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. 2018 Oct 4:2018:9634184.
doi: 10.1155/2018/9634184. eCollection 2018.

Towards Ultra Low-Cost Myoactivated Prostheses

Neethu Sreenivasan  1 , Diego Felipe Ulloa Gutierrez  1 , Paolo Bifulco  2 , Mario Cesarelli  2 , Upul Gunawardana  1 , Gaetano D Gargiulo  1   3
Affiliations

Towards Ultra Low-Cost Myoactivated Prostheses

Neethu Sreenivasan et al. Biomed Res Int. .

Abstract

In developing countries, due to the high cost involved, amputees have limited access to prosthetic limbs. This constitutes a barrier for this people to live a normal life. To break this barrier, we are developing ultra-low-cost closed-loop myoactivated prostheses that are easy to maintain manufacture and that do not require electrodes in contact with the skin to work effectively. In this paper, we present the implementation for a simple but functional hand prosthesis. Our simple design consists of a low-cost embedded microcontroller (Arduino), a wearable stretch sensor (adapted from electroresistive bands normally used for "insulation of gaskets" against EM fields), to detect residual muscle contraction as direct muscle volumetric shifts and a handful of common, not critical electronic components. The physical prosthesis is a 3D printed claw-style two-fingered hand (PLA plastic) directly geared to an inexpensive servomotor. To make our design easier to maintain, the gears and mechanical parts can be crafted from recovered materials. To implement a closed loop, the amount of closure of prosthesis is fed back to the user via a second stretch sensor directly connected to claw under the form of haptic feedback. Our concept design comprised of all the parts has an overall cost below AUD 30 and can be easily scaled up to more complicated devices suitable for other uses, i.e., multiple individual fingers and wrist rotation.

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Figures

Figure 1
Figure 1
Circuit diagram of ERB sensors for ASEMG detection, limited to only one ERB (see text).
Figure 2
Figure 2
3D printed hand of the feedback ERB is visible (see text) and the connection to the circuitry has been removed to avoid clutter in the figure.
Figure 3
Figure 3
Circuit diagram of servomotor current sensing.
Figure 4
Figure 4
Circuit diagram of user feedback with span control.
Figure 5
Figure 5
Circuit diagram of vibration buzzer in feedback control.
Figure 6
Figure 6
Device test setup (1: ASEMG circuit, 2: Arduino Nano, 3: mechanical claw with feedback band, and 4: vibration motor).
Figure 7
Figure 7
PCB assemblies: (a) ASEMG detection circuit; (b) user feedback circuit.
Figure 8
Figure 8
Prototype work mode: (a) hand fully open; (b) hand closing.
Figure 9
Figure 9
Raw signals of ERB sensor (yellow) and filtered and amplified signal (green) on continuous muscular variations.
Figure 10
Figure 10
Oscilloscope results for signals of ERB sensor (yellow) and filtered and amplified signal (green): (a) signal after sudden flexion; (b) signals when fingers are moved.
Figure 11
Figure 11
Raw signals of ERB feedback sensor (yellow) and PWM2 duty signals (green): (a) fingers full closed; (b) fully open.
Figure 12
Figure 12
Arduino serial plotter capture for hand closing: red color represents standard myoelectric potential; blue color represents myoelectric potential detected by ERB bands.
Figure 13
Figure 13
Arduino serial plotter capture for ERB band hand opening: red color represents standard myoelectric potential; blue color represents myoelectric potential detected by ERB bands.
Figure 14
Figure 14
Arduino serial plotter capture for haptic feedback versus claw angle.
See this image and copyright information in PMC

References

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