Design and technical construction of a tactile display for sensory feedback in a hand prosthesis system

<p>Abstract</p> <p>Background</p> <p>The users of today's commercial prosthetic hands are not given any conscious sensory feedback. To overcome this deficiency in prosthetic hands we have recently proposed a sensory feedback system utilising a "tactile display" on the remaining amputation residual limb acting as man-machine interface. Our system uses the recorded pressure in a hand prosthesis and feeds back this pressure onto the forearm skin. Here we describe the design and technical solution of the sensory feedback system aimed at hand prostheses for trans-radial/humeral amputees. Critical parameters for the sensory feedback system were investigated.</p> <p>Methods</p> <p>A sensory feedback system consisting of five actuators, control electronics and a test application running on a computer has been designed and built. Firstly, we investigate which force levels were applied to the forearm skin of the user while operating the sensory feedback system. Secondly, we study if the proposed system could be used together with a myoelectric control system. The displacement of the skin caused by the sensory feedback system would generate artefacts in the recorded myoelectric signals. Accordingly, EMG recordings were performed and an analysis of the these are included. The sensory feedback system was also preliminarily evaluated in a laboratory setting on two healthy non-amputated test subjects with a computer generating the stimuli, with regards to spatial resolution and force discrimination.</p> <p>Results</p> <p>We showed that the sensory feedback system generated approximately proportional force to the angle of control. The system can be used together with a myoelectric system as the artefacts, generated by the actuators, were easily removed using a simple filter. Furthermore, the application of the system on two test subjects showed that they were able to discriminate tactile sensation with regards to spatial resolution and level of force.</p> <p>Conclusions</p> <p>The results of these initial experiments in non-amputees indicate that the proposed tactile display, in its simple form, can be used to relocate tactile input from an artificial hand to the forearm and that the system can coexist with a myoelectric control systems. The proposed system may be a valuable addition to users of myoelectric prosthesis providing conscious sensory feedback during manipulation of objects.</p

Self-powered wireless carbohydrate/oxygen sensitive biodevice based on radio signal transmission

peer-reviewedHere for the first time, we detail self-contained (wireless and self-powered) biodevices with wireless signal transmission. Specifically, we demonstrate the operation of self-sustained carbohydrate and oxygen sensitive biodevices, consisting of a wireless electronic unit, radio transmitter and separate sensing bioelectrodes, supplied with electrical energy from a combined multi-enzyme fuel cell generating sufficient current at required voltage to power the electronics. A carbohydrate/oxygen enzymatic fuel cell was assembled by comparing the performance of a range of different bioelectrodes followed by selection of the most suitable, stable combination. Carbohydrates (viz. lactose for the demonstration) and oxygen were also chosen as bioanalytes, being important biomarkers, to demonstrate the operation of the self-contained biosensing device, employing enzyme-modified bioelectrodes to enable the actual sensing. A wireless electronic unit, consisting of a micropotentiostat, an energy harvesting module (voltage amplifier together with a capacitor), and a radio microchip, were designed to enable the biofuel cell to be used as a power supply for managing the sensing devices and for wireless data transmission. The electronic system used required current and voltages greater than 44 mu A and 0.57 V, respectively to operate; which the biofuel cell was capable of providing, when placed in a carbohydrate and oxygen containing buffer. In addition, a USB based receiver and computer software were employed for proof-of concept tests of the developed biodevices. Operation of bench-top prototypes was demonstrated in buffers containing different concentrations of the analytes, showcasing that the variation in response of both carbohydrate and oxygen biosensors could be monitored wirelessly in real-time as analyte concentrations in buffers were changed, using only an enzymatic fuel cell as a power supply.PUBLISHEDpeer-reviewe

