---
_id: '11950'
abstract:
- lang: eng
  text: Advances in electromyographic (EMG) sensor technology and machine learning
    algorithms have led to an increased research effort into high density EMG-based
    pattern recognition methods for prosthesis control. With the goal set on an autonomous
    multi-movement prosthesis capable of performing training and classification of
    an amputee’s EMG signals, the focus of this paper lies in the acceleration of
    the embedded signal processing chain. We present two Xilinx Zynq-based architectures
    for accelerating two inherently different high density EMG-based control algorithms.
    The first hardware accelerated design achieves speed-ups of up to 4.8 over the
    software-only solution, allowing for a processing delay lower than the sample
    period of 1 ms. The second system achieved a speed-up of 5.5 over the software-only
    version and operates at a still satisfactory low processing delay of up to 15
    ms while providing a higher reliability and robustness against electrode shift
    and noisy channels.
author:
- first_name: Alexander
  full_name: Boschmann, Alexander
  last_name: Boschmann
- first_name: Andreas
  full_name: Agne, Andreas
  last_name: Agne
- first_name: Georg
  full_name: Thombansen, Georg
  last_name: Thombansen
- first_name: Linus Matthias
  full_name: Witschen, Linus Matthias
  id: '49051'
  last_name: Witschen
- first_name: Florian
  full_name: Kraus, Florian
  last_name: Kraus
- first_name: Marco
  full_name: Platzner, Marco
  id: '398'
  last_name: Platzner
citation:
  ama: Boschmann A, Agne A, Thombansen G, Witschen LM, Kraus F, Platzner M. Zynq-based
    acceleration of robust high density myoelectric signal processing. <i>Journal
    of Parallel and Distributed Computing</i>. 2019;123:77-89. doi:<a href="https://doi.org/10.1016/j.jpdc.2018.07.004">10.1016/j.jpdc.2018.07.004</a>
  apa: Boschmann, A., Agne, A., Thombansen, G., Witschen, L. M., Kraus, F., &#38;
    Platzner, M. (2019). Zynq-based acceleration of robust high density myoelectric
    signal processing. <i>Journal of Parallel and Distributed Computing</i>, <i>123</i>,
    77–89. <a href="https://doi.org/10.1016/j.jpdc.2018.07.004">https://doi.org/10.1016/j.jpdc.2018.07.004</a>
  bibtex: '@article{Boschmann_Agne_Thombansen_Witschen_Kraus_Platzner_2019, title={Zynq-based
    acceleration of robust high density myoelectric signal processing}, volume={123},
    DOI={<a href="https://doi.org/10.1016/j.jpdc.2018.07.004">10.1016/j.jpdc.2018.07.004</a>},
    journal={Journal of Parallel and Distributed Computing}, publisher={Elsevier},
    author={Boschmann, Alexander and Agne, Andreas and Thombansen, Georg and Witschen,
    Linus Matthias and Kraus, Florian and Platzner, Marco}, year={2019}, pages={77–89}
    }'
  chicago: 'Boschmann, Alexander, Andreas Agne, Georg Thombansen, Linus Matthias Witschen,
    Florian Kraus, and Marco Platzner. “Zynq-Based Acceleration of Robust High Density
    Myoelectric Signal Processing.” <i>Journal of Parallel and Distributed Computing</i>
    123 (2019): 77–89. <a href="https://doi.org/10.1016/j.jpdc.2018.07.004">https://doi.org/10.1016/j.jpdc.2018.07.004</a>.'
  ieee: A. Boschmann, A. Agne, G. Thombansen, L. M. Witschen, F. Kraus, and M. Platzner,
    “Zynq-based acceleration of robust high density myoelectric signal processing,”
    <i>Journal of Parallel and Distributed Computing</i>, vol. 123, pp. 77–89, 2019.
  mla: Boschmann, Alexander, et al. “Zynq-Based Acceleration of Robust High Density
    Myoelectric Signal Processing.” <i>Journal of Parallel and Distributed Computing</i>,
    vol. 123, Elsevier, 2019, pp. 77–89, doi:<a href="https://doi.org/10.1016/j.jpdc.2018.07.004">10.1016/j.jpdc.2018.07.004</a>.
  short: A. Boschmann, A. Agne, G. Thombansen, L.M. Witschen, F. Kraus, M. Platzner,
    Journal of Parallel and Distributed Computing 123 (2019) 77–89.
date_created: 2019-07-12T13:13:55Z
date_updated: 2022-01-06T06:51:13Z
department:
- _id: '78'
doi: 10.1016/j.jpdc.2018.07.004
intvolume: '       123'
keyword:
- High density electromyography
- FPGA acceleration
- Medical signal processing
- Pattern recognition
- Prosthetics
language:
- iso: eng
page: 77-89
publication: Journal of Parallel and Distributed Computing
publication_identifier:
  issn:
  - 0743-7315
publication_status: published
publisher: Elsevier
status: public
title: Zynq-based acceleration of robust high density myoelectric signal processing
type: journal_article
user_id: '398'
volume: 123
year: '2019'
...