Tanvi Banerjee

Learn More
In this paper, we propose a tree based regression algorithm, (TREG) that addresses the problem of data compression in wireless sensor networks. By function approximation based on multivariable polynomial regression and passing only the coefficients returned by the regression function instead of aggregated data, TREG achieves the following goals: (1) the(More)
Wide adoption of smartphones and availability of low-cost sensors has resulted in seamless and continuous monitoring of physiology, environment, and public health notifications. However, personalized digital health and patient empowerment can become a reality only if the complex multisensory and multimodal data is processed within the patient context.(More)
In this paper, we present results of an automatic vision-based gait assessment tool, using two cameras. Elderly residents from TigerPlace, a retirement community, were recruited to participate in the validation and test of the system in scripted scenarios representing everyday activities. The residents were first tested on a GAITRite mat, an electronic(More)
We present an approach for activity state recognition implemented on data collected from various sensors—standard web cameras under normal illumination, web cameras using infrared lighting, and the inexpensive Microsoft Kinect camera system. Sensors such as the Kinect ensure that activity segmentation is possible during the daytime as well as night. This is(More)
We describe a novel technique to combine motion data with scene information to capture activity characteristics of older adults using a single Microsoft Kinect depth sensor. Specifically, we describe a method to learn activities of daily living (ADLs) and instrumental ADLs (IADLs) in order to study the behavior patterns of older adults to detect health(More)
13 Humanitarian and public institutions are increasingly relying on data from social media sites to measure 14 public attitude, and provide timely public engagement. Such engagement supports the exploration of 15 public views on important social issues such as gender-based violence (GBV). In this study, we examine 16 Big (Social) Data consisting of nearly(More)
Monitoring indoor air quality is critical because Americans spend 93% of their life indoors, and around 6.3 million children suffer from asthma. We want to passively and unobtrusively monitor the asthma patient’s environment to detect the presence of two asthma-exacerbating activities: smoking and cooking using the Foobot sensor. We propose a data-driven(More)
We present an approach for patient activity recognition in hospital rooms using depth data collected using a Kinect sensor. Depth sensors such as the Kinect ensure that activity segmentation is possible during day time as well as night while addressing the privacy concerns of patients. It also provides a technique to remotely monitor patients in a(More)
The purpose of this study was to test the implementation of a fall detection and "rewind" privacy-protecting technique using the Microsoft® Kinect™ to not only detect but prevent falls from occurring in hospitalized patients. Kinect sensors were placed in six hospital rooms in a step-down unit and data were continuously logged. Prior to implementation with(More)