In this paper, we describe two longitudinal studies in which fall detection sensor technology was tested in the homes of older adults. The first study tested Doppler radar, a two-webcam system, and a depth camera system in ten apartments for two years. This continuous data collection allowed us to investigate the real-world setting of target users and compare the advantages and limitations of each sensor modality. Based on this study, the depth camera was chosen for a current ongoing study in which depth camera systems have been installed in 94 additional older adult apartments. We include a discussion of the different sensor systems, the pros and cons of each, and results of the fall detection and false alarms in the older adult homes.

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Mechanisms for highly efficient chromosome-associated equal segregation, and for maintenance of steady state copy number, are at the heart of the evolutionary success of the 2-micron plasmid as a stable multi-copy extra-chromosomal selfish DNA element present in the yeast nucleus. The Flp site-specific recombination system housed by the plasmid, which is central to plasmid copy number maintenance, is regulated at multiple levels. Transcription of the FLP gene is fine-tuned by the repressor function of the plasmid-coded partitioning proteins Rep1 and Rep2 and their antagonist Raf1, which is also plasmid-coded. In addition, the Flp protein is regulated by the host’s post-translational modification machinery. Utilizing a Flp-SUMO fusion protein, which functionally mimics naturally sumoylated Flp, we demonstrate that the modification signals ubiquitination of Flp, followed by its proteasome-mediated degradation. Furthermore, reduced binding affinity and cooperativity of the modified Flp decrease its association with the plasmid FRT (Flp recombination target) sites, and/or increase its dissociation from them. The resulting attenuation of strand cleavage and recombination events safeguards against runaway increase in plasmid copy number, which is deleterious to the host—and indirectly—to the plasmid. These results have broader relevance to potential mechanisms by which selfish genomes minimize fitness conflicts with host genomes by holding in check the extra genetic load they pose.

A multiple instance dictionary learning approach, dictionary learning using functions of multiple instances (DL-FUMI), is used to perform beat-to-beat heart rate estimation and to characterize heartbeat signatures from ballistocardiogram (BCG) signals collected with a hydraulic bed sensor. DL-FUMI estimates a "heartbeat concept" that represents an individual's personal ballistocardiogram heartbeat pattern. DL-FUMI formulates heartbeat detection and heartbeat characterization as a multiple instance learning problem to address the uncertainty inherent in aligning BCG signals with ground truth during training. Experimental results show that the estimated heartbeat concept obtained by DL-FUMI is an effective heartbeat prototype and achieves superior performance over comparison algorithms.

We propose in this paper an effective method to obtain the pulse rate from a hydraulic sensor that is placed under the mattress. The sensor captures the superposition of the ballistocardiogram (BCG) and the respiration signals. The BCG is modeled as the j-peak with a frequency modulation component. The proposed method utilizes the Hilbert transform to effectively capture the j-peak, which allows the pulse rate information to come out distinctively in the frequency domain. Among the five subjects tested, the error in pulse rate estimation is less than 1%.