to digital converter. A serial peripheral interface is employed to transfer the digitized signal from the analog to digital converter to a microcontroller which identifies muscle impulses and actuates motors in the printed hand. The function that the mechanical hand preforms is determined by the sequence of impulses produced by the user in quick succession. If the control logic of the hand detects a function call, it will provide haptic feedback to the user alerting them to the device status. A pressure sensor in the thumb of the prosthetic hand provides feedback to the hands control logic, reducing the risk of dropping or crushing an object being held in the device. 5 Acknowledgements I would like to thank my team mates Alim Baytekin, Alborz Erfani, and Natalie Levasseur for all of the hard work and long nights they committed to this project over the school year. I would like to thank Dr. Leonard MacEachern for agreeing to supervise a project that we were all so passionate about and for all the encouragement and advice he provided us. I would like to thank Mark Kilbanov and Nick Stupich who were always willing to answer questions and provide support, even very late into the night and on the weekends. I would like to thank the War Amps and Smiths Prosthetic Services for providing background information and lending their support to the project. I would like to thank the Carleton University Department of Mechanical Engineering, particularly Stephan Biljan, for printing our prototype hand. I would like to thank all the faculty members in the Carleton University Department of Electronics and the Department of Systems and Computer Engineering for all of their collective advice and support. Lastly, I would like to thank the Lab Manager in the Department of Electronics at Carleton University, Nagui Mikhael. Nagui is an incredible individual who takes a personal interest in the success of every student who works in his labs. We could not have completed our prototype without his support. 6 1 Introduction A low-cost 3D printed prosthetic hand with intelligent EMG control was designed in the department of electronics at Carleton University as a fourth year engineering design project. The team members who worked on the project were Alim Baytekin, Alborz Erfani, Natalie Levasseur, and myself. Dr. Leonard MacEachern supervised the design and manufacture of the prototype prosthetic hand. The intention of this report is to provide a technical overview of the design of the prototype that was developed. Particular emphasis will be placed on the design of the mechanical hand, the intelligent motor control logic, haptic feedback implementation, and the integration of all of the individual system components into a functional prototype. 1.1 Background The cost of a modern myoelectric prosthetic hand in Canada ranges from $15,000 to $50,000. The average arm amputee owns a more moderately priced device costing about $15,000 [2]. The high cost associated with myoelectric hands creates a significant economic barrier to ownership for many amputees in Canada and abroad. Additionally, hand functionality is limited among these more moderately priced devices. Many of these hands only have the ability to open and close in a single grip. Meanwhile, the functionality afforded by high end, upper-limb prosthetics has never been greater. Products such as the I-Limb and the BeBionic hand operate using independently actuated fingers and are capable of many grips. Unfortunately, the prohibitive costs associated with these devices prevent all except the best funded amputees from taking advantage of this revolutionary technology. There is a clear deficiency of low-cost, high functionality devices in the upper-limb prosthetics market. The goal of this project is to address this deficiency by developing a myoelectric hand that has similar functionally to the most expensive hands available at a cost dramatically lower than the least expensive hands. In order to accomplish this goal, two parallel systems had to be developed: an in- 7 expensive electromechanical hand that was a reasonable analog of a human hand and an inexpensive EMG based control platform. In order to keep the costs down and hasten manufacturing, the team decided that the mechanical hand components should be printed using a 3D printer. For the same reasons, the team decided that the EMG control platform should be comprised of inexpensive, readily available components. 3D Printing technology has been around since 1986 [3]. The cost associated with the technology and the fragility of the parts that were produced prevented the widespread adoption of 3D printing as a manufacturing technique. Over the past few years, this paradigm has begun to shift. Introduction of high quality consumer 3D printers, such as the Makerbot Replicator and the Bits from Bytes RapMan, have made 3D printing available to a much wider audience. There are now more than 24 consumer-grade 3D printers available for under $5000 [4]. The majority of these printers use fused deposition modeling (FDM) as their printing technique, which provides the most robust parts of any 3D printing technology. EMG signal acquisition systems are traditionally composed of analog filters and gain stages for each channel. In order to meet our goal of using fewer components than a traditional EMG acquisition system, our team explored a newer approach to the problem. A high resolution analog to digital converter can be used to capture the signal with a resolution of only a couple hundred Nano Volts. This level of resolution allows all of the filtering to be done in the digital domain. All of the signal processing must be performed on a microcontroller. Fortunately, the cost and accessibility of microcontrollers has been improving over the past few years. Arduino microcontrollers are still a mainstay in the inexpensive microcontroller category, characterized by their low cost and simple C++ based programing environment. Other more powerful microcontrollers are also beginning to enter the market. The fastest Arduino currently available, the DUE, runs at a clock frequency of 84MHz. Even more speed can be found in the Beaglebone, a new, Arduino-sized microcontroller tha operates at up to 700MHz. As the quality of, and access to advanced components and manufacturing techniques 8 improves, many previously specialized applications will begin to see lower cost alternatives. One of these areas of growth is prosthetics and our 3D-printed prosthetic hand exemplifies that trend. 1.2 Prosthetic Hand Overview The low-cost prosthetic hand developed for this project consists of four primary components: a 3D-printed electromechanical hand, an EMG interface, a microcontroller capable of real-time signal processing, and a stable embeded control system. The 3D-printed hand prototype was modeled, printed and assembled for less than $250. The hand contains over 30 components, including 15 unique printed components. It is actuated with high-torque hobby servos that are controlled by pulse width modulated (PWM) signals regulated by the microcontroller, an Arduino Due. Figure 1 shows a basic overview of the hand’s electronic control system. Figure 1: Top Level Overview of the Electronic Control System for the Prosthetic Prototype 9 The EMG interface works by acquiring differential signals from muscle impulses in the residual limb of the user. Those signals are then amplified, and pass them to a high resolution analog to digital converter (ADC). The ADC then outputs the signals over a serial peripheral interface (SPI) to the microcontroller. The Arduino processes the signals by preforming a Fast Fourier Transform (FFT) which converts the signals from the time domain to the frequency domain. Once a signal is in the frequency domain, the magnitude of the relevant frequency bins can be calculated. If the magnitude of these relevant bins exceeds a threshold value, a muscle impulse is said to have been detected on that channel. Control logic embedded in the microcontroller captures combinations of muscle impulses across all of the available channels, henceforth known as opcodes. The control logic analyzes sequences of opcodes, and actuates the motors in the hand in order to perform the function dictated by the given opcode sequence. This novel method of using sequences of opcodes to dictate prosthetic hand function is called a Multiple Impulse User Interface (MIUI). A pressure sensor that resides on the gripping surface of the prosthetic thumb provides feedback to the microcontroller through an onboard ADC. This feedback is used to control the pressure that is applied when the prosthetic hand grips an object. The control system is also equipped with a haptic feedback system, that causes small motors to vibrate in response to a successfully received command. 