Design of a Flexible Wearable Smart sEMG Recorder Integrated Gradient Boosting Decision Tree Based Hand Gesture Recognition

This paper proposed a wearable smart sEMG recorder integrated gradient boosting decision tree (GBDT) based hand gesture recognition. A hydrogel-silica gel based flexible surface electrode band is used as the tissue interface. The sEMG signal is collected using a neural signal acquisition analog front end (AFE) chip. A quantitative analysis method is proposed to balance the algorithm complexity and recognition accuracy. A parallel GBDT implementation is proposed featuring a low latency. The proposed GBDT based neural signal processing unit (NSPU) is implemented on an FPGA near the AFE. A RF module is used for wireless communication. A hand gesture set including 12 gestures is designed for human-computer interaction. Experimental results show an overall hand gesture recognition accuracy of 91%.

Medienart:

E-Artikel

Erscheinungsjahr:

2019

Erschienen:

2019

Enthalten in:

Zur Gesamtaufnahme - volume:13

Enthalten in:

IEEE transactions on biomedical circuits and systems - 13(2019), 6 vom: 15. Dez., Seite 1563-1574

Sprache:

Englisch

Beteiligte Personen:

Song, Wei [VerfasserIn]
Han, Qingquan [VerfasserIn]
Lin, Zhonghang [VerfasserIn]
Yan, Nan [VerfasserIn]
Luo, Deng [VerfasserIn]
Liao, Yiqiao [VerfasserIn]
Zhang, Milin [VerfasserIn]
Wang, Zhihua [VerfasserIn]
Xie, Xiang [VerfasserIn]
Wang, Anhe [VerfasserIn]
Chen, Yang [VerfasserIn]
Bai, Shuo [VerfasserIn]

Links:

Volltext

Themen:

Journal Article
Research Support, Non-U.S. Gov't

Anmerkungen:

Date Completed 18.05.2020

Date Revised 18.05.2020

published: Print-Electronic

Citation Status MEDLINE

doi:

10.1109/TBCAS.2019.2953998

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM303539208