Suneeta Godbole

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Physical activity (PA) provides health benefits in older adults. Research suggests that exposure to nature and time spent outdoors may also have effects on health. Older adults are the least active segment of our population, and are likely to spend less time outdoors than other age groups. The relationship between time spent in PA, outdoor time, and various(More)
BACKGROUND Active travel is an important area in physical activity research, but objective measurement of active travel is still difficult. Automated methods to measure travel behaviors will improve research in this area. In this paper, we present a supervised machine learning method for transportation mode prediction from global positioning system (GPS)(More)
OBJECTIVE This study evaluated the effect of four active videogames (AVGs) varying in behavioral contingencies (behavior-consequence relations) on adolescent AVG play and overall activity levels over 4 weeks. MATERIALS AND METHODS Each AVG, manufactured by SSD/Xavix(®) (Shiseido Co. of Japan, Tokyo, Japan), was coded and scored for the number of positive(More)
Physical activity monitoring in free-living populations has many applications for public health research, weight-loss interventions, context-aware recommendation systems and assistive technologies. We present a system for physical activity recognition that is learned from a free-living dataset of 40 women who wore multiple sensors for seven days. The(More)
Wrist accelerometers are being used in population level surveillance of physical activity (PA) but more research is needed to evaluate their validity for correctly classifying types of PA behavior and predicting energy expenditure (EE). In this study we compare accelerometers worn on the wrist and hip, and the added value of heart rate (HR) data, for(More)
Numerous studies have demonstrated multiple health benefits of being outside and exposure to natural environments. It is essential to accurately measure the amount of time individuals spend outdoors to assess the impact of exposure to outdoor time on health. SenseCam is a wearable camera that automatically captures images. The annotated images provide an(More)
Machine learning techniques are used to improve accelerometer-based measures of physical activity. Most studies have used laboratory-collected data to develop algorithms to classify behaviors, but studies of free-living activity are needed to improve the ecological validity of these methods. With this aim, we collected a novel free-living dataset that uses(More)
We describe a study that aims to understand physical activity and sedentary behavior in free-living settings. We employed a wearable camera to record 3 to 5 days of imaging data with 40 participants, resulting in over 360,000 images. These images were then fully annotated by experienced staff with a rigorous coding protocol. We designed a deep learning(More)
BACKGROUND Excessive sitting has been linked to poor health. It is unknown whether reducing total sitting time or increasing brief sit-to-stand transitions is more beneficial. We conducted a randomized pilot study to assess whether it is feasible for working and non-working older adults to reduce these two different behavioral targets. METHODS Thirty(More)
Obesity is a major public health concern in the United States. Eating while doing other activities, including watching television can increase energy intake. However, to our knowledge, no studies have quantified and examined the eating context among adults during everyday life. Existing studies are limited because they rely predominantly on self-reported(More)