A Study of Detecting Social Interaction with Sensors in a Nursing Home Environment.pdfVIP

A Study of Detecting Social Interaction with Sensors in a Nursing Home Environment.pdf

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A Study of Detecting Social Interaction with Sensors in a Nursing Home Environment

A Study of Detecting Social Interaction with Sensors in a Nursing Home Environment Datong Chen, Jie Yang, and Howard Wactlar School of Computer Science, Carnegie Mellon University {datong,yang+,hdw}@ Abstract. Social interaction plays an important role in our daily lives. It is one of the most important indicators of physical or mental diseases of aging pa- tients. In this paper, we present a Wizard of Oz study on the feasibility of de- tecting social interaction with sensors in skilled nursing facilities. Our study ex- plores statistical models that can be constructed to monitor and analyze social interactions among aging patients and nurses. We are also interested in identify- ing sensors that might be most useful in interaction detection; and determining how robustly the detection can be performed with noisy sensors. We simulate a wide range of plausible sensors using human labeling of audio and visual data. Based on these simulated sensors, we build statistical models for both individ- ual sensors and combinations of multiple sensors using various machine learn- ing methods. Comparison experiments are conducted to demonstrate the effec- tiveness and robustness of the sensors and statistical models for detecting interactions. 1 Introduction The worldwide population over age 65 is expected to more than double from 357 million in 1990 to 761 million by 2025 [17]. At present, five percent of Americans over age 65 reside in nursing homes, with up to 50 percent of those over the age of 85 likely being placed in a nursing home at some point in their lives [13]. Among these nursing home residents, about 80% of them are believed to suffer from a psychiatric

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