While the potential benefits of smart home technology are widely recognized, a lightweight design is needed for the benefits to be realized at a large scale. We introduce the CASAS “smart home in a box”, a lightweight smart home design that is easy to install and provides smart home capabilities out of the box with no customization or training. We discuss types of data analysis that have been performed by the CASAS group and can be pursued in the future by using this approach to designing and implementing smart home technologies.

Abstract-Due to an increased popularity of assistive healthcare technologies activity recognition has become one of the most widely studied problems in technology-driven assistive healthcare domain. Current approaches for smart-phone based activity recognition focus only on simple activities such as locomotion. In this paper, in addition to recognizing simple activities, we investigate the ability to recognize complex activities, such as cooking, cleaning, etc. through a smart phone. Features extracted from the raw inertial sensor data of the smart phone corresponding to the user's activities, are used to train and test supervised machine learning algorithms. The results from the experiments conducted on ten participants indicate that, in isolation, while simple activities can be easily recognized, the performance of the prediction models on complex activities is poor. However, the prediction model is robust enough to recognize simple activities even in the presence of complex activities.

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In experiments using a total of 144 albino rat subjects, the authors assessed the ability of fear-weakening treatments to prevent fear renewal (relapse). Conditioned suppression of operant behavior served as the measure of fear in an A-B-A (acquisition-treatment-test) renewal paradigm. In Experiment 1, 100 nonreinforced exposures to a feared cue during treatment (extinction) did not reduce fear renewal relative to 20 exposures. In Experiment 2, explicitly unpaired (EU) treatments thwarted both renewal and reacquisition. In Experiment 3, conditioned inhibition (CI) and differential conditioning (DC) treatments weakened renewal and resisted both reacquisition and a form of reinstatement. In Experiment 4, EU, DC, and CI treatments all thwarted renewal. Evidence suggested that the ability of the treatments to do so reflected the combined effects of transfer of extinction across treatment and test contexts and habituation to the unconditioned stimulus.