10 2 The Engineering Project As participants in an engineering project, it was important that our team considered: how our product might affect the health and safety of its users, what the role of ethics and engineering professionalism was in the project, and the way that the project was managed. The ways in which our device might affect the health and safety of users must be addressed at every level of the design process. Myoelectric devices are classified as class 2 medical devices in Canada because they are electrically powered [5]. Special precautions, such as power source isolation must be taken to ensure that the risk of an electric discharge is minimized. As engineering students, it is imperative that we adhere to the professional standards and practices that are expected of professional engineers. The design and manufacture of a prototype that met all of the project objectives prior to the end of the school year would not have been possible without carful and deliberate project planning. A carful division of labor, regular team meetings, and proper time management were essential to the completion of the project. 2.1 Health and Safety There are three primary factors to consider when assessing the electrical safety of any medical device: the magnitude of the potential current, the duration of current flow, and the pathway the current takes. A myoelectric arm carries a large battery capable of driving 3 Amps of DC current in order to power the motors at maximum torque. This is more than sufficient current to cause respiratory paralysis, pain and fatigue. It may also be enough current to trigger a sustained myocardial contraction. A sustained myocardial contraction, though unplesent, is not necessarily fatal. The heart stops beating during the contraction, but a normal heart beat usually returns when current is no longer applied [6, p. 640].So, as long as the current is not sustained for an extended period, lethality is unlikely. The chance of a 3A discharge into the body is small, however, much less current than this, applied to a vulnerable part of the body can still be extreamly dangerous. 11 The path of the current has a significant effect on the seriousness of any electric shock. A microshock occurs if current passes through a persons cardiac tissue. Microshocks are much more likely than macroshocks to be lethal, even with an applied current as small as 10µA [6, p. 653]. Although the magnitude of current that is required to cause fibrillation of the heart is far larger when applied through the skin, due to the potential for harm as a result of small leakage currents passing through cardiac tissue, it is important that proper precautions are taken to prevent leakage currents in production devices. The primary solution for mitigating electrical risk in medical devices is to use an isolated power supply system. Though we did not include proper isolation in this first design iteration, an optical or capacitive isolation stage should be implemented in the next iteration. The isolation stage should be placed between the electrodes on the users residual limb and the microcontroller. This will limit the possible current that the user would be exposed to if there was an electrical discharge into the body. 2.2 Engineering Professionalism Canadian Engineers are bound by legal and Ethical responsibilities, outlined In Ontario by the Professional Engineers of Ontario (PEO) the regulating body for professional engineering in Ontario. The PEO defines these responsibilities in its Code of Ethics, located in section 77 of the Professional Engineers Act[7]. In accordance with the principles outlined in the Code of Ethics, our team acted with courtesy toward one another, other teams and the Carleton University faculty. Our Team also acted professionally by being honest and forthcoming in the face of uncertainty. Team members did not impart a false impression of competence which could have led to delays, mistakes or even dangerous situations for team members or the public. A concerted effort was made to keep records of design decisions and the responsibilities of each team member. These records were developed in the form of the project proposal, the progress report, and countless email interactions. These records will be useful if there is ever any inquiry surrounding the work performed over the course of the project. 12 2.3 Project Management To ensure that all the project objectives were met, the project was sub-divided into four areas of responsibility at the beginning of the school year. Due to the multidisciplinary nature of this undertaking, a carful division of labor was essential to ensure that each team member was contributing in a way that would optimize their skill set. Although there was significant cooperation between all of the group members on every component of the project, the division of labor devised at the projects outset was quite representative of the roles carried out by each of the group members throughout the course of the project. Alborz Erfani developed the EMG interface. This included circuit design of the pre-amplification stage and the ADC stage of the system. It also included the implementation of an SPI driver in the microcontroller to facilitate data acquisition from the ADC. Natalie Levasseur developed the pressure sensor array for grip pressure control. This included selecting a force sensor and modifying it to ensure a consistent response in varying use cases. Natalie also implemented the pressure acquisition stage of the hand control logic; programing the Microcontroller to read the onboard ADC and return actual force values. Alim Baytekin implemented the digital processing of the EMG signals once they were acquired. This included transferring functions from time domain to frequency domain by preforming a real time FFT. Additionally Alim filtered the signal and characterized the muscle impulses on the various channels. The element of this project that I focused on was the design of the mechanical hand, the intelligent motor control logic, haptic feedback implementation, and the integration of all of the individual system components into a functional prototype. In addition to a well-defined division of labor, at the beginning of the project, the group decided on a schedule for the achievement of various project milestones. These included several design and test periods. This schedule was very helpful in ensuring we met the overarching goals of the project on time. A detailed description of the project timeline is given in the Gantt charts given in Table 5 and Table 6 in Appendix A. 13 3 EMG Signals and their Applications in Prosthetics The process of recording and interpreting changes in electrical potential produced by contracting skeletal muscles is called Electromyography or (EMG) [8, p. XV]. EMG signals can be used to detect when a muscle, or group of muscles have contracted. This makes EMG a very good candidate for upper limb prosthetic device control. EMG allows myoelectric hand users to manipulate their artificial limbs using muscles on their residual limb that would otherwise remain unused. 