Zum Inhalt springen
Menü
Technische Universität München
Technische Universität München

Exoskeleton and Wearables Enhanced Prevention and Treatment

Im TUM Innovation Network eXprt arbeitet ein multidisziplinäres Team aus den Ingenieurwissenschaften, Neurowissenschaften und klinischer Neurologie gemeinsam daran, tragbare Technologien zu entwickeln. Das Projekt stellt Instrumente bereit, um sensomotorische und kognitive Beeinträchtigungen des täglichen Lebens sensibel zu erkennen. Durch Erkenntnisse der Neuroingenieurwissenschaften werden die Forschungsergebnisse verlorene motorische Funktionen effizient kompensieren und so eine Verschlechterung des Zustands verhindern und die Lebensqualität der bedürftigen Menschen verbessern.

Unser Team

Assoziierte Forscher:innen

Promotionen

  • Human Agency and lntentionality in Neuroengineering: Co-Design, Intention Prediction and Neural Correlates of Agency in Brain-Machine Interfaces (Nicholas Berberich)
  • Human model-based control of rehabilitative and assistive exoskeletons (Francesco Bianchin)
  • Human Motion Anomaly Detection - Towards Explainable Systems (Patrick Carqueville)
  • Contactless tactile sensor system for cutaneous perception based on silicon (Tobias Chlan)
  • Neural and behavioural changes associated with motor recovery due to exoskeleton training (Sandra Gigl)
  • A Real-World Data-Driven Approach: Monitoring of Neurological Conditions using a Wearable Sensor-Based System (Paula Villa Fulton)
  • TBD (Lucas Wolski)

Publikationen

  1. Paredes-Acuna, N., Utpadel-Fischler, D., Ding, K. et al. Upper limb intention tremor assessment: opportunities and challenges in wearable technology. J NeuroEngineering Rehabil 21, 8 (2024). doi.org/10.1186/s12984-023-01302-9
  2. Alireza Malekmohammadi, Stefan K Ehrlich, Gordon Cheng: Modulation of theta and gamma oscillations during familiarization with previously unknown music. Brain Research 1800, 2023
  3. Alireza Malekmohammadi, Stefan K. Ehrlich, Josef P. Rauschecker and Gordon Cheng: Listening to familiar music induces continuous inhibition of alpha and low-beta power. JNP Journal of Neurophysiology Volume 19 (6), 2023, 1344-1358
  4. F. Wang, J. R. G. Olvera, N. Thakor and G. Cheng: A Bio-Plausible Approach to Realizing Heat-Evoked Nociceptive Withdrawal Reflex on the Upper Limb of a Humanoid Robot. IEEE Robotics and Automation Letters 8 (6), 2023, 3398-3405
  5. Nouran Adly, Tetsuhiko F. Teshima, Hossein Hassani, George Al Boustani, Lennart J.K. Weiß, Gordon Cheng, Joe Alexander, Bernhard Wolfrum: Printed Silk Microelectrode Arrays for Electrophysiological Recoding and Controlled Drug Delivery. Advanced Healthcare Materials 12 (7), 2023
  6. Gulde, P., Vojta, H., Schmidle, S., Rieckmann, P., & Hermsdörfer, J. (2023). Outside the laboratory assessment of upper-limb laterality in patients with stroke: A cross-sectional study. Stroke, 55(1), 146-155. doi:10.1161/STROKEAHA.123.043657.
  7. Gulde, P., Vojta, H., Schmidle, S., Rieckmann, P., & Hermsdörfer, J. (2023). Going beyond PA: Assessing sensorimotor capacity with wearables in multiple sclerosis—a cross-sectional study. Journal of NeuroEngineering and Rehabilitation, 20(1), 123. doi:10.1186/s12984-023-01247-z
  8. Schmidle, S., Gulde, P., Herdegen, S., Böhme, G.-E., & Hermsdörfer, J. (2022). Kinematic analysis of activities of daily living performance in frail elderly. BMC Geriatrics, 22(1), 244. doi:10.1186/s12877-022-02902-1
  9. Schmidle, S., Gulde, P., Koster, R., Soaz, C., & Hermsdörfer, J. (2023). The relationship between self-reported physical frailty and sensor-based physical activity measures in older adults – a multicentric cross-sectional study. BMC Geriatrics, 23(1), 43. doi:10.1186/s12877-022-03711-2
To top