Lecture 13 and 14 Dimitar Stefanov

Feedback in the prosthesis control Visual observation Transmission of force and pressure through the socket Indirect feedback from the prosthesis to the body (force -, slip- and pressure-transducers mounted to the terminal device plus interface devices attached to the residual limb) bladders, plungers or vibrotactile actuators Force sensors, slip sensors, pressure sensors Interface devices Residual limb or other intact area of the body Terminal device

Prostheses controlled by myoelectric signal (MES) The MES, captured on the surface of the skin, has been exploited as a control source of powered prostheses. In the 1950's the first powered prosthetic limb was built. By 1964, Robert Scott of the University of New Brunswick developed the first control system for prosthetic limbs.

The myoelectric signal (MES)

A single motor unit A motoneuron activates a group of muscle fibres of the motor unit A linear model: A series of excitatory impulses from a motor neuron innervate a group of muscle fibres. The excitatory impulses are separated by the intervals x 1, x 2,.., x n. The motor unit action potential (MUAP) is the electrical response of each impulse. Potentials between the electrodes, placed in proximity to the motor unit, depends on the MUAP. The speed of the pulse wave – from 2 to 6 m/s, in inverse relation to the fibre diameter (Buchtal54) In order to sustain a voluntary muscle contraction, the motor units must be repeatedly activated. Series of MUAPs – motor train.

MES during sustained contractions Control of a skeletal muscle is achieved by: 1.Recruitment *– varying the number and composition of activated motor units 2.Firing rate – varying the rate of activation of the individual motor units. *Size principle of recruitment – the smallest motor units are being recruited first (Henneman65). At a contraction, which is up to 30% from the maximal contraction, the recruitment process in dominated. At a contraction, which is between 30 and 75% from the maximal contraction, the firing rate in dominated in the force production. At a contraction, which is over 75% from the maximal contraction, the force increasing is a result solely of the the firing rate increasing.

*single device – motor or lock belonging to the hand, elbow, or wrist of the prosthesis ** In case of lock, only one channel of MES is required. In case of motor control, two channels of MES are required. *** At each moment, one or more single devices can be operated. Variants of prosthetic devices: 1.One MES** and one single device* 2.One MES and n single devices (at each moment only one single device of the prostheses is controlled) 3.n MES and n single devices*** 4.n MES and m single devices (m>n). At each moment p single devices are operated. ( )

Control information from the MES, which relates to variant 2: Selection of the device, which will be controlled from the MES (choice of a motor or a lock) Information about the speed of the selected single device. Example: The length of the signals from one and the same MES source can determine the device and its level of activation. Short MES for selection of the single device and long lasting MES for activation of the same device. The amplitude of the long signal determines the level of activation of the device. Simple algorithms of prosthetic control: 1.Control signal which relates to the estimated amplitude of the MES (Dorcas, 1966) 2.Control signal which relates to the rate of change of the MES (Childrese, 1969)

Speed control of the motor of the prosthesis: 1.Analogue control (speed, proportional to the amplitude of the control signal) 2.Binary control (The motor is either not activated or moves on a constant speed when the amplitude of the control signal exceeds certain threshold). Analogue control of a simple device Electrodes on agonist/antagonist muscle The result signal determines the direction and the force in the controlled joint. The relationship between a user’s input signals and the movement of the prosthesis’ motorized components is called a control strategy. In the most commonly used myoelectric control strategy a flexor muscle signal is used to close a hand and an extensor muscle signal is used to open the hand. We refer to this as classic myoelectric control.

Block diagram of analogue proportional control

Nonlinear integrator Example: +Vcc R Zener -diode C T1 T2 t v t v output

Binary control

One-channel control of a terminal device

In the past, the control strategy of a powered prosthesis was a built-in feature of the electronic circuit that was sold with the prosthesis. Changing the control strategy meant changing the electronics. Programmable myoelectric control The electronics can be easily programmed to implement the selected strategy.

MyoMicro TM Software product of Variety Ability Systems Inc., Ontario, Canada Software product for easily programming of the electronic control systems from Variety Ability Systems Inc. or Liberty Technology. SPM from VASI Inc.

MyoMicro TM VARIGRIP modules from Liberty Technology.

MyoMicro system Hardware module + software package The MyoMicro software allows selection of a control strategy and programming the circuit board with the selected control strategy using "strategy wizard". The MyoMicro hardware module is connected both to the computer’s parallel port and computer’s serial port. The programmable prosthesis controller is connected also to the same hardware module. Flexible programming - One strategy can be initially used and later the control strategy can be changed.

In MyoMicro, control strategies are described graphically as a collection of primitive building blocks. Three basic types of building blocks: 1.Input devices - correspond to electrodes, touchpads, and switches 2.Signal processors - represent the required modification of the input signals (comparator, differencer, etc.). 3.Motor Controls – power amplifiers which operate the physical effectors (hand, elbow or wrist). Supported control strategies: 1.Proportional Control strategy 2.Digital Control strategy 3."doing more with less“ strategy.