3.1 Fundamentals of Surface Electromyography The basis of skeletal muscle organization is the motor unit (MU). Each MU is composed of a motor nerve fiber attached to a bundle of muscle fibers. A MU is the smallest muscle component that can be activated voluntarily. The activation of a single MU manifests itself as a distributed biopotential due to the superposition of action potentials of all of the muscle fibers in the bundle. Depending on the size of a MU, the amplitude of a measured EMG signal also known as a myoelectric signal is between 20µV and 2000µV [6, p. 145]. The frequencies of interest when recording EMG signals are about 30Hz to 300Hz. When intramuscular probes and proper signal filtering are employed, it is possible to contract the muscle in such a way that the distinctive activation of a single MU can be observed as illustrated in Figure 2. Figure 2: Single Motor Unit Activation Clearly Visible As the force of contraction increases, it becomes impossible to distinguish an individual MU in the time domain signal. The reason for this is a combination of increased MU recruitment (more MUs firing) and increased MU activation rate [8, p. 2]. The result is a time domain signal that resembles stochastic noise as illustrated in Figure 3. 14 Figure 3: Multiple Motor Unit Activation Appears Extremely Noisy This noisy, distributed signal increases the difficulty of isolating the EMG signal from a single muscle. The problem is compounded when a surface EMG(SEMG) acquisition strategy is employed. Unlike intramuscular, needle based myoelectric signal acquisition, SEMG requires a relatively large superficial muscle or pronounced muscle group [8, p. 455]. A closely spaced electrode pair positioned along the muscle fiber is required to acquire a highly localized signal, suitable for a single muscle control channel. If the bipolar electrode pair is spaced a little further apart, then the signal that is recorded will be a spatial and temporal superposition of the electrical activity of all of the active MUs in the muscle group [8, p. 455]. The interpretation of these complex signals is further complicated by electrical noise. The primary source of electrical noise in all bioinstrumentation applications results from capacitive coupling between the human body and power delivery lines. In North America electricity is supplied at about 60Hz, so this is the primary frequency at which noise occurs [9]. The noise is also observed at the harmonic frequencies, integer multiples of 60Hz, including 120Hz and 180Hz. 3.2 Application of Electromyography in Prosthetics A myoelectric hand is an artificial hand whose control system is based on Electromyography . Myoelectric prosthetic devices are controlled by purposeful muscle contractions, usually in the users residual limb. Tight fitting prosthetic sockets hold dry electrodes against prominent superficial muscles or groups of muscles in the users residual limb. 15 These electrodes register surface EMG signals. By carefully controlling muscle contractions, myoelectric arm users are able to open and close basic myoelectric hands and switch between active functions in multi-function hands. The control loop employed in a myoelectric arm is shown in figure 4. Figure 4: Myoelectric Arm Control Loop Myoelectric control systems come in single and multi-channel configurations. Typically, children and those with little muscle in their residual limb are fitted with single channel control systems, while most adults are fitted with two-channel control systems. Using a single muscle per control channel is impractical because it requires precise placement of an electrode pair over the muscle being observed. Muscle group signal acquisition is much more forgiving in the exact placement of the electrodes, which is a major consideration given the tendency of prosthetic sockets to shift while in use. For this reason muscle group signal acquisition is a much more common control approach [8, p. 455]. It is simpler to obtain and process more complex EMG signals than it is to attempt to maintain single muscle channel control in a real world prosthetic. In in order to control a myoelectric prosthesis, features that indicate the intention of the user must be extracted from these complex signals. Most commercially available devices use signal amplitude to elicit a control system response. This control technique is commonly employed in single and multi-channel devices as is shown in Figure 5 and Figure 6 respectively. Pattern recognition control systems have been employed in the past to operate multi16 Figure 5: Single Channel Amplitude Control Figure 6: Duel Channel Amplitude Control function control systems. These systems are not normally used do to their lack of intuitiveness and the basic functionality of most limbs in use today. A limb with only two functions requires a simple control system. 17 4 EMG Acquisition System There are four stages in the EMG acquisition circuit: the Electrodes, the pre-amplification stage, the signal digitization stage, and the interface between the analog to digital converter and the micro controller. This chapter gives a brief overview of these stages, however, a more detail technical examination of the EMG signal acquisition system can be found in the report submitted by Alborz Erfani. 4.1 Electrode Selection An interface is required to acquire biopotential signals generated from voluntary muscle impulses in the residual limb of a myoelectric arm user. Biopotential electrodes are used to meet this requirement. A biopotential electrode is a kind of transducer, converting current carried by ions in the body to current carried by electrons in the electronic circuitry [6, p. 189]. The core process that permits this transduction at the electrode electrolyte interface is a redox chemical reaction that takes between the electrode and electrolyte. The general reaction that occurs is given below. C* ) C n+ + ne− (1) Am− * ) A + me− (2) These reactions occur continuously when the electrode is in contact with the electrolyte, even when there is no current passing across the interface. In the case of no net current, the oxidation and reduction reactions balance. The oxidation reaction dominates when there is net current flow from the electrode to the electrolyte, and the reduction reaction dominates when the net current flow is from the electrolyte to the electrode [6, p. 190]. When an electrode is placed against an electrolyte, the local concentration of ions around the electrode in the electrolyte will change, so the electric potential of the electrolyte in this region will differ from the electric potential in other parts of the electrolytic solution. This potential difference is known as the half-cell potential of the interface. The 18 half-cell potential of an interface is determined by the metal in the electrode, the concentration of ions in the electrolyte solution, and the temperature [6, p. 191]. It is not possible to experimentally measure the half-cell potential of an interface without using another electrode which carries its own half-cell