Many laboratories have begun to develop brain-computer interface (BCI) systems that provide communication and control capabilities to people with severe motor disabilities. Further progress and realization of practical applications depends on systematic evaluations and comparisons of different brain signals, recording methods. read more read lessĪbstract: Many laboratories have begun to develop brain-computer interface (BCI) systems that provide communication and control capabilities to people with severe motor disabilities. Meeting those challenges will accelerate the discovery of principles that govern movement control and improve treatments for individuals with movement pathologies. Developing software that enables a concerted effort from many investigators poses technical and sociological challenges. OpenSim provides a platform on which the biomechanics community can build a library of simulations that can be exchanged, tested, analyzed, and improved through a multi-institutional collaboration. We are using this system to simulate the dynamics of individuals with pathological gait and to explore the biomechanical effects of treatments. We have developed a freely available, open-source software system (OpenSim) that lets users develop models of musculoskeletal structures and create dynamic simulations of a wide variety of movements. Simulations can also be used to identify the sources of pathological movement and establish a scientific basis for treatment planning. Dynamic simulations of movement allow one to study neuromuscular coordination, analyze athletic performance, and estimate internal loading of the musculoskeletal system. read more read lessĪbstract: Dynamic simulations of movement allow one to study neuromuscular coordination, analyze athletic performance, and estimate internal loading of the musculoskeletal system. For the standard 24 h MIT/BIH arrhythmia database, this algorithm correctly detects 99.3 percent of the QRS complexes. The algorithm automatically adjusts thresholds and parameters periodically to adapt to such ECG changes as QRS morphology and heart rate. This filtering permits use of low thresholds, thereby increasing detection sensitivity. A special digital bandpass filter reduces false detections caused by the various types of interference present in ECG signals. It reliably recognizes QRS complexes based upon digital analyses of slope, amplitude, and width. We have developed a real-time algorithm for detection of the QRS complexes of ECG signals. Abstract: We have developed a real-time algorithm for detection of the QRS complexes of ECG signals.
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