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Recognition Model for Activity Classification in Everyday Movements in the Context of Dementia Diagnostics - Cooking
Get PDFBy monitoring movements and activities, the progression of neurological diseases
can bedetected. The documentation required for this is associated with a high level of
effort, which is hardly possible in view of the increasing shortage of nursing staff. In
ordertograduallyrelievethenursingstaff, wearedevelopinganapproachtoautomate
documentation in cooperation with two dementiaresidential communities. The aim of
this work is to facilitate everyday life of caregivers. Previous research results from this
working group show that everyday activities of dementia patients can be recognized
well by combining smartwatch sensor technology and machine learning. However,
the state of research has gaps when it comes to recognize activities consisting of a
variety of movement patterns. In this paper, we present an approach to classify the
activity of cooking. We divide this activity into several sub-activities each consisting
of a distinct motion pattern that a recurrent network recognizes. This is followed by
a model for calculating the probability that cooking actually occurred based on the
different sub-activities recognized. We show the advantages of different smartwatch
sensor combinations and compare the different approaches of our model with the
prediction accuracy of the classification. This model can later be integrated into the
care documentation of the residential communities in addition to the activities that
are easier to recognize.Published Versio
Improving the Processing Efficiency of Femtosecond Laser Sulfur Hyperdoping of Silicon by Diffractive Beam Shaping
No full textPublished Versio
Second Victims among German Emergency Medical Services Physicians (SeViD-III-Study)
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Importance of catchment hydrological processes and calibration of hydrological‐hydrodynamic rainfall‐runoff models in small rural catchments
Get PDFGefördert im Rahmen des Projekts DEALPublished Versio
Human factors and political price regulations to enhance electric vehicle miles traveled
Get PDFA shift to electric vehicles is necessary for transport decarbonization and requires the
consideration of human factors in the design of political regulations. By applying the
Theory of Planned Behavior this research identifies key motivational determinants of
the decision to state a higher share of electric vehicle miles traveled. In a stated adaptation
experiment, respondents were confronted with new price regulations and could
adapt all mobility tools in their household, e.g. include an electric vehicle, and specify
the annual vehicle miles traveled. The results of a structural equation model on data
of 424 respondents show that the stated proportion of electric vehicle miles traveled
is higher with a person’s greater intention to buy an electric vehicle, while the intention
itself is predicted by a person’s attitude, subjective norm, and perceived behavior
control of buying an electric vehicle.Published Versio
Will China’s three-child policy defuse the demographic time bomb?
Get PDFChina is undergoing a particularly fast demographic transition. Accelerated through decades of political restrictions on family planning, the median age is rising and there is a growing share of retirees, while labour force potential is declining. Faced with dire consequences for both economic growth and wealth distribution, the government has gradually relaxed its one-child policy. Will this policy shift succeed? Our study simulates China's old-age dependency ratio and total dependency ratio until the end of the century, assuming total fertility rates between 1.0 and 2.0 with constant and increasing life expectancy. It shows that both ratios would substantially increase even in the best case. Therefore, China urgently needs reforms beyond family policy.Published Versio
