Exploiting the Intertemporal Structure of the Upper-Limb sEMG: Comparisons between an LSTM Network and Cross-Sectional Myoelectric Pattern Recognition Methods

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Abstract

The use of natural myoelectric interfaces promises great value for a variety of potential applications, clinical and otherwise, provided a computational mapping between measured neuromuscular activity and executed motion can be approximated to a satisfactory degree. However, prevalent methods intended for such decoding of movement intent from the surface electromyogram (sEMG) based on pattern recognition typically do not capitalize on the inherently time series-like nature of the acquired signals. In this paper, we present the results from a comparative study in which the performances of traditional cross-sectional pattern recognition methods were compared with that of a classifier built on the natural assumption of temporal ordering by utilizing a long short-term memory (LSTM) neural network. The resulting evaluation indicate that the LSTM approach outperforms traditional gesture recognition techniques which are based on cross-sectional inference. These findings held both when the LSTM classifier operated on conventional features and on raw sEMG and for both healthy subjects and transradial amputees.

Detaljer

Författare
Enheter & grupper
Forskningsområden

Ämnesklassifikation (UKÄ) – OBLIGATORISK

  • Annan medicinteknik
Originalspråksvenska
Titel på värdpublikation2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
FörlagIEEE - Institute of Electrical and Electronics Engineers Inc.
ISBN (elektroniskt)978-1-5386-1312-2
ISBN (tryckt)978-1-5386-1312-2
StatusPublished - 2019 jul
PublikationskategoriForskning
Peer review utfördJa
Evenemang41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) - Berlin, Tyskland
Varaktighet: 2019 jul 232019 jul 27

Konferens

Konferens41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
LandTyskland
OrtBerlin
Period2019/07/232019/07/27