potential. So, as a way of objectively comparing the half-cell potentials of different metals, the standard practice is to measure the half-cell potential of an electrode against a standard hydrogen electrode that has a defined half-cell potential of zero. Figure 7: Hhalf-cell potentials for various commonly used electrode materials [4, p.196] These half-cell potentials are representative of conditions where there is no net current crossing the interface. When there is a current and the observed half-cell potential differs from the zero-current half-cell potential, the electrode is said to be polarized. This difference between the observed half-cell potential and the the zero-current half-cell potential is known as the over-potential [6, p. 192]. There are two possible categories of electrode that can be employed in EMG acquisition. The industry standard for prosthetic control systems is to use use dry electrodes, whose interface is composed of silver. These reusable electrodes are fit into the wall of a prosthetic socket. In our design we employed disposable, pre-gelled, silver/sliver-chloride 19 electrodes. The advantage of these electrodes is that they are much less expensive, readily available and are nearly ideally non-polarizable. This greatly simplifies the modeling of the electrode skin interface. 4.2 Pre-Amplification Stage The amplitude of the electrical signal emitted by a single motor unit is in the range of 20µV to 2000µV [6, p. 145]. These signals must be amplified in order to make use of the entire dynamic range of the ADC, the Texas Instruments ADS1298. In order to achieve this pre-amplification; an instrumentation amplifier with a gain of about 100 was employed for each EMG channel. The instrumentation amplifier that was used was the single supply AD627. 4.3 Signal Digitization Digitization of the signal was preformed by the TI ADS1298, a bioinstrumentation front end, which includes a 24-bit high resolution ADC. The purpose of pre-amplification of the Analog EMG signal is to optimize the utilization of the ADS1298’s dynamic range. The 24-bit ADC more than 16.7 million quantization levels spanning a 5.6V input range. This gives the ADC roughly 341nV of accuracy on each EMG channel. The ADS1298 has many options that are easily programmed by sending opcodes to the device over the Serial Peripheral Interface. This allows the device to be easily customized to suit many different applications. For our application, each analog channel had a gain of 1, full 24-bit resolution was employed and a sampling occurred at a rate of 1kHz. 4.4 Microcontroller Interface Once the EMG signals are digitized, they need to be delivered to the microcontroller for processing. This occurs over a Serial Peripheral Interface (SPI). SPI is a four line interface that allows high frequency serial transmission of digital data. The four lines of an SPI interface are, Master In Slave Out (MISO), Master Out Slave In (MOSI), Chip Select (CS), and Serial Clock (SCLK). The MISO is the line on which serial data is fed 20 into the microcontroller. The MOSI line allows commands to be sent to the ADS1298 from the microcontroller in the form of opcodes. These can be used to change attributes of the ADS1298 operation, such as: the gain applied to each of the analog channels, the resolution of the ADC, and the sampling rate of the analog channels. The CS line must be low in order for the SPI system to function with the ADS1298. In applications where multiple ADS1298s are employed, this line is used to select which device is currently being accessed. In our application there is only one ASD1298, so we are able to permanently tie this line low. The SCLK line dictates the rate of data transfer over the SPI interface. The master device, in our case the microcontroller, supplies a clock signal on the SCLK line. One bite of data is transferred on the MISO and MOSI lines on each clock cycle. This means that SPI communication occurs in full duplex for every bit sent, another bit is received simultaneously. In addition to these four core lines, a fifth line is used when interfacing the ADS1298. The Data Ready (DR) line is used to tell the microcontroller that the ADS1298 has a set of data in its buffer that is ready to be sent. The ADS1298 captures eight channels of data in parallel. With 24 bits of data per channel, this amounts to 192 bits of signal data in each transfer. When the onboard data buffer is full, the ADS1298, sets the data ready pin high. An edge triggered interrupt in the microcontroller begins an ISR which initiates the SPI transfer. At this point the microcontroller begins outputting a serial clock at 2MHz and duplex data transfer begins. There are no opcodes to send to the ADS1298 in normal operation, so zeros flow out of the MOSI line on every clock cycle, while data is being received by the microcontroller on the MISO line. Each time a data transfer is initiated, a 24 bit header containing information about the ADS1298 settings is sent prior to the 192 bits of sample data. So, for every transfer 216 bits of data are sent. Data to be transferred over SPI is broken up, and transferred as a series of 8bit words that can each be interpreted as 2 digit hexadecimal numbers [10]. Once the data has been received by the microcontroller, it is separated by channel and stored in a buffer for signal processing. 21 5 Digital Signal Processing Once an EMG signal has been acquired and digitized by the EMG signal acquisition system, it needs to be processed so that intentional muscle impulses can be detected. This process involves converting the signal information from the time domain to the frequency domain where the meaning of the data can be more easily ascertained. This section gives an overview of the signal processing system, a more detailed description of the system can be found in the report submitted by Alim Baytekin. 5.1 Fast Fourier Transform When the data enters the microcontroller via SPI it needs to be divided into buffers; one for each of the eight channels. The first three eight-bit words that arrive belong to the header and can be ignored. The next three words belong to channel one, the following three to channel two, and so on. Once the buffers are populated with a sufficient number of samples, a Fast Fourier Transform (FFT) is preformed, which converts the data from the time domain to the frequency domain. The Cooley-Tukey FFT algorithm is applied for the conversion. The conversion uses rectangular windowing and takes place for each of the eight channels with a window size of 128 samples. This means that at a sampling frequency of 1000Hz, 128ms are required for the buffers to fill before the first FFT can be calculated. Each time the FFT is calculated, the buffers are purged and new samples repopulate it, and the next FFT is computed. The resulting size of the frequency bins is 7.84576Hz and the latency is 128ms. This latency can be reduced computing the FFT more than once every 128 samples. If each sample that is added to the buffer replaces the oldest sample in the buffer, the FTT could be preformed more often, thereby reducing latency. When an FFT is performed, it returns real and imaginary components which together make up the complex frequency domain signal. In order to extract useful information from this signal, complex values in relevant bins must be converted into magnitudes. These magnitudes can then be compared to a threshold value to determine if muscle 22 contraction has occurred. 