M. Sc. Patricia Weede

Room B-Audiolab
Kaiserstraße 2, 24143 Kiel, Germany
Phone: +49 431 880-6141
E-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
ORCID: 0009-0003-4617-7805
Google scholar: Link

 

 

Research: Tremor analysis

A tremor of various parts of the body can occur as a symptom of different diseases. These include Parkinson's disease and essential tremor. Both belong to the most common neurological diseases. While Parkinson's disease has other symptoms such as slowed movements or rigid muscles, essential tremor is a description of the disease itself.

Differentiating between different diseases on the basis of the tremor has proven to be difficult. The tremor characteristics of different diseases overlap and cannot be clearly distinguished. Therefore, many misdiagnoses between different diseases occur. Based on a misdiagnosis, a therapeutic approach can lead to a degradation of the symptoms and the course of the disease. 

An analysis of different characteristics and other features of different tremors should be used to increase the accuracy of diagnoses. For this purpose, different sensors, such as EMG or acceleraction sensors, are used to record the respective tremor. In addition, features are extracted that are processed using different machine learning algorithms.

Related topics:

  • Pattern recognition
  • Feature extraction
  • Signal analysis
  • Machine learning

 

Further interests:

  • Real-time digital signal processing
  • Movement analysis
  • Adaptive filters

 

Short CV

Time span Details
2019 - current Research assistant at the Christian-Albrechts-Universität zu Kiel, Kiel, Germany
2017 - 2019 M.Sc. in Electrical and Information Engineering at the Christian-Albrechts-Universität zu Kiel, Kiel, Germany
2012 - 2017 B.Sc. in Electrical and Information Engineering at the HAW Hamburg, Hamburg, Germany
2012 - 2015 Electronics Technician for Equipment and Systems, Field: Medical Technical Equipment, apprenticeship,
Philips Medical Systems, Hamburg, Germany

 

Publications

  1.    

    P. Weede, P.D. Smietana, G. Kuhlenbäumer, G. Deuschl, G. Schmidt: Two-Stage Convolutional Neural Network for Classification of Movement Patterns in Tremor Patients, Information, 15(4): 231, 2024, doi: https://doi.org/10.3390/info15040231

  2.    

    I. S. Schiller, K. Krüger, P. Weede, M. Sopha and G. Schmidt: Real-Time Modification of Voice Quality using VQ-Synth: Exploring Our Perception of Acoustic Voice Perturbations,  Proc. DAGA, Hannover, Germany, 2024

  3.    

    J. Winter, K. Krüger, P. Piepjohn, G. Schmidt: Objective Measures for Speech Evaluation, Biosignale Workshop, 2022, Dresden, Germany

  4.    

    P. Piepjohn, C. Bald, G. Kuhlenbäumer, J.S. Becktepe, G. Deuschl, G. Schmidt: Real-time classification of movement patterns of tremor patients, Biomedical Engineering / Biomedizinische Technik, vol. 67, no. 2, 2022, pp. 119-130. doi: https://doi.org/10.1515/bmt-2021-0140

  5.    

    P. Piepjohn, C. Bald, G. Kuhlenbäumer, G. Deuschl, G. Schmidt: Echtzeitklassifizierung von Bewegungsmustern von Tremorpatienten, Biosignale Workshop, 2020, Kiel, Germany

  6.    

    H. Falk, F. Hopfner, P. Wiegand, P. Piepjohn, G. Schmidt, G. Deuschl, G. Kuhlenbäumer: Sind Smartphones zur akzelerometrischen Messung von Tremores geeignet?, DGN Stuttgart, September 2019