Yazar "Moghaddamnia, Sanam" için listeleme
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Efficiency of deep neural networks for joint angle modeling in digital gait assessment
Alcaraz, Javier Conte; Moghaddamnia, Sanam; Peissig, Jürgen (Springer Open, 2021)Reliability and user compliance of the applied sensor system are two key issues of digital healthcare and biomedical informatics. For gait assessment applications, accurate joint angle measurements are important. Inertial ... -
Functional quality assessment of whole-body vibration training devices based on instantaneous amplitude and frequency of photogrammetric vibration measurements
Moghaddamnia, Sanam; Rofallski, Robin; Luhmann, Thomas; Kaeding, Tobias S. (Medical Engineering & Physics, 2023)The practical use of whole-body vibration training (WBVT) and such research may be negatively influenced by generated vibrations with amplitudes, frequencies, and/or patterns that deviate from preset adjustments on WBVT ... -
A Machine Learning Approach to Predict the Sepsis Status: Analyzing the Connection Between Relevant Laboratory Values and Other Physiological Measurements Obtained in Intensive Care Unit
Sepsis is a life-threatening disease caused by the body's response to an infection, which leads to tissue damage, organ failure and death. According to literature, about 1.7 million Americans each year suffer from sepsis ... -
Monitoring the rehabilitation progress using a DCNN and kinematic data for digital healthcare
Alcaraz, Javier Conte; Moghaddamnia, Sanam; Penner, Maxim; Peissig, Jürgen (Institute of Electrical and Electronics Engineers, 2021)Monitoring the progress of patients during the rehabilitation process after an operation is beneficial for adjusting care and medical treatment in order to improve the patient's quality of life. The supervised methods used ... -
On the efficiency of LSTM in classifying musical impressions from EEG recordings
The objective of this study is the classification of musical impressions with long short-term memory (LSTM) approach using EEG recordings of 20 subjects, while listening to different music genres. For this purpose, a deep ... -
Parameter and feature selection in decision trees for the classification of musical impressions from EEG records
Reliable classification of different emotions is an important issue for emotional interaction between humans and computers. Therefore, this study aims at assessing the performance of decision trees in classifying musical ...
