Home Research Project Details 3b - Control of multi-joint multi-sensor hand prostheses
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3b - Control of multi-joint multi-sensor hand prostheses

J. Michael Herrmann, Armin Biess, Florentin Wörgötter, and Otto Bock HealthCare GmbH

The project is devoted to the robust and efficient signal analysis of myoelectric data obtained from non-invasive electrode arrays. The goal of the project is the control of prostheses with multiple degrees of freedom and additional sensors based on this data analysis, such that it achieves a flexibility that compares to natural movements.

Advanced prosthetic devices for the upper extremities are usually controlled by myoelectric signals derived from residual or still available muscles. However, conventional transcutaneous recording of movement activity is quite limited in terms of the degrees of freedom that can be controlled reliably and simultaneously. Advances in signal processing and nerve transfer surgery (Kuiken et al. 2007) have considerably improved the achievable signal quality, which now enables some amputees to benefit from recent developments of prosthetic hands. For example, the “Michelangelo” hand (Fig. SP3b) provides proportional control for multi-axial movements, but a complexity reduction had to be achieved by controlling movement synergies rather than the individual degrees of freedom. Even if high-bandwidth signal transduction from the subject to the device is in sight, the information flow in the reverse direction will retain severe limitations. In order to exploit recent advances in robotics in prosthetic devices appropriate feedback signals must be reconstructed from an optimal combination of local sensors and efficient data analysis.



Fig.SP3b: The multidimensional myographic signals (left) are transformed into a space of invariant features. Features are combined with sensory input at the device to achieve flexible control of an advanced hand prosthesis (Michelangelo, on the right).

Belongs to Group(s):
Otto Bock HealthCare GmbH, Self-organization in adaptive systems, Computational motor control theory

Is part of  Section 3 

Members working within this Project:
Herrmann, J. Michael  
Hesse, Frank  
Wörgötter, Florentin 
Biess, Armin 
Graimann, Bernhard  

Selected Publication(s):

Farina, D, Jensen, W, and Akay, M (2013).
Introduction to Neural Engineering for Motor Rehabilitation
Wiley Online Library (ISBN: Print ISBN: 9780470916735 Online ISBN: 9781118628522).

Hass, J, and Herrmann, JM (2012).
The neural representation of time: An information-theoretic perspective
Neural Computation 24(6):1519-1552.

Hass, J, Blaschke, S, and Herrmann, JM (2012).
Cross-modal distortion of time perception: demerging the effects of observed and performed motion
PLoS One 7(6):1-8.

Jiang, N, Dosen, S, Müller, K, and Farina, D (2012).
Myoelectric ̈ control of artificial limbs: is there the need for a change of focus?
IEEE Signal Processing Magazine 152:1-4.

Schrobsdorff, H, Ihrke, M, Behrendt, J, Hasselhorn, M, and Herrmann, JM (2012).
Inhibition in the dynamics of selective attention: an integrative model for negative priming
Frontiers in Psychology 3(Article 491):1-21.

Lorrain, T, Jiang, N, and Farina, D (2011).
Influence of the training set on the accuracy of surface EMG classification in dynamic contractions for the control of multifunction prostheses
J. NeuroEng. & Rehab 8(25):1-9.

Hanushkin, A, Morrison, A, Herrmann, JM, and Diesmann, M (2010).
Compositionality of arm movements can be realized by propagating synchrony
Journal of Computational Neuroscience 30:675-697 doi: 10.1007/s10827-010-0285-9.

Hesse, F, and Herrmann, JM (2010).
Homeokinetic Proportional Control of Myoelectric Prostheses
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2010) October 18-22, 2010.

Hesse, F, and Herrmann, JM (2010).
Homeokinetic Prosthetic Control: Collaborative Selection of Myosignal Features
19th IEEE Int. Symposium in Robot and Human Interactive Communication:410-415.

Jiang, N, Falla, D, d´Avella, A, Graimann, B, and Farina, D (2010).
Myoelectric control in neurorehabilitation
Crit Rev Biomed Eng. 38:381-91.