iossifidis Lab
Everyone has experienced muscle fatigue during daily life, but it is more common during physical training or after an illness. In our research project, the muscle fatigue estimator is used as a control unit that regulates the amount of support provided by an exoskeletal system. To be more precise, the estimator is intended to predict … Read More “Muscle Fatigue Estimator (Thesis-Proposal)” »
Consortium: Prof. Dr. Ioannis Iossifidis (PI, consortium lead), Dr. Christian Klaes (PI), Ruhr University Bochum-Knappschaft University Hospital, Prof. Dr. Martin Tegenthoff (PI) Ruhr University- Bergmannsheil University Hospital, Dr. Corinna Weber, Snap GmbH (PI)) Project duration: 01/2020 — 12/2022 Funding volume: € 2.092.917,- Restrictions in hand and arm function are a highly relevant consequence of neurological diseases, … Read More “Virtual reality based Machine Learning for Arm-Hand Function Evaluation and Support System (VAFES)” »
Consortium: Prof. Dr. Ioannis Iossifidis (PI, consortium lead), Dr. Christian Klaes (PI), Ruhr University Bochum-Knappschaft University Hospital, Prof. Dr. Martin Tegenthoff (PI) Ruhr University- Bergmannsheil University Hospital, Dr. Corinna Weber, Snap GmbH (PI)) Project duration: 10/2019 — 09/2022 Funding volume: € 2,084,843 Project REXO is among the winners of the lead market health competition — … Read More “Smart upper extremity rehabilitation with an intelligent soft exoskeleton (REXO)” »
DFG: Emmy-Noether-Grand: Dr. Christian Klaes (PI, Coordinator), Prof. Dr. Kirsten Schmieder (PI), Prof. Dr. Ioannis Iossifidis (PI).03/2016 — 02/2021 Tetraplegic patients are paralyzed from the neck down. Their severe condition is often the result of car accidents or falls. According to the National Spinal Cord Injury Statistical Center approximately 160.000 persons in the USA are … Read More “Motor‐parietal cortical neuroprosthesis with somatosensory feedback for restoring hand and arm functions in tetraplegic patients” »
Brain-computer interface (BCI) systems are a rapidly growing technology that controlsexternal devices, e.g. a neuroprosthetic limb, by directly decoding intended movements from the recorded neural activities and bypassing the spinal cord. Decoding neural activity is a two-step process, feature vector extraction and classification/regression. In online BCI applications, non-stationary behavior of neural signals makes the process of … Read More “Spike-Deeptector in conjunction with artifact rejector: A deep-learning based feature extractor for online invasive BCI applications (Thesis-Proposal)” »
contact: Muhammad Ayaz Hussain, M. Sc., Tel: +49 208 88254806muhammad.hussain@hs-ruhrwest.de A brushless dc (BLDC) motor drive is characterized by higher efficiency, lower maintenance, and higher cost. In a market driven by profit margins, the appliance industry is reluctant to replace the conventional motor drives with the advanced motor drives (BLDC) due to their higher cost. … Read More “Control of a Brushless DC Motor (Thesis-Proposal)” »
Reinforcement Learning (RL) is a subdomain of machine learning that has developed rapidly in recent years and has become increasingly popular. In reinforcement learning an agent learns from experience using a scalar reward signal, in contrast to learning from examples of labelled data as it is done in supervised machine learning. The agent interacts with … Read More “Comparing and Evaluating Prioritized Experience Replay Methods in Reinforcement Learning (Thesis-Proposal)” »
Reinforcement Learning (RL) is a subdomain of machine learning that has developed rapidly in recent years and has become increasingly popular. In reinforcement learning an agent learns from experience using a scalar reward signal, in contrast to learning from examples of labelled data as it is done in supervised machine learning. The agent interacts with … Read More “Comparing and Evaluating Distributional Reinforcement Learning Methods (Thesis Proposal)” »
Interview with Professor Ioannis Iossifidis, Head of Robotics and BCI Laboratory, Ruhr West University of Applied Sciences published at Medica Magazine Read the whole interview: https://www.medica-tradefair.com/en/News/Interviews/Previous_Interviews/Interviews_2020/Sensor-Based_Smart_Glove_Enables_Parkinson_s_Diagnosis
Journal of Neural Engineering: https://iopscience.iop.org/article/10.1088/1741-2552/ab1e63 In electrophysiology, microelectrodes are the primary source for recording neural data (single unit activity). These microelectrodes can be implanted individually or in the form of arrays containing dozens to hundreds of channels. Recordings of some channels contain neural activity, which are often contaminated with noise. Another fraction of channels does … Read More “SpikeDeeptector: a deep-learning based method for detection of neural spiking activity” »
