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Alexander Boschmann
University of Paderborn
13Publications
6H-index
70Citations
Publications 13
Newest
#1Alexander Boschmann (University of Paderborn)H-Index: 6
#2Andreas Agne (University of Paderborn)H-Index: 8
Last.Marco Platzner (University of Paderborn)H-Index: 25
view all 6 authors...
Abstract 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 acc...
1 CitationsSource
#1Jan Cedric Mertens (TUM: Technische Universität München)
#2Alexander Boschmann (University of Paderborn)H-Index: 6
Last.Christian Plessl (University of Paderborn)H-Index: 15
view all 4 authors...
The purpose of this research was to develop a wearable, low-cost prototype based on real-time kinematic GPS and a microelectromechanical inertial measurement unit to measure the sprinting velocity of an athlete. The software package RTKLIB was used to calculate the RTK-GPS positions and different Kalman filters were implemented to provide a loosely coupled sensor fusion. With this setup, we performed empirical studies to determine whether the velocities obtained by this novel approach are suffic...
Source
Mar 1, 2017 in DATE (Design, Automation, and Test in Europe)
#1Alexander Boschmann (University of Paderborn)H-Index: 6
#2Georg Thombansen (University of Paderborn)H-Index: 1
Last.Marco Platzner (University of Paderborn)H-Index: 25
view all 5 authors...
The combination of high-density electromyographic (HD EMG) sensor technology and modern machine learning algorithms allows for intuitive and robust prosthesis control of multiple degrees of freedom. However, HD EMG real-time processing poses a challenge for common microprocessors in an embedded system. With the goal set on an autonomous prosthesis capable of performing training and classification of an amputee's HD EMG signals, the focus of this paper lies in the acceleration of the computationa...
Source
#1Alexander Boschmann (University of Paderborn)H-Index: 6
#2Strahinja Dosen (GAU: University of Göttingen)H-Index: 21
Last.Dario Farina (GAU: University of Göttingen)H-Index: 76
view all 5 authors...
In recent years, the field of prosthetics developed immensely, along with a variety of control methods and computer interfaces for prosthetic training. In this work, we present an architecture for an augmented reality training system enabling the user to control a virtual prosthetic hand displayed as an extension of the residual limb using EMG pattern recognition in a stereoscopic augmented reality scene. Validated in online experiments with four able-bodied subjects, the novel system provided a...
4 CitationsSource
Dec 1, 2015 in ReConFig (Reconfigurable Computing and FPGAs)
#1Alexander Boschmann (University of Paderborn)H-Index: 6
#2Andreas Agne (University of Paderborn)H-Index: 8
Last.Marco Platzner (University of Paderborn)H-Index: 25
view all 6 authors...
In recent years, 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 that is 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. Using the Xilinx Zynq as a low-cost of...
6 CitationsSource
Aug 1, 2014 in EMBC (International Conference of the IEEE Engineering in Medicine and Biology Society)
#1Alexander Boschmann (University of Paderborn)H-Index: 6
#2Marco Platzner (University of Paderborn)H-Index: 25
8 CitationsSource
#2Marco PlatznerH-Index: 25
Jul 1, 2013 in EMBC (International Conference of the IEEE Engineering in Medicine and Biology Society)
#1Alexander Boschmann (University of Paderborn)H-Index: 6
#2Barbara Nofen (University of Paderborn)H-Index: 2
Last.Marco Platzner (University of Paderborn)H-Index: 25
view all 3 authors...
Pattern recognition of myoelectric signals in upper-limb prosthesis control has been subject to intense research for several years. However, few systems have yet been successfully clinically implemented. One possible explanation for this discrepancy is that published reports mostly focus on classification accuracy of myoelectric signals recorded under laboratory conditions as the metric for the system's performance. These data are usually acquired only during the static state of the contraction ...
2 CitationsSource
#1Alexander Boschmann (University of Paderborn)H-Index: 6
#2Marco Platzner (University of Paderborn)H-Index: 25
Pattern recognition based myoelectric control schemes are an active field of research. However, there are numerous disparities between current research findings and actual clinical results. In literature, electromyographic signals are usually recorded in a fixed position and used for both, training and testing of the classifier. This supports the test subject in performing repeatable contractions throughout the trials of the experiment and generally results in a high classification accuracy. In ...
11 CitationsSource
Aug 1, 2012 in EMBC (International Conference of the IEEE Engineering in Medicine and Biology Society)
#1Alexander Boschmann (University of Paderborn)H-Index: 6
#2Marco Platzner (University of Paderborn)H-Index: 25
The robustness and usability of pattern recognition based myoelectric control systems degrade significantly if the sensors are displaced during usage. This effect inevitably occurs during donning, doffing or using an upper-limb prosthesis over a longer period of time. Electrode shift has been previously studied but remains an unsolved problem. In this study we investigate if increasing the number of electrode channels and recording locations can improve the degraded classification accuracy cause...
9 CitationsSource
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