5.2 Advantages of DSP Filtering One of the major advantages of preforming signal processing in the digital domain rather than in an analog circuit is that filtering becomes largely unnecessary. As discussed previously, the major source of noise in an EMG signal is power line noise. In North America, power is delivered at a frequency of about 60Hz, so a band of frequency spectrum between 55Hz and 65Hz can simply be ignored when analyzing the EMG signal. This method of signal processing greatly simplifies the hardware design and allows for modification of the filtering system in software. In other parts of the world the frequency of power line noise may differ, but this system easily adapts to these differences by simply ignoring a different part of the spectrum. 23 6 Grip Pressure Acquisition One of the core goals of this project was to develop a system that would regulate the pressure that the prosthetic hand applies to an object it is gripping. In order to accomplish this, a pressure sensor needed to be selected, modified, characterized, and implemented on the hand. The following section gives a brief overview of this process. For a more comprehensive description, please see the final report of Natalie Levasseur. 6.1 Force Sensor Selection Many force sensors were candidates for use in this project. The active component of each of these sensors is a force transducer that converts mechanical pressure into an electrical signal. The type of electrical signal varies for each type of load cell. The two foremost options were a load cell whose resistive characteristic changed with applied pressure, and one for which capacitance characteristics changed with applied pressure. The decision was made to use a Force Sensing Resistor (FSR) for several reasons. First, it is a robust system that can withstand repeated use. Second, it is a commercially manufactured component that is very inexpensive and readily available. Third, the response of an FSR is straightforward to understand and characterize, so integration with the 12-bit ADC on our microcontroller presented no complications. 6.2 Force Sensor Integration Once the pressure sensor was chosen, it was implemented using a simple opamp feedback circuit as was recommended by the manufacturer. This optimized the pressure sensor output for the dynamic range of the 12-bit ADC on the microcontroller. The circuit that was employed is illustrated in figure 8 below. The position of the hand chosen for the force sensor was at the very tip of the thumb. This location was chosen because most of the hand functions that involve holding an object will activate the sensor. In future design iterations, many more force sensors will be incorporated into the device, giving the hand much more control over how an object 24 Figure 8: FSR Signal Processing Circuit is held and what fingers are supplying the pressure. An important consideration in the implementation of the force sensor was how differing force distributions across the surface of the FSR would affect its response. After some experimentation, it was determined that the FSR requires a fairly evenly distributed force across its surface to provide a consistent response. So, the force sensor was modified in an attempt to fulfill this requirement. The modification involved sandwiching a soft piece of rubber between the active surface of the force sensor and a piece of hard plastic as illustrated in figure 9. The result was a sensor that would provide a consistent output when a point force was applied to different areas of the device. 25 Figure 9: FSR Pressure Distribution Modification 26 7 User Interface and Hand Actuation System Once a muscle contraction has been identified by the EMG acquisition system, that information must be processed further to determine what, if any action should be taken by the prosthetic hand. Two factors are considered when determining if an actuation should occur. The first is determining if a multi-input command has been recognized. The second is considering what kind of pressure is being applied at the thumb sensor. 7.1 Theory of Operation for Multi-Input System Our hand uses a pattern based recognition system, herein referred to as the Multiple Impulse User Interface (MIUI). MIUI works by receiving and interpreting combinations of very short EMG impulses and carrying out a pre-determined sequence of commands. For example, if the user had a two electrode channels, Channel A and Channel B, then a possible code would be A-B. This could be the code for the ”Soft-Grip” function that closes the hand around an object until it has a firm, but non-crushing grip. The integrated pressure sensor provides feedback about grip strength and the motor control logic maintains a firm grip, even in the case where there is some slippage. Once the object has been successfully grasped, the user is notified by haptic feedback and they are free to stop paying attention to what their prosthetic hand is doing, feeling confident that it will not let go unless instructed to do so by another code. This ”Soft Grip” example is only one of many functions that can be requested with user customizable codes. The use of the ADS1298 as a front end allows more advanced users to add up to eight channels to various muscle groups on their residual limbs to improve signal acquisition accuracy and increase the number of available functions. The number of functions that can be implemented with this system is dependent on the number of channels being employed and the number of opcodes required to call a function. The number of available opcodes is related to the number of channels by the relationship: O = 2n − 1 27 (3) Where, O is the number of opcodes, and n is the number of channels. This is just the number of possible channel activation combinations minus one. The minus one term simply represents an all null (no contractions detected) opcode which should not be included in any function calls to preserve system stability. The maximum number of functions that can be called is simply the number of possible opcodes raised to the power of the number of opcodes required to call a function: F = (2n − 1)m (4) Where, F is the maximum number of functions that can be called and m is the number of opcodes required for each function call. The ADS1298 provides up to eight input channels and there is no theoretical limit to the number of sequential opcodes that can be used to call a function. However, there are significant trade-offs to consider when using more channels and longer sequences of opcodes. Increasing the number of channels increases the complexity of each opcode, while increasing the number of required opcodes increases latency. A comparison of the number of possible functions relative to the number of channels and required opcodes is given in table 1. Table 1: Number of Discrete Functions Availible in MIUI System 28 A major advantage of MIUI over traditional prosthetic control schemes is the flexibility it offers to the end user. As is evident from table 1 above, the MIUI control system is customizable for each user. A child who receives their first myoelectric arm at the age of three will use a very simple control scheme that requires one or two electrodes and only a single opcode. As the child grows older, they will be able to incrementally increase the number of channels and the number of opcodes they use, increasing the functionality of their hand. 62% of child amputees who register with the War Amps are upper-limb amputees, but only 11% of adult amputees are missing upper-limbs [2]. This suggests that many arm amputees use myoelectric limbs for the vast majority of their lives, which gives them decades to gradually improve their hand’s functionality. This makes a flexible system that can grow with the user an ideal choice for those just beginning to use a prosthetic arm. 7.2 