8 accepted papers
Many robot caregiving tasks, such as bathing, dressing, and transferring, require a robot arm to make contact with a human body at multiple points rather than solely at the end effector. However, varied human touch preferences can lead to unsafe or uncomfortable multi-contact interactions. To addres…
Robot-assisted bite acquisition involves picking up food items with varying shapes, compliance, sizes, and textures. Fully autonomous strategies may not generalize efficiently across this diversity. We propose leveraging feedback from the care recipient when encountering novel food items. However, f
Abnormal heart sounds may have diverse frequency characteristics depending upon underlying pathological conditions. Designing a binary classifier for predicting normal and abnormal heart sounds using supervised learning requires a lot of training data, covering different types of cardiac abnormaliti…
In this work, we present a data-driven simulation and training engine capable of learning end-to-end autonomous vehicle control policies using only sparse rewards. By leveraging real, human-collected trajectories through an environment, we render novel training data that allows virtual agents to dri
In this work, we present MapLite: a one-click autonomous navigation system capable of piloting a vehicle to an arbitrary desired destination point given only a sparse publicly available topometric map (from OpenStreetMap). The onboard sensors are used to segment the road region and register the topo
In this paper we propose a feature extraction algorithm for classifying Coronary Artery Disease (CAD) patients from Photoplethysmogram (PPG) signals. Several domain-independent features, representing inherent properties of a time series are explored in our study. These are combined with Heart Rate V…
This paper presents a demo proposal of a standalone smartphone application that can automatically analyse the signal quality of PCG, as it is recorded on a low-cost smartphone-based digital stethoscope. Features, related to the inherent pattern of the autocorrelated signal envelope, have been used f…
Photoplethysmography (PPG) signals, captured using smart phones are generally noisy in nature. Although they have been successfully used to determine heart rate from frequency domain analysis, further indirect markers like blood pressure (BP) require time domain analysis for which the signal needs t…