Roberto Luis Shinmoto Torres

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—The increasing ageing population around the world and the increased risk of falling among this demographic, challenges society and technology to find better ways to mitigate the occurrence of such costly and detrimental events as falls. The most common activity associated with falls is bed transfers ; therefore, the most significant high risk activity.(More)
The development of human activity monitoring has allowed the creation of multiple applications, among them is the recognition of high falls risk activities of older people for the mitigation of falls occurrences. In this study, we apply a graphical model based classification technique(conditional random field) to evaluate various sliding window based(More)
Aging populations are increasing worldwide and strategies to minimize the impact of falls on older people need to be examined. Falls in hospitals are common and current hospital technological implementations use localized sensors on beds and chairs to alert caregivers of unsupervised patient ambulations; however, such systems have high false alarm rates. We(More)
The present study introduces a method for improving the classification performance of imbalanced multiclass data streams from wireless body worn sensors. Data imbalance is an inherent problem in activity recognition caused by the irregular time distribution of activities, which are sequential and dependent on previous movements. We use conditional random(More)
The utilization of whole grains in food formulations is nowadays recommended. Extrusion cooking allows obtaining precooked cereal products and a wide range of ready-to-eat foods. Two rice varieties having different amylose content (Fortuna 16% and Paso 144, 27%) were extruded using a Brabender single screw extruder. Factorial experimental design was used to(More)
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