Christian Klauer

control systems theory and application -- neuroprosthetic systems -- real-time software design


I am a control scientist for application and theory with a focus on autonomous driving vehicles and biomedical engineering. I got my Ph.D. from Technische Universität Berlin, where I was working since 2010 in the Control Systems Group. For almost ten years, my focus was on the investigation of novel control schemes for neuroprosthetic devices to restore lost motor functions in case of stroke and Spinal Cord Injury (SCI).

After my Ph.D., I continued my work as a Postdoctoral Research Fellow in the Neuroingineering section at NearLab, Politecnico di Milano on the restoration of hand functions under paralysis. Today, I am working in the field of autonomous vehicles with TomTom Location Technology Germany GmbH., RG
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Recent Work

Autonomous Driving

Path tracking control, jerk minimization, and motion planning for TomTom's autonomous vehicle. [Submitted to IFAC 2020]

A Grasping-Neuroprosthesis

Electrical stimulation and control to restore paralyzed hand functions. [REF]

Research on feedback controlled Neuro-Prosthetic Systems

Neuro-prosthetic systems using Functional Electrical Stimulation (FES) to restore or support motor functions in neurologically impaired patients are considered. FES stimulated muscles usually behave highly non-linear and time variant. Hence, an often encountered difficulty is the precise control of limb motion by adjusting the stimulation intensity.
The considered topics include:

Recruitment Control

A novel control method (Lambda, λ-control) was developed which linearises the static input non-linearity (recruitment curve) of FES-activated muscles by fast feedback of the detected muscle activity caused by FES. This activity is estimated by the FES evoked electromyogram (eEMG). It could be shown that the developed approach robustly compensates the unwanted effects related to uncertainties and time-variances of the highly nonlinear muscular recruitment behavior. The Lambda-control method allows the precise adjustment of the muscular recruitment. Therefore, the feedback-controlled muscles are much easier to model and to control in Neuro-prosthetic systems.

Applications / Neuroprosthesis

Artificially induced hand functions (DAAD (German Academic Exchange Service), Politecnico di Milano 2018)
Support of the arm elevation in case of a paresis (only weak residual muscle activity in the shoulder deltoid is present) (BMBF (German Federal ministry of Education and Research),, TU-Berlin, 2014-2017)
EEG-based BCI (Berlin Brain-computer interface) for the Linear Control of an Upper-Limb Neuroprosthesis (EU-FP7,, TU-Berlin, 2010-2013)
Restoration of reaching functions (EU-FP7,, TU-Berlin, 2010-2013)

Research on Discrete-Time Control Systems

Because of the pulse-based nature present in Functional Electrical Stimulation, the framework of discrete-time control perfectly suitable for control systems' design. Therefore, the following topics were addressed:

Inertial Measurement Units (IMU)

Feedback control of limb movements requires a measurement of motion information e.g. inter-segment joint angles or velocities. Because of their small size, Inertial Motion Units are a perfect choice. Singal processing employing kinematic models allows obtaining the needed information in real-time.

Open-Source Software Projects (ORTD): A framework for the implementation of advanced real-time control systems aiming to be an open-source alternative to Simulink Coder. It provides features including state machines and, as a real-time capable interpreter is used, sub-simulations that can be exchanged during runtime. Besides, this framework properly handles multiple threads, their communication, allows to synchronize control systems to external events (e.g. even irregular timers or incoming network packages) and provides many other nice features. Because of a high-level schematic-description language -- based on Scilab commands provided by a toolbox -- lower implementation-effort results compared to C/C++.

This framework has grown since 2008 along with the needs for the implementation of the feedback-control schemes in the area of neuroprosthetics.

An axample application, ready to launch in your browser (at least chrome and firefox): The ORTD-interpreter (C++) is running a control system inside a docker container along with node.js (Javascript) to provide a html-based user interface. Source Code


Refereed Articles

Conference and Workshop Papers