Implementation The control system that was implemented in the prototype hand is a two-channel, two-opcode control system. Figure ?? in Appendix C shows an overview of the prototype MIUI implementation. The MIUI system works by polling the EMG acquisition system to see if any channels have experienced muscle contraction. If no contractions have occurred, then the system continues to poll, waiting for the first contraction. Once a contraction is detected, the system checks to see what channels have been activated and it registers the corresponding opcode. Every possible combination of channel activations is given an opcode number. The opcode numbers assigned for our prototype implementation are given in table 2. Channels with Contraction A B A&B Opcode Number 1 2 3 Table 2: Active Channels and Their Corresponding Opcode Numbers Once the first opcode has been registered, the system begins polling for the second 29 opcode. If no opcode is registered within one second, there is a timeout and the system begins polling for the first opcode again. If a second opcode is registered, the system sets the digital pin that controls haptic feedback to high causing a small motor to vibrate. The control system then activates hand function that corresponds with the opcode sequence. A complete list of hand functions implemented in this prototype and their corresponding opcode sequences are given in table 3. Opcode Sequence 1,1 2,2 3,3 1,2 2,1 3,1 Hand Function Fast Flat Palm Fast Fist Fast Index Finger Point Two Finger Pinch Three Finger Pinch Slow Grip With Pressure Sensor Feedback Table 3: Implemented Hand Functions and Their Corresponding Opcodes The the final position of each servo, the speed of the hand movement, and the maximum pressure that the hand will apply are all pre-defined components of the hand functions. The angle of displacement of each servo is controlled by Pulse Width Modulation. If the hands motors are not in their final position as dictated by the function that has been called, they will move to that position. Some functions change the pulse width of the PWM signal in a single step, causing the servos to move at their top speed; these functions have the prefix ”Fast” in their names. Other hand functions ramp the pulse width up or down in many steps resulting in slower hand movement. With regard to the maximum pressure a function can apply, the prototype hand has two types of functions: those that do not respond to pressure sensor feedback and those that do respond to pressure sensor feedback. The only currently implemented command that responds to pressure sensor feedback is the ”Soft Grip” function mentioned above. In the case of this function, the motors are actuated by slowly ramping down the pulse width of the PWM signal. As the hand slowly closes the pressure sensor is polled. As the pressure on the sensor increases, the resistance of the FSR decreases causing the voltage applied to the ADC to increase. Once this voltage reaches a desired threshold, motor actuation ceases. Finally, after completeng this function, the hand is placed in ”pressure 30 sensitive mode”. While in this mode, the control system will poll for the first opcode again. However, because the last function to be called was pressure sensitive, the hand will continue to poll the pressure sensor approximately every 100ms. If the pressure applied to the sensor drops, it is indicative of a slipping object, so the control system will increase tension on the motors to attempt to increase the pressure applied the pressure sensor and to get a stronger grip on the object. The control system will leave ”pressure sensitive mode” as soon as a function that is not pressure dependant is called. This control system was fully implemented prior to the end of the project; however, stability in the EMG acquisition system was not sufficient to interface it with the control system. In order to prove the functionality of the control system, a simple push-button implementation was constructed. Figure 10 shows the push-button implementation. In this implementation, push-buttons were used to simulate confirmed muscle contractions on two channels. In the figure above, the red button is a power button which primes the system for operation. The black button represents channel A and the green button represents channel B. These buttons directly replace the inputs that would otherwise be supplied by the EMG acquisition and signal processing stages. The pushing of a button is equivalent to the contraction of a muscle on the corresponding channel. This push-button implementation worked flawlessly, demonstrating the effectiveness of a simple Multiple Impulse User Interface. 31 Figure 10: Push-Button Implementation of Multiple Impulse User Interface 32 8 Mechanical Hand Design and Manufacture 8.1 Mechanical Design Requirements In order to meet the functionality objectives our team set out for the prosthetic hand, we had to set several design requirements for the mechanical hand component. First, the hand had to be printable using a fused deposition modeling (FDM) 3D printer. FDM provides the most robust physical product of all 3D printing technologies and it is also the technology most widely available in inexpensive consumer grade printers. This makes FDM the most accessible type of 3D printing. Second, the hand must be capable of preforming multiple functions, such as pinch, bat grip, and index point. To accomplish this, at least the thumb and index finger must be actuated independently of any other fingers. Ideally, each finger should be actuated independently. Third, the design should strive to accurately reproduce the look and style of a human hand. There should be four parallel fingers, at least one of which is directly opposed by the thumb, so they can come together in a pinch. 8.2 Preliminary design work The concept of wire actuated fingers came from a simple toy that we were introduced to at the start of the project. Cables running down the palmer side of each finger in the toy caused the fingers to curl toward the palm as tension was applied. When tension on a finger cable was released, the finger associated with that cable was extended due to the elastic force of the bent plastic which was now free to return to its original shape. Prior to modeling the mechanical hand in a solid modeling suite, several cardboard mock ups of the final hand were developed to get a sense of how the final mechanical system would behave. In these mockups, plastic zip-ties were employed to act as both the palmer cables and the elastic recoil mechanism. In a final mock-up, elastic bands were run the length of each finger on the dorsal side of the hand. This is the configuration that was employed in the final prototype design. Figure 11 illustrates the design principles that were employed in this final mock up and in the prototype hand. 33 Figure 11: Basic Mechanical Hand Operation During the course of assembling these mock-ups, it appeared as though it would be possible to implement an antagonistic force scheme for finger actuation. In this scheme, two cables would run the length of each finger; one down the palmer side of the finger and a second down the dorsal side of the finger. Both of the cables would be secured to the same servo, on opposite ends of the actuator arm. When the servo rotated, tension would be applied to the palmer cable while the dorsal cable would be supplied with slack. The advantage of this scheme is that the motors would not be required to work against an elastic force that was constantly working to retract the fingers. The final prototype hand design did include the holes on the dorsal side of each finger that are