Some "doing more with less“ control strategies: A./ Level-sensitive control The input signal is compared to two preset thresholds. Typically, if the input signal is in the middle region the hand will close. If the input signal is in the high region, i.e., above the upper threshold, the hand will open. When the input signal is in the middle region the output is slightly delayed to avoid inadvertent hand closing while the signal is in transition between the high and low regions. Digital control only Input Signal Time Open Close Level Sensitive System time delay

When the input signal crosses the lower threshold, the system waits for a preset period of time (tens of milliseconds) and then compares the signal to the upper threshold. If the signal is still below the upper threshold after the preset time delay, it is considered to be a slowly rising signal and the hand closes. If the signal exceeds the upper threshold before the end of the delay, it is considered to be a quickly rising signal and the hand opens. Proportional or digital control B./ Rate-sensitive control Input Signal Time Open Close Rate Sensitive System time delay time delay

Control a hand and a wrist with two input signals only. At first the control signals operate the hand (flexors to close, extensors to open). Cocontraction of the flexors and extensors switches control to the powered wrist. A flexor signal will then supinate the wrist and an extensor signal will pronate the wrist. To switch control back to the hand, the user can cocontract again. If no signal is received for a preset period of time, control automatically reverts to the hand. C./ Mode switching control

The prosthesis controller is adjusted and preprogrammed via the computer. MyoMicro possesses option for monitoring of the user’s input signals from electrodes during the adjustment. User can try a variety of different strategies and the best suitable strategy can be found easily. Menu examples:

Other attempts to increase the number of states from the surface MES Usage of many sites (or channels) of amplitude coded information (Schmiedl77, Wirta78, Almstrom81). A vector of features is subject of some pattern recognition. Disadvantage: Requirement of many electrode sites, problems in locating and maintenance of the integrity of patterns. Usage of time-series model (Graupe82, Doershuk83). Disadvantage: sensitivity to the signal amplitude. All methods for incensement the number of signals, commented until now, use steady-state analysis to the MES (signals that are produced during constant muscle effort).

Recent tendency – reduction of the number of electrodes and reduction of the sensitivity to the electrode placement. Multifunction Myoelectric Control Systems (Control of Artificial Limbs using Myoelectric Pattern Recognition) Electrodes placed over a set of muscles Multiple control signals Control system's ability to control more than one device, such as an elbow and a wrist by one MES. Control of prostheses for high-level amputations

Structure of the transient MES MES which coincide with the onset of rapid contractions Hudgins (1991) placed a single pair of surface electrodes over the biceps and triceps and investigated the signals between the electrodes during small isometric and anisometric contractions. Patterns of transient MES, corresponding to flexion/extension of the elbow and pronation/supination of the forearm: Elbow flexionElbow extension Forearm pronationForearm supination

Basmajian (1985) The motor unit recruitment order appears stable for a given task, once the task has been learned. Two channel transient MES patterns Kuruganti (1995) The performance of pattern recognition Hudgins’ myoelectric scheme can be enhanced by using two channels (localized MES) instead of one channel (global MES). The localized activity of the biceps and the triceps can be better analyzed by two sets of closely spaced bipolar electrode pairs.

Patterns of transient MES using two sets of electrode pairs: Elbow flexionElbow extension Forearm pronationForearm supination Biceps Triceps Biceps Triceps Biceps Triceps Biceps Triceps Localization of the signals provides a greater distinction between the classes than one channel.

Hudgins (1991, 1993) investigated the information contents of the transient burst of myoelectric activity accompanying the onset of sudden muscular effort. The Hudgins’ multifunction control scheme for powered upper-limb prosthesis

Time-domain features of the MES are used (zero- crossing, mean absolute value, mean absolute value slope, and trace length) Simple multilayer perception (MLP) ANN is used as a classifier. The controller identified four types of muscle contractions using signals measured from the biceps and triceps.

Multifunction control from a single site Output control signals derived from natural muscle contractions Results from the experiments: Average classification performance – 89% for a group of 15 subjects (9 normally-limbed subjects and 9 persons with limb deficits). Two ways for further improvement of the classification accuracy: 1.Improvement the classifier (type and characteristics) 2.Improvement the means of the signal representation (improvement of the feature set).

1.Although some classifiers possess obviously better characteristics, the effect of the improved classifier to the recognition characteristics is not so significant. 2.The signal representation most significantly affects the classification performance (Bishop 96). } The problem of the signal representation for pattern classification can be broken down into following 3 tasks: 1.Feature extraction 2.Dimensionality reduction 3.Classification. Procedure of signal representation

The transient MES patterns have their structure both in the time and the frequency domain. It is supposed that the better recognition methods should be based on time-frequency representation (time- frequency based feature set). Feature sets based upon the short-time Fourier transformations, the wavelet transform Dimensionality reduction – very important

Difficulties: 1.EMG from muscles other than that which the experimenter intends to record may be included in the signal ("cross-talk“). 2.Relating EMG to individual muscle tension requires independent verification via direct mechanical measurement of individual muscle tension. At present, there is no practical method for reliably making such in-vivo measurements. Relating Surface EMG Amplitude to Joint Torque Ongoing project at the Worchester polytechnic Institute, Dept. of EECS, Relation between the surface EMG amplitude to the tension (or force) produced by individual muscles. non-linear relationship Easier task is finding relations between the surface EMG amplitude and the joint torque. EMG-torque relationship can be modeled as a polynomial relationship in case of constant-posture, nonfatiguing contractions about the elbow.

Example of cable driven, body powered prostheses.