E
Ernest Nlandu Kamavuako
Researcher at King's College London
Publications - 106
Citations - 1963
Ernest Nlandu Kamavuako is an academic researcher from King's College London. The author has contributed to research in topics: Computer science & Electromyography. The author has an hindex of 22, co-authored 93 publications receiving 1472 citations. Previous affiliations of Ernest Nlandu Kamavuako include University of Kindu & Aalborg University.
Papers
More filters
Proceedings ArticleDOI
Evaluation of the Myo armband for the classification of hand motions
Irene G. Mendez,B. W. Hansen,C. M. Grabow,E. J. L. Smedegaard,N. B. Skogberg,X. J. Uth,A. Bruhn,Bo Geng,Ernest Nlandu Kamavuako +8 more
TL;DR: The Myo armband is a wireless wearable device, developed by Thalmic Labs, which enables EMG recordings with a limited bandwidth (<100Hz), which implies that MYB may be suitable for pattern recognition applications despite the limitation in the bandwidth.
Journal ArticleDOI
Combined surface and intramuscular EMG for improved real-time myoelectric control performance
TL;DR: The results obtained in this study imply that targeting muscles that are involved in the rotation of the forearm could improve the performance of myoelectric control systems that include both wrist rotation and opening/closing of a terminal device.
Journal ArticleDOI
Classification of EEG signals to identify variations in attention during motor task execution
Susan Aliakbaryhosseinabadi,Ernest Nlandu Kamavuako,Ning Jiang,Dario Farina,Natalie Mrachacz-Kersting +4 more
TL;DR: It is possible to explore user's attention variation when performing motor tasks in synchronous BCI systems with time-frequency features and this is the first step towards an adaptive real-time BCI with an integrated function to reveal attention shifts from the motor task.
Journal ArticleDOI
Surface Versus Untargeted Intramuscular EMG Based Classification of Simultaneous and Dynamically Changing Movements
Ernest Nlandu Kamavuako,Jakob Celander Rosenvang,Ronnie Wedel Horup,Winnie Jensen,Dario Farina,Kevin Englehart +5 more
TL;DR: The results of intramuscular recordings obtained in this study are promising for future use of implantable electrodes, because, besides the value added in terms of potential chronic implantation, the performance is theoretically the same as for surface EMG provided that enough information is captured in the recordings.
Journal ArticleDOI
Influence of the feature space on the estimation of hand grasping force from intramuscular EMG
Ernest Nlandu Kamavuako,Jakob Celander Rosenvang,Mette Frydensbjerg Bøg,Anne Smidstrup,Ema Erkocevic,Marko Jörg Niemeier,Winnie Jensen,Dario Farina,Dario Farina +8 more
TL;DR: The performance of all the features to predict force significantly increased and Willison amplitude (WAMP) and root mean square (RMS) showed the highest R2 values for poly1.