required to configure this type of actuation system. However, in order to be effective, an additional 34 cable suspension system would have been required as the displacement of the palmer cable was not equal to the displacement of the dorsal cable. This or a similar system of antagonistic actuation will be incorporated into the next design iteration of the prosthetic hand. 8.3 3D Modeling Solid modeling of the 15 unique hand components was performed in Auto Desk Inventor. The index, middle, ring and pinky fingers are each made up of a tip segment, a middle segment and a base segment, which is connected to the palm of the hand. The thumb is composed of just two segments but sits on a raised platform away from the palm, allowing it to directly oppose the other fingers when contracted. Figure 12 shows the assembly of the printed hand as well as the hands major design features. Figure 12: Prototype Hand Assembly 35 The axel holes for each of the joint is 3mm, except for where finger segments interface with the palm, in which case the axel holes were 5mm. The joint channel width differed from joint to join and ranged in size from 1cm to 1.2cm. Each joint key was 1mm narrower than its corresponding joint channel to reduce friction between the channel wall and the channel key. 8.4 Simulation Once initial models of all of the components had been completed, they were virtually assembled inside Autodesk Inventor. This was accomplished by constraining the parts in the model to each other about the axis of revolution of each of the joint that connects them. Virtual assembly of the hand allowed for the examination of the entire system to ensure its mechanical function was adequate. If any feature of a component did not mesh with another component, then modifications to one or both components were performed. There were several features of the mechanical system that had to be examined prior to dynamic simulation in order to ensure basic functionality. First, the holes for the joint axels had to be of equal size and line up for each interfacing part. Second, the width of each joint canal must be slightly larger than the width of the joint key of the interfacing part. I chose to make this difference 1mm. Third, the depth of the joint canal must be large enough to contain the entire joint key of the interfacing part. Once the basic geometry of the components meshed correctly, the model could be simulated dynamically. To accomplish this, a dynamic constraint solver was employed. This function prevents the parts, which are constrained about their respective joint axes from moving through an area that is occupied by another physical object. Simply stated, it prevents the model from moving in a way that would not be possible were it a physical object. If a finger stopped as it was moved through its desired range of motion, it was clear that there was a physical conflict. In this case one or both of the interfering parts would be modified and the motion would be re-simulated. This was an iterative process, requiring dozens of simulations and modifications before a satisfactory model was generated. 36 8.5 3D Printing Upon completion of virtual mechanical simulations, the hand was ready for manufacture. The method of manufacture selected was rapid prototyping on a Fused Deposition Modeling (FDM) 3D printer. Fused Deposition Modeling, also known as Fused Filament Fabrication is a type of additive manufacturing where a thread of molten plastic is used to trace out a layer of a part in the X-Y plane. Once an entire layer is traced, the print platform is lowered and the next layer is printed. The prototype hand model was converted into stereolithography (STL) files in Autodesk Inventor. These STL files were loaded into the printer’s software, arranged for printing, and converted to G code. G code is the control code that provides the printer with instructions regarding the velocity of the print head, extruder temperature and the filament extrusion velocity. The hand parts were printed in 18 hours on a Dimension SST 3D printer. The plastic used to print the prototype hand was Acrylonitrile Butadiene Styrene (ABS) Plastic. The Dimension SST has a layer thickness of 0.254mm. Figure 13: Prototype Hand Printing in Progressy 37 Figure 13 shows the hand about one third of the way into the print. The white material being printed is the ABS plastic that will constitute the finished parts and the black printed material is support material that dissolves when exposed to a weakly basic solution. After the print is complete, parts are submerged in a bath of basic solution and the support material takes about one hour to dissolve away. 8.6 Motor Selection Hobby servos are DC motors that have internal gearing, integrated motor drivers and internal feedback systems. Hobby servos were selected for use in this first prototype of our prosthetic hand because their inclusion greatly simplified the design and helped to ensure that there was a working prototype for the end of the project. The servos used in this project are single-rotation servos, meaning they are unable to continuously rotate and have maximum and minimum angular displacements. The drive shaft of each servos motor is attached to a potentiometer. This provides feedback to the motors internal driver, indicating the current angle of displacement. The motors angular displacement is set by the microcontroller using Pulse Width Modulation (PWM). A PWM signal is a periodic signal with two possible amplitudes 0V and 5V. The two parameters of PWM that can be modified are the frequency of the signal and the duty cycle - the percentage of each cycle where the signal is high. The manufacturer of the servo usually publishes the optimal frequency at which to run the PWM signal. In this case the frequency was 50Hz. Altering the duty cycle alters the pulse width. This is how the motor is directed. An illustration of a PWM signal can be seen in Figure 14. A servo must have a PWM signal to provide torque; even holding torque. The signal provided to a servo has a pulse width of between approximately 1ms and 2ms. One end of the input signal range directs the servo to its minimum angular displacement, while the other end of the range directs the servo to its maximum displacement. Every servo has different tolerances, and it is possible for a servo to strip its internal gears if it is directed to go beyond its minimum or maximum tolerance. The servos that were chosen for this project were Turnigy TGY1501 MG: Hobby 38 Figure 14: Illistration of PWM signal [1] Servos. These operating specifications for this servo are given in Table 4. The primary reason for selecting this servo was the high torque that they can supply at a low pricepoint. When all five servos were at stall, the maximum current draw was approximately 3A. Motor Feature Speed Torque Weight Current Draw Cost Value 0.14s/60 @ 6V 17kg-cm @ 6V 60g 300mA @ Stall Torque $12 each Table 4: Turnigy TGY 1501 MG: Hobby Servos 8.7 Assembly After the printed hand components were manufactured, they were assembled and integrated with the other mechanical components of the hand. The first step in the process was to assemble the printed components. 