The Experts below are selected from a list of 110673 Experts worldwide ranked by ideXlab platform

Mansow-model Sebastian - One of the best experts on this subject based on the ideXlab platform.

  • Instrumental Assessment of Stepping in Place Captures Clinically Relevant Motor Symptoms of Parkinson’s Disease
    2020
    Co-Authors: Otte Karen, Ellermeyer Tobias, Vater Tim-sebastian, Voigt Marlen, Kroneberg Daniel, Rasche Ludwig, Krüger Theresa, Röhling, Hanna Maria, Kayser Bastian, Mansow-model Sebastian
    Abstract:

    Fluctuations of motor symptoms make clinical assessment in Parkinson's disease a complex task. New technologies aim to quantify motor symptoms, and their Remote Application holds potential for a closer monitoring of treatment effects. The focus of this study was to explore the potential of a stepping in place task using RGB-Depth (RGBD) camera technology to assess motor symptoms of people with Parkinson's disease. In total, 25 persons performed a 40 s stepping in place task in front of a single RGBD camera (Kinect for Xbox One) in up to two different therapeutic states. Eight kinematic parameters were derived from knee movements to describe features of hypokinesia, asymmetry, and arrhythmicity of stepping. To explore their potential clinical utility, these parameters were analyzed for their Spearman's Rho rank correlation to clinical ratings, and for intraindividual changes between treatment conditions using standard response mean and paired t-test. Test performance not only differed between ON and OFF treatment conditions, but showed moderate correlations to clinical ratings, specifically ratings of postural instability (pull test). Furthermore, the test elicited freezing in some subjects. Results suggest that this single standardized motor task is a promising candidate to assess an array of relevant motor symptoms of Parkinson's disease. The simple technical test setup would allow future use by patients themselves

Mansow-model S. - One of the best experts on this subject based on the ideXlab platform.

  • Instrumental assessment of stepping in place captures clinically relevant motor symptoms of Parkinson's disease
    'MDPI AG', 2020
    Co-Authors: Otte K., Ellermeyer T., Vater T.s., Voigt M., Kroneberg D., Rasche L., Krüger T., Röhling H.m., Kayser B., Mansow-model S.
    Abstract:

    Fluctuations of motor symptoms make clinical assessment in Parkinson’s disease a complex task. New technologies aim to quantify motor symptoms, and their Remote Application holds potential for a closer monitoring of treatment effects. The focus of this study was to explore the potential of a stepping in place task using RGB-Depth (RGBD) camera technology to assess motor symptoms of people with Parkinson’s disease. In total, 25 persons performed a 40 s stepping in place task in front of a single RGBD camera (Kinect for Xbox One) in up to two different therapeutic states. Eight kinematic parameters were derived from knee movements to describe features of hypokinesia, asymmetry, and arrhythmicity of stepping. To explore their potential clinical utility, these parameters were analyzed for their Spearman’s Rho rank correlation to clinical ratings, and for intraindividual changes between treatment conditions using standard response mean and paired t-test. Test performance not only differed between ON and OFF treatment conditions, but showed moderate correlations to clinical ratings, specifically ratings of postural instability (pull test). Furthermore, the test elicited freezing in some subjects. Results suggest that this single standardized motor task is a promising candidate to assess an array of relevant motor symptoms of Parkinson’s disease. The simple technical test setup would allow future use by patients themselves

Fayssal Fehli - One of the best experts on this subject based on the ideXlab platform.

F. Filippetti - One of the best experts on this subject based on the ideXlab platform.

  • a web based Remote laboratory for monitoring and diagnosis of ac electrical machines
    IEEE Transactions on Industrial Electronics, 2011
    Co-Authors: A Yazidi, G-a. Capolino, H Henao, F Betin, F. Filippetti
    Abstract:

    This paper deals with the development of a virtual platform for a Web-based Remote Application dedicated to condition monitoring and fault detection for ac electrical machines. The platform is based on several tools developed by using the LabVIEW software. Various techniques of condition monitoring and diagnosis of electrical and mechanical faults in ac electrical machines have been integrated such as the broken rotor bar, winding short circuit, bearing damage, or static/dynamic eccentricities. The main features are related to a user-friendly interface, a low-maintenance source code, and a standardized database for ac electrical machine diagnosis. The platform architecture, as well as three different test-rig configurations, has been described. The complete system can be controlled in both local and Remote modes by using a simple Internet connection. Some Remote experiences have been carried out between the University of Picardie “Jules Verne,” Amiens, France, and the University of Bologna, Bologna, Italy, to verify the effectiveness of the proposed system. The direct Applications of this original package are based on diagnosis techniques applied to ac electrical machine faults. Some examples of rotor broken bar detection using classical techniques have been presented to show the effectiveness of the proposed platform. Further information will soon be available on the Open European Laboratory on Electrical Machines Web site: www.oelem.org.

Otte K. - One of the best experts on this subject based on the ideXlab platform.

  • Instrumental assessment of stepping in place captures clinically relevant motor symptoms of Parkinson's disease
    'MDPI AG', 2020
    Co-Authors: Otte K., Ellermeyer T., Vater T.s., Voigt M., Kroneberg D., Rasche L., Krüger T., Röhling H.m., Kayser B., Mansow-model S.
    Abstract:

    Fluctuations of motor symptoms make clinical assessment in Parkinson’s disease a complex task. New technologies aim to quantify motor symptoms, and their Remote Application holds potential for a closer monitoring of treatment effects. The focus of this study was to explore the potential of a stepping in place task using RGB-Depth (RGBD) camera technology to assess motor symptoms of people with Parkinson’s disease. In total, 25 persons performed a 40 s stepping in place task in front of a single RGBD camera (Kinect for Xbox One) in up to two different therapeutic states. Eight kinematic parameters were derived from knee movements to describe features of hypokinesia, asymmetry, and arrhythmicity of stepping. To explore their potential clinical utility, these parameters were analyzed for their Spearman’s Rho rank correlation to clinical ratings, and for intraindividual changes between treatment conditions using standard response mean and paired t-test. Test performance not only differed between ON and OFF treatment conditions, but showed moderate correlations to clinical ratings, specifically ratings of postural instability (pull test). Furthermore, the test elicited freezing in some subjects. Results suggest that this single standardized motor task is a promising candidate to assess an array of relevant motor symptoms of Parkinson’s disease. The simple technical test setup would allow future use by patients themselves