Myoelectric Control for Hand Prostheses

An investigation of improvements of myoelectric prostheses has been undertaken. The primary aims of this thesis were (1) to generate an accurate prediction of as many hand movement as possible, (2) to produce a training setup for subjects allowing intuitive and instant control over multiple movements, and (3) to reduce the training cycle for the control system to a maximum of a couple of minutes to enable optimizations, e.g., electrode placement. A median of six movements has been predicted with a 100% accuracy. At the initial predictions, a new set-up for training amputees using a data glove has been proposed, and training of less than 30 seconds of off-line learning, as well as direct online learning, has been conducted. Thus, the initial goals were fulfilled. Further, an online learning system has proved to further increase the accuracy and the number of movements performed while the response time for prediction decreased to 50–100 ms

Refined myoelectric control in below-elbow amputees using artificial neural networks and data glove

Purpose: To develop a system for refined motor control of artificial hands based on multiple electromyographic (EMG) recordings, allowing multiple patterns of hand movements. Methods: Five subjects with traumatic below-elbow amputations and 1 subject with a congenital below-elbow failure of formation performed 10 imaginary movements with their phantom hand while surface electrodes recorded the EMG data. In a training phase a data glove with 18 degrees of freedom was used for positional recording of movements in the contralateral healthy hand. These movements were performed at the same time as the imaginary movements in the phantom hand. An artificial neural network (ANN) then could be trained to associate the specific EMG patterns recorded from the amputation stump with the analogous specific hand movements synchronously performed in the healthy hand. The ability of the ANN to predict the 10 imaginary movements off line, when they were reflected in a virtual computer hand, was assessed and calculated. Results: After the ANN was trained the subjects were able to perform and control 10 hand movements in the virtual computer hand. The subjects showed a median performance of 5 types of movement with a high correlation with the movement pattern of the data glove. The subjects seemed to relearn to execute motor commands rapidly that had been learned before the accident, independent of how old the injury was. The subject with congenital below-elbow failure of formation was able to perform and control several hand movements in the computer hand that cannot be performed in a myoelectric prosthesis (eg, opposition of the thumb). Conclusions: With the combined use of an ANN and a data glove, acting in concert in a training phase, amputees rapidly can learn to execute several imaginary movements in a virtual computerized hand, this opens promising possibilities for motor control of future hand prostheses

Characterization of Pneumatic Touch Sensors for a Prosthetic Hand

This paper presents the results from the characterization of pneumatic touch sensors (sensing bulbs) designed to be integrated into myoelectric prostheses and body-powered prostheses. The sensing bulbs, made of silicone, were characterized individually (single sensing bulb) and as a set of five sensors integrated into a silicone glove. We looked into the sensing bulb response when applying pressure at different angles, and also studied characteristics such as repeatability, hysteresis, and frequency response. The results showed that the sensing bulbs have the advantage of responding consistently to pressure coming from different angles. Additionally, the output (pneumatic pressure) is dependent on the size of interacting object applied to the sensing bulb. This means that the sensing bulb will give higher sensation when picking up sharper objects than blunt objects. Furthermore, the sensing bulb has good repeatability, linearity with an error of 2.95± 0.40%, and maximum hysteresis error of 2.39± 0.17% on the sensing bulb. This well exceeds the required sensitivity range of a touch sensor. In summary, the sensing bulb shows potential for use in prosthetic hands

SmartHand tactile display: A new concept for providing sensory feedback in hand prostheses.

Abstract A major drawback with myoelectric prostheses is that they do not provide the user with sensory feedback. Using a new principle for sensory feedback, we did a series of experiments involving 11 healthy subjects. The skin on the volar aspect of the forearm was used as the target area for sensory input. Experiments included discrimination of site of stimuli and pressure levels at a single stimulation point. A tactile display based on digital servomotors with one actuating element for each of the five fingers was used as a stimulator on the forearm. The results show that the participants were able to discriminate between three fingers with an accuracy of 97%, between five fingers with an accuracy of 82%, and between five levels with an accuracy of 79%. The tactile display may prove a helpful tool in providing amputees with sensory feedback from a prosthetic hand by transferring tactile stimuli from the prosthetic hand to the skin at forearm level