PMID- 28671632
OWN - NLM
STAT- MEDLINE
DCOM- 20180529
LR  - 20240326
IS  - 1424-8220 (Electronic)
IS  - 1424-8220 (Linking)
VI  - 17
IP  - 7
DP  - 2017 Jul 3
TI  - A Hybrid FPGA-Based System for EEG- and EMG-Based Online Movement Prediction.
LID - 10.3390/s17071552 [doi]
LID - 1552
AB  - A current trend in the development of assistive devices for rehabilitation, for 
      example exoskeletons or active orthoses, is to utilize physiological data to 
      enhance their functionality and usability, for example by predicting the 
      patient's upcoming movements using electroencephalography (EEG) or 
      electromyography (EMG). However, these modalities have different temporal 
      properties and classification accuracies, which results in specific advantages 
      and disadvantages. To use physiological data analysis in rehabilitation devices, 
      the processing should be performed in real-time, guarantee close to natural 
      movement onset support, provide high mobility, and should be performed by 
      miniaturized systems that can be embedded into the rehabilitation device. We 
      present a novel Field Programmable Gate Array (FPGA) -based system for real-time 
      movement prediction using physiological data. Its parallel processing 
      capabilities allows the combination of movement predictions based on EEG and EMG 
      and additionally a P300 detection, which is likely evoked by instructions of the 
      therapist. The system is evaluated in an offline and an online study with twelve 
      healthy subjects in total. We show that it provides a high computational 
      performance and significantly lower power consumption in comparison to a standard 
      PC. Furthermore, despite the usage of fixed-point computations, the proposed 
      system achieves a classification accuracy similar to systems with double 
      precision floating-point precision.
FAU - Wohrle, Hendrik
AU  - Wohrle H
AD  - DFKI GmbH, Robotics Innovation Center (RIC), Robert-Hooke-Str. 1, D-28359 Bremen, 
      Germany. hendrik.woehrle@dfki.de.
FAU - Tabie, Marc
AU  - Tabie M
AD  - DFKI GmbH, Robotics Innovation Center (RIC), Robert-Hooke-Str. 1, D-28359 Bremen, 
      Germany. marc.tabie@dfki.de.
FAU - Kim, Su Kyoung
AU  - Kim SK
AD  - DFKI GmbH, Robotics Innovation Center (RIC), Robert-Hooke-Str. 1, D-28359 Bremen, 
      Germany. Su-Kyoung.Kim@dfki.de.
FAU - Kirchner, Frank
AU  - Kirchner F
AD  - DFKI GmbH, Robotics Innovation Center (RIC), Robert-Hooke-Str. 1, D-28359 Bremen, 
      Germany. frank.kirchner@dfki.de.
AD  - Robotics Group, Department of Mathematics and Computer Science, University of 
      Bremen, Robert-Hooke-Str. 1, D-28359 Bremen, Germany. frank.kirchner@dfki.de.
FAU - Kirchner, Elsa Andrea
AU  - Kirchner EA
AD  - DFKI GmbH, Robotics Innovation Center (RIC), Robert-Hooke-Str. 1, D-28359 Bremen, 
      Germany. elsa.kirchner@dfki.de.
AD  - Robotics Group, Department of Mathematics and Computer Science, University of 
      Bremen, Robert-Hooke-Str. 1, D-28359 Bremen, Germany. elsa.kirchner@dfki.de.
LA  - eng
PT  - Journal Article
DEP - 20170703
PL  - Switzerland
TA  - Sensors (Basel)
JT  - Sensors (Basel, Switzerland)
JID - 101204366
SB  - IM
MH  - Brain-Computer Interfaces
MH  - Electroencephalography
MH  - Electromyography
MH  - Humans
MH  - *Movement
MH  - Orthotic Devices
MH  - Self-Help Devices
PMC - PMC5539567
OTO - NOTNLM
OT  - brain-computer interfaces
OT  - embedded brain reading
OT  - embedded systems
OT  - fpgas
OT  - mobile computing
OT  - movement prediction
OT  - neuromuscular rehabilitation
COIS- The authors declare no conflict of interest.
EDAT- 2017/07/04 06:00
MHDA- 2018/05/31 06:00
PMCR- 2017/07/01
CRDT- 2017/07/04 06:00
PHST- 2017/04/07 00:00 [received]
PHST- 2017/06/19 00:00 [revised]
PHST- 2017/06/28 00:00 [accepted]
PHST- 2017/07/04 06:00 [entrez]
PHST- 2017/07/04 06:00 [pubmed]
PHST- 2018/05/31 06:00 [medline]
PHST- 2017/07/01 00:00 [pmc-release]
AID - s17071552 [pii]
AID - sensors-17-01552 [pii]
AID - 10.3390/s17071552 [doi]
PST - epublish
SO  - Sensors (Basel). 2017 Jul 3;17(7):1552. doi: 10.3390/s17071552.