22 gauge solid copper wire was used as 39 the axel for each of the joints. A single, straight piece of wire was required for each of the 3mm holes and three twisted wires of the same gauge were used in each of the 5mm holes. Wire was used rather than a proper fastener due to the lack of space between fingers. Neither the head of a bolt nor the nut used to secure it would fit in the available space. Unfortunately, there was no room in the design for countersunk bolt holes or embedded nuts. Instead, the wire was secured inside the axel holes with high strength tape. Figure 15: Dorsal Side of Assembled Prototype Once the printed components of the hand were assembled, the dorsal elastics were installed so the fingers would stay extended unless forcefully bent. The elastics were secured to each finger segment and the palm segment with plastic zip-ties. Once this was completed, it was time determine where to place the servos. Many tests were performed with the servos in various locations to see how their 40 configuration effected the actuation of the fingers. It was quickly determined that at least three of the servos would not fit inside the hand itself. To accommodate these motors, a mounting platform was installed just below the palm segment. The mounting platform consisted of a piece of Acrylic secured with a small block of medium density fiber board (MDF). The MDF was secured to the palm segment by two 8cm lengths of 18 gauge steel wires. The mounting platform was further supported by a 1cm long M4 screw connecting it directly to the palm segment. The next step was the installation of the motors. Each servo was secured with M4 screws. Two servos were installed in the body of the hand and the other three servos were installed on the mounting platform. 50lb braded fishing line was used as the palmer cable that would bend each of the fingers. This line was chosen due to its very high tensile strength, its resistance to abrasion and its resistance to stretching. A 30cm length of line was threaded through the palmer channels of each finger. Each line was secured at the palm segment end to a motor and at the fingertip to the zip-tie holding the dorsal elastic in place. 8.8 Testing The prototype hand has been through many rounds of rigorous mechanical testing. Each finger was fully actuated hundreds times, and as a result, many positive and negative aspects of the mechanical design were discovered. We have determined that the cable based actuation system is very effective. This was observed in the early cardboard mockups of the hand; however, the system was not expected to scale to a larger device as effectively as it did. The pressure imparted through the fingers when the motors were fully engaged was considerable. The hand could easily lift a 600g bottle of water and maintain a solid grip despite aggressive agitation. The diverse mechanical functionality of the final product was another positive result. The prototype met the required design goal of effectively preforming several grips with impressive precision. Despite the project being a resounding success, there were many design flaws that 41 will need to be addressed in future design iterations. Firstly, the single-cable-actuated mechanical design requires the motors to work against the dorsal elastics at all times when the fingers are curled. This requires a continuous high current draw by the motors. This is simply unacceptable for a practical prosthetic limb. The next design iteration of the mechanical hand must address this issue first and foremost. The antagonistic force scheme discussed at the beginning of this chapter is a promising candidate to solve this problem. An additional deficiency encountered in this design is the routing of the cables from the finger tips to the motors. The complexity of the cable routing can be seen in figure 15. Abrasion encountered by the high strength fishing line as it rubs against the plastic of the printed components and motors causes frequent line failures. To address this problem, a better cable routing strategy must be developed. Strategically placed bearings or low friction pylons will help to correct this issue, but moving away from fishing line in favor of aircraft cable might be a better long term solution. This solution might prevent the cables from failing, but it may exacerbate another problem the hand is facing. Repeated actuation of the fingers by the high strength motors has begun sawing through the printed parts. Using wire rather than synthetic fishing line will almost certainly increase the rate at which the printed parts degrade. A simple solution to this problem has presented itself during testing. By lining the abrasive surfaces of the hand with stronger and less abrasive materials, the ware on both the hand and the cables has been significantly reduced. Metal sheaths should be used to cover contact points in the future to extend the life of printed components. Additionally, the printed layers of the components should be oriented so that the weakest z-axis layers are not parallel to the actuation cables. This has also played a substantial role in the quick degradation of these parts. Though there are many deficiencies in this first mechanical design, all of these problems can be overcome in future design iterations by applying systematic testing and experimenting with creative solutions. All things considered, this mechanical design has been a definite success. 42 8.9 Benefits of a 3D printed hand There are two major advantages to producing prosthetic hands with 3D printers. First, it is very inexpensive. The accelerating adoption of consumer grade printers and the decrease in the price of feed stock means that replacement and upgraded parts can now be printed in many materials for only tens of dollars. Second, 3D printing allows for mass customization, a sought after quality in prosthetics. Using this technology, every hand can be designed to meet a specific users needs, including the size of the hand and its complexity. The size of each hand can inexpensively be modeled to match the proportions of the opposite hand. Also, some people lack the fine motor skills, experience or need for an advanced hand with many degrees of freedom and a myriad of functions. Due to the modular nature of the hand design, these users can use a simpler hand and upgrade individual components as they grow and their abilities or preferences change. 43 References [1] Arduino. (2008). pwm [online]. available: http://www.ti.com/lit/ds/symlink/mf10n.pdf. [2] ”national amputee center”. War Amps, March 2013. [3] Carl R. Deckard. ”method and apparatus for producing parts by selective sintering”. 4,863,538, September 1989. [4] Brian Heater. ”the shape of things to come: A consumer’s guide to 3d printers”. http://www.engadget.com/2013/01/29/3d-printer-guide/. [5] Health canada. (2006). guidance for industry- keyword index to assist manufacturers in verifying the class of medical devices [online]. available: http://ec.europa.eu/enterprise/newsroom/cf/ getdocument.cfm?doc id=4761. [6] Michael R. Neuman et al. Medical Instrumentation, Application and Design. John Wiley and Sons Inc., 111 River Street, Haboken, New Jersey, 4th edition, 2010. [7] K. p. nearing. ecor 4995. class lecture. topic:“professional engineers: Responsibilities of regulated profession”, faculty of engineering, carleton university, ottawa, ontario, january 24, 2013. [8] Roberto Merletti et al. Electromyography Physiology, Engineering, and Non-Invasive Applications. John Wiley and Sons Inc., 111 River Street, Haboken, New Jersey, 2004. [9] Delsys. (2002), surface electromyography: Detection and recording [online]. available: http://www.delsys.com/attachments pdf/wp semgintro.pdf. [10] Texas intruments. (2000). low-power, 8-channel, 24-bit analog front-end for biopotential measurements [online]. available: http://arduino.cc/en/tutorial/pwm. 44 Appendix A Gantt chart showing the breakdown of projected tasks throughout the academic year: Fall 2012 Table 5: Gantt Chart Displaying the Project Schedule for the Fall Term 45 Winter 2013 Table 6: Gantt Chart Displaying the Project Schedule for the Winter Term 46