Gravenhorst, Franz

Franz studied Electrical Engineering and Information Technology at KIT (Karlsruhe Institute of Technology, Germany). He received his Diploma (Masters) degree in 2010.
During his studies he specialised in signal processing. Franz spent a semester abroad and worked at the Research & Development department of an automotive company in Detroit (Michigan, USA). There, he performed a study researching signal processing for low-cost radar sensors.
In Germany he worked as teaching assistant at the Institute of Biomedical Engineering where he also wrote his Master thesis about a new approach for T wave extraction in electrocardiogram (ECG) signals.
He joined the Wearable Group at ETH to start his PhD in 2010.
When he is not at his office you most certainly can find him in a rowing boat on the Zürichsee.

Research Interests in Biomedical Signal Processing

• Sensors:
  - electrocardiogram (ECG) sensors
  - electrodermal activity (EDA) devices
• Methods:
  - wavelets
  - short time fourier transform (STFT)
  - principal component analysis (PCA)

Research Projects

MONARCA - Monitoring, treatment and prediction of bipolar Disorder Episodes:

In many fields of medical science, therapists are supported by electrical devices to improve the diagnosis and therapy. But when it comes to mental disorders there is still a lack of knowledge how to detect or even monitor these illnesses with the help of electronic devices. The EU-funded project MONARCA aims on developing a wearable system for handling mental disorders.

Manic depression is a mental disorder (also known as bipolar disorder) which is characterized by repeated relapses of mania and depression.
Therapists are highly interested to have access to relevant physiological and behavioural measures from daily life of the patients. These measures from daily life would enable the therapist to assess early warning signs and to predict the occurrence of manic and depressive episodes in an objective and timely way. However, currently the therapist has no long-term objective measures based on physiology or behaviour from daily life at hand.

The new European research project MONARCA aims on developing and validating mobile technologies for multi-parametric, long term monitoring of behavioural and physiological information relevant to bipolar disorder. It will combine those solutions with an appropriate platform and a set of services into an innovative system for management, treatment, and self-treatment of the disease. This approach is in line with the emerging field of pervasive healthcare: making healthcare available everywhere, any time and to anyone.
As part of MONARCA, the Wearable Computing Lab's contribution will comprise three parts:
(i) further development of existing sensor technology to measure physiological signals,
(ii) implementation of algorithms for detecting user’s mental state on mobile platforms, and
(iii) evaluation of sensor technology and algorithms in medical trials.

[project homepage]

 

Rowing Project:

Rowing is one of the oldest Olympic sports. It exercises all the major muscle groups and improves cardiovascular endurance and muscular strength. We use miniaturized motion sensors on the body and the boat to measure on the water. In collaboration with pro rowers and trainers we investigate possibilities to improve rowing technique and speed.

[project homepage]

Teaching

• Assistant for Wearable Systems I, taught by Prof. Tröster. (Autumn Semester 2010)

Student Projects

Feel free to contact me if you are interested in performing a student project in the field of biomedical signal processing.

Publications

For all IEEE publications please consider the IEEE Copyright Notice:
"Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE."

2011

• An IMU-based Sensor Network to Continuously Monitor Rowing Technique on the Water
  Bernd Tessendorf, Franz Gravenhorst, Bert Arnrich and Gerhard Tröster
  in: Proceedings of the Seventh International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP 2011), Adelaide, Australia, IEEE press, 2011
  [ BiBTeX RIS ]
• Analyzing Rowing Crews in Different Rowing Boats based on Angular Velocity Measurements with Gyroscopes
  Franz Gravenhorst, Bernd Tessendorf, Bert Arnrich, Camille Codoni and Gerhard Tröster
  in: Proceedings of the International Symposium on Computer Science in Sport (IACSS 2011), Shanghai, China, 2011
  [ BiBTeX RIS PDF ]
• Towards a Rowing Technique Evaluation Based on Oar Orientation
  Franz Gravenhorst, Bernd Tessendorf and Gerhard Tröster
  in: International Conference on Pervasive Computing (Pervasive 2011), 2011
  [ BiBTeX RIS ]
• Towards Long Term Monitoring of Electrodermal Activity in Daily Life
  Cornelia Setz, Franz Gravenhorst, Johannes Schumm, Bert Arnrich and Gerhard Tröster
  (2011), in: Accepted for Personal and Ubiquitous Computing Journal
  [ BiBTeX RIS PDF DOI ]