Carlos Torres

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Accurate respiration measurement is crucial in motion-adaptive cancer radiotherapy. Conventional methods for respiration measurement are undesirable because they are either invasive to the patient or do not have sufficient accuracy. In addition, measurement of external respiration signal based on conventional approaches requires close patient contact to the(More)
Efforts towards Internet use as a means for public services are definitely increasing worldwide. In Sao Paulo State, Brazil, usability is considered an important factor to citizen-centric e-government. The dispersed nature of e-government development, by many different teams and the broad audience of internet makes user modeling an essential task for(More)
Kintense is a robust, accurate, real-time, and evolving system for detecting aggressive actions such as hitting, kicking, pushing, and throwing from streaming 3D skeleton joint coordinates obtained from Kinect sensors. Kintense uses a combination of: (1) an array of supervised learners to recognize a predefined set of aggressive actions, (2) an unsupervised(More)
Clinical evidence suggests that sleep pose analysis can shed light onto patient recovery rates and responses to therapies. In this work, we introduce a formulation that combines features from multimodal data to classify human sleep poses in an Intensive Care Unit (ICU) environment. As opposed to the current methods that combine data from multiple sensors to(More)
Manual analysis of body poses of bedridden patients requires staff to continuously track and record patient poses. Two limitations in the dissemination of pose-related therapies are scarce human resources and unreliable automated systems. This work addresses these issues by introducing a new method and a new system for robust automated